{"capsules":[{"id":"bdb67173-d9f9-5f0b-a5b1-ba41c29c01c5","title":"Ukraine Border and Regional Resilience","type":"KNOWLEDGE","tags":["europe","public-knowledge","romania","source-backed"],"trust_level":100,"trust_score":0.92,"verification_status":"sources_verified","evidence_level":"institutional","quality_status":"curated","curation_status":"verified","provenance_status":"valid","valid_until":"2026-08-19T00:00:00+00:00","source_url":"https://www.nato.int/content/what-is-nato/en.html","sources_cited":["https://www.nato.int/content/what-is-nato/en.html","https://www.oecd.org/en/publications/oecd-economic-surveys-romania-2026_4844067e-en.html"],"answer_eligible":true,"contains_disputed_claims":false,"reliability_tier":"high","reliability_reasons":["specific_source"],"source_url_specificity":"specific_source","requires_reverification":false,"content_hash":"976a49ea53215fc706ca10084068b7997acda981506e126a3404d4f638b84278","owner":"system","created_at":"2026-05-21T11:27:02.065Z","snippet":"Romania borders Ukraine, so the war next door affects transport, refugees, grain routes, airspace, border communities, energy, defence planning, and Black Sea security. The border also makes Romania important for humanitarian support and regional resilience.\n\nStudent takeaway: Romania's border with Ukraine makes humanitarian, transport, airspace, grain, energy, and security questions part of everyday regional policy.\n\nTeacher note: Use this europe topic to connect one clear claim to its cited evidence, then ask learners what the source proves and what it does not prove.","content_length":576,"entry_protection":{"status":"protected","label":"ATIS + seven-phase checked","message":"This capsule has persisted ATIS and seven-phase entry-pipeline markers.","pipeline_required":true,"atis_required":true,"pipeline":{"completed":true,"phase_count":7,"required_phase_count":7,"phases":["ingestion","analysis","validation","consensus","execution","propagation","settlement"],"completed_at":"2026-06-01T13:22:08.039416+00:00"},"atis":{"checked":true,"decision":"allow","checked_at":"2026-06-01T13:22:08.036721+00:00"}},"preview_is_truncated":false,"freshness_status":"current"},{"id":"320fd9d3-3fda-54a1-9523-d0b297489a51","title":"STEM Strengths and Talent Retention","type":"KNOWLEDGE","tags":["education","public-knowledge","romania","source-backed"],"trust_level":100,"trust_score":0.92,"verification_status":"sources_verified","evidence_level":"institutional","quality_status":"curated","curation_status":"verified","provenance_status":"valid","valid_until":"2026-08-19T00:00:00+00:00","source_url":"https://op.europa.eu/webpub/eac/education-and-training-monitor/en/country-reports/romania.html","sources_cited":["https://op.europa.eu/webpub/eac/education-and-training-monitor/en/country-reports/romania.html","https://digital-strategy.ec.europa.eu/en/factpages/romania-2025-digital-decade-country-report"],"answer_eligible":true,"contains_disputed_claims":false,"reliability_tier":"high","reliability_reasons":["specific_source"],"source_url_specificity":"specific_source","requires_reverification":false,"content_hash":"902cd86cb6ea8a20f6953955cb9865c0d8a31f73348ca1b5ceeaea0964fe7cb1","owner":"system","created_at":"2026-05-21T11:26:37.03Z","snippet":"Romania has a notable STEM profile in higher education, but participation alone does not solve skills needs. EU monitoring points to basic-skills weaknesses, teacher-training needs, fewer STEM graduates per young population than the EU average, and the challenge of keeping talent in productive local ecosystems.\n\nStudent takeaway: Romania has high STEM participation shares in higher education, but fewer STEM graduates per young population and ongoing talent-retention challenges.\n\nTeacher note: Use this education topic to connect one clear claim to its cited evidence, then ask learners what the source proves and what it does not prove.","content_length":641,"entry_protection":{"status":"protected","label":"ATIS + seven-phase checked","message":"This capsule has persisted ATIS and seven-phase entry-pipeline markers.","pipeline_required":true,"atis_required":true,"pipeline":{"completed":true,"phase_count":7,"required_phase_count":7,"phases":["ingestion","analysis","validation","consensus","execution","propagation","settlement"],"completed_at":"2026-06-01T13:21:47.961374+00:00"},"atis":{"checked":true,"decision":"allow","checked_at":"2026-06-01T13:21:47.958684+00:00"}},"preview_is_truncated":false,"freshness_status":"current"},{"id":"951b3228-9f2e-5f3a-8a02-7bcdcec51586","title":"Education Reform and Skills Gaps","type":"KNOWLEDGE","tags":["education","public-knowledge","romania","source-backed"],"trust_level":100,"trust_score":0.92,"verification_status":"sources_verified","evidence_level":"institutional","quality_status":"curated","curation_status":"verified","provenance_status":"valid","valid_until":"2026-08-19T00:00:00+00:00","source_url":"https://op.europa.eu/webpub/eac/education-and-training-monitor/en/country-reports/romania.html","sources_cited":["https://op.europa.eu/webpub/eac/education-and-training-monitor/en/country-reports/romania.html","https://www.oecd.org/en/publications/oecd-economic-surveys-romania-2026_4844067e-en.html"],"answer_eligible":true,"contains_disputed_claims":false,"reliability_tier":"high","reliability_reasons":["specific_source"],"source_url_specificity":"specific_source","requires_reverification":false,"content_hash":"526e45991470ece3e66a3ae0e4cde8ef86735b1fcbaf72794238f8a32495ebbb","owner":"system","created_at":"2026-05-21T11:26:34.067Z","snippet":"The EU Education and Training Monitor 2025 says Romania has started broad education reform supported by EU funds. It also identifies persistent problems: basic-skills gaps, early school leaving, low adult-learning participation, rural-urban inequality, and the need for labour-market-relevant skills.\n\nStudent takeaway: EU monitoring says Romania has begun broad education reform but still faces basic-skills, early-school-leaving, adult-learning, and rural-urban equity gaps.\n\nTeacher note: Use this education topic to connect one clear claim to its cited evidence, then ask learners what the source proves and what it does not prove.","content_length":635,"entry_protection":{"status":"protected","label":"ATIS + seven-phase checked","message":"This capsule has persisted ATIS and seven-phase entry-pipeline markers.","pipeline_required":true,"atis_required":true,"pipeline":{"completed":true,"phase_count":7,"required_phase_count":7,"phases":["ingestion","analysis","validation","consensus","execution","propagation","settlement"],"completed_at":"2026-06-01T13:21:45.085571+00:00"},"atis":{"checked":true,"decision":"allow","checked_at":"2026-06-01T13:21:45.083118+00:00"}},"preview_is_truncated":false,"freshness_status":"current"},{"id":"e23714c7-37b4-5477-8f11-d98a9afc5ec5","title":"Early Medieval Crossroads","type":"KNOWLEDGE","tags":["history","public-knowledge","romania","source-backed"],"trust_level":95,"trust_score":0.92,"verification_status":"sources_verified","evidence_level":"institutional","quality_status":"curated","curation_status":"verified","provenance_status":"valid","valid_until":"2027-05-21T00:00:00+00:00","source_url":"https://cic.cdep.ro/en/prezentare/parlament","sources_cited":["https://cic.cdep.ro/en/prezentare/parlament"],"answer_eligible":true,"contains_disputed_claims":false,"reliability_tier":"high","reliability_reasons":["specific_source"],"source_url_specificity":"specific_source","requires_reverification":false,"content_hash":"8427ec9364dfd615cbfeb0008d23e04525279ae5180ecbb6c6bbc6a35618be21","owner":"system","created_at":"2026-05-21T11:23:26.434Z","snippet":"After Roman withdrawal, the lands that are now Romania became a meeting ground for Slavic, Turkic, Magyar, Byzantine, steppe, and local communities. This period is difficult to reduce to a single national story; it is better understood as a frontier zone where trade, migration, Christian traditions, and military pressure shaped later regional identities.\n\nStudent takeaway: The territory of present-day Romania sat between empires, migration routes, trade corridors, and frontier communities before modern states formed.\n\nTeacher note: Use this history topic to connect one clear claim to its cited evidence, then ask learners what the source proves and what it does not prove.","content_length":679,"entry_protection":{"status":"protected","label":"ATIS + seven-phase checked","message":"This capsule has persisted ATIS and seven-phase entry-pipeline markers.","pipeline_required":true,"atis_required":true,"pipeline":{"completed":true,"phase_count":7,"required_phase_count":7,"phases":["ingestion","analysis","validation","consensus","execution","propagation","settlement"],"completed_at":"2026-06-01T13:18:42.018814+00:00"},"atis":{"checked":true,"decision":"allow","checked_at":"2026-06-01T13:18:42.016820+00:00"}},"preview_is_truncated":false,"freshness_status":"current"},{"id":"b80855c7-34eb-5a9b-815a-1cf8764a5b21","title":"Radio Romania: Interim Government Status","type":"KNOWLEDGE","tags":["caretaker-government","public-knowledge","romania","source","source-backed"],"trust_level":90,"trust_score":0.9,"verification_status":"sources_verified","evidence_level":"institutional","quality_status":"curated","curation_status":"verified","provenance_status":"valid","valid_until":"2026-08-19T00:00:00+00:00","source_url":"https://www.rri.ro/en/news-and-current-affairs/newsflash/may-8-2026-id1015203.html","sources_cited":["https://www.rri.ro/en/news-and-current-affairs/newsflash/may-8-2026-id1015203.html"],"answer_eligible":true,"contains_disputed_claims":false,"reliability_tier":"high","reliability_reasons":["specific_source"],"source_url_specificity":"specific_source","requires_reverification":false,"content_hash":"e3dc84979831d04ce8e6596eb0b83c76c792ac7890edacbd20ee3420ac9e38bb","owner":"system","created_at":"2026-05-21T11:23:10.798Z","snippet":"Radio Romania International's 8 May 2026 newsflash explains that the caretaker cabinet had limited powers after the no-confidence motion, including limits on decrees, bills, and new reform policies.\n\nStudent takeaway: This source anchor shows where readers can verify the facts before repeating them.\n\nTeacher note: Ask learners which claim this source can support and which questions need a different source.","content_length":409,"entry_protection":{"status":"protected","label":"ATIS + seven-phase checked","message":"This capsule has persisted ATIS and seven-phase entry-pipeline markers.","pipeline_required":true,"atis_required":true,"pipeline":{"completed":true,"phase_count":7,"required_phase_count":7,"phases":["ingestion","analysis","validation","consensus","execution","propagation","settlement"],"completed_at":"2026-06-01T13:18:21.335041+00:00"},"atis":{"checked":true,"decision":"allow","checked_at":"2026-06-01T13:18:21.333242+00:00"}},"preview_is_truncated":false,"freshness_status":"current"},{"id":"a8f66cbc-0285-5cd5-9e7f-f4393f462dda","title":"EU Digital Decade 2025: Romania","type":"KNOWLEDGE","tags":["digital-decade","public-knowledge","romania","source","source-backed"],"trust_level":90,"trust_score":0.9,"verification_status":"sources_verified","evidence_level":"institutional","quality_status":"curated","curation_status":"verified","provenance_status":"valid","valid_until":"2026-08-19T00:00:00+00:00","source_url":"https://digital-strategy.ec.europa.eu/en/factpages/romania-2025-digital-decade-country-report","sources_cited":["https://digital-strategy.ec.europa.eu/en/factpages/romania-2025-digital-decade-country-report"],"answer_eligible":true,"contains_disputed_claims":false,"reliability_tier":"high","reliability_reasons":["specific_source"],"source_url_specificity":"specific_source","requires_reverification":false,"content_hash":"6aef2c9e73c00bcf005c9950ad0e446804c23b900daa94280e3f3cce8787a60c","owner":"system","created_at":"2026-05-21T11:22:52.454Z","snippet":"The 2025 Digital Decade country report describes Romania's strong fixed connectivity and technology assets, while also identifying weak SME digitalisation, limited emerging-technology uptake, low digital skills, and persistent R&D and innovation gaps.\n\nStudent takeaway: This source anchor shows where readers can verify the facts before repeating them.\n\nTeacher note: Ask learners which claim this source can support and which questions need a different source.","content_length":462,"entry_protection":{"status":"protected","label":"ATIS + seven-phase checked","message":"This capsule has persisted ATIS and seven-phase entry-pipeline markers.","pipeline_required":true,"atis_required":true,"pipeline":{"completed":true,"phase_count":7,"required_phase_count":7,"phases":["ingestion","analysis","validation","consensus","execution","propagation","settlement"],"completed_at":"2026-06-01T13:18:02.762909+00:00"},"atis":{"checked":true,"decision":"allow","checked_at":"2026-06-01T13:18:02.760168+00:00"}},"preview_is_truncated":false,"freshness_status":"current"},{"id":"a8c33d9f-1607-5b53-a409-392426e86a3b","title":"EU Education and Training Monitor 2025: Romania","type":"KNOWLEDGE","tags":["education-monitor","public-knowledge","romania","source","source-backed"],"trust_level":90,"trust_score":0.9,"verification_status":"sources_verified","evidence_level":"institutional","quality_status":"curated","curation_status":"verified","provenance_status":"valid","valid_until":"2026-08-19T00:00:00+00:00","source_url":"https://op.europa.eu/webpub/eac/education-and-training-monitor/en/country-reports/romania.html","sources_cited":["https://op.europa.eu/webpub/eac/education-and-training-monitor/en/country-reports/romania.html"],"answer_eligible":true,"contains_disputed_claims":false,"reliability_tier":"high","reliability_reasons":["specific_source"],"source_url_specificity":"specific_source","requires_reverification":false,"content_hash":"82e05c645d46d948bc49f21a1e2f27ad3d38606378e63221cde3fa24dec20de4","owner":"system","created_at":"2026-05-21T11:22:49.127Z","snippet":"The EU Education and Training Monitor 2025 country report describes Romania's education reform, STEM participation, basic-skills gaps, early school leaving, vocational education, higher education participation, adult learning, and rural-urban equity challenges.\n\nStudent takeaway: This source anchor shows where readers can verify the facts before repeating them.\n\nTeacher note: Ask learners which claim this source can support and which questions need a different source.","content_length":472,"entry_protection":{"status":"protected","label":"ATIS + seven-phase checked","message":"This capsule has persisted ATIS and seven-phase entry-pipeline markers.","pipeline_required":true,"atis_required":true,"pipeline":{"completed":true,"phase_count":7,"required_phase_count":7,"phases":["ingestion","analysis","validation","consensus","execution","propagation","settlement"],"completed_at":"2026-06-01T13:17:59.561735+00:00"},"atis":{"checked":true,"decision":"allow","checked_at":"2026-06-01T13:17:59.559662+00:00"}},"preview_is_truncated":false,"freshness_status":"current"},{"id":"dde47b26-51fa-55f2-a80b-a80591dc4783","title":"OECD Economic Survey: Romania 2026","type":"KNOWLEDGE","tags":["oecd-survey","public-knowledge","romania","source","source-backed"],"trust_level":90,"trust_score":0.9,"verification_status":"sources_verified","evidence_level":"institutional","quality_status":"curated","curation_status":"verified","provenance_status":"valid","valid_until":"2026-08-19T00:00:00+00:00","source_url":"https://www.oecd.org/en/publications/oecd-economic-surveys-romania-2026_4844067e-en.html","sources_cited":["https://www.oecd.org/en/publications/oecd-economic-surveys-romania-2026_4844067e-en.html"],"answer_eligible":true,"contains_disputed_claims":false,"reliability_tier":"high","reliability_reasons":["specific_source"],"source_url_specificity":"specific_source","requires_reverification":false,"content_hash":"044ce8269d317e0d5bc9f6b55e4fef0e99cd817b36462582afe20ab257245364","owner":"system","created_at":"2026-05-21T11:22:46.136Z","snippet":"The OECD Economic Survey: Romania 2026 reviews fiscal sustainability, competitiveness, employment, demographic pressure, education and skills, health, labour participation, infrastructure, climate risk, and the reform agenda connected with Romania's OECD accession process.\n\nStudent takeaway: This source anchor shows where readers can verify the facts before repeating them.\n\nTeacher note: Ask learners which claim this source can support and which questions need a different source.","content_length":484,"entry_protection":{"status":"protected","label":"ATIS + seven-phase checked","message":"This capsule has persisted ATIS and seven-phase entry-pipeline markers.","pipeline_required":true,"atis_required":true,"pipeline":{"completed":true,"phase_count":7,"required_phase_count":7,"phases":["ingestion","analysis","validation","consensus","execution","propagation","settlement"],"completed_at":"2026-06-01T13:17:56.457200+00:00"},"atis":{"checked":true,"decision":"allow","checked_at":"2026-06-01T13:17:56.455112+00:00"}},"preview_is_truncated":false,"freshness_status":"current"},{"id":"183c39f2-b7a9-5c8c-ba8d-9680a6357dd4","title":"European Commission Schengen Membership Note","type":"KNOWLEDGE","tags":["public-knowledge","romania","schengen-full","source","source-backed"],"trust_level":95,"trust_score":0.92,"verification_status":"sources_verified","evidence_level":"institutional","quality_status":"curated","curation_status":"verified","provenance_status":"valid","valid_until":"2026-08-19T00:00:00+00:00","source_url":"https://home-affairs.ec.europa.eu/news/bulgaria-and-romania-join-schengen-area-2025-01-03_en","sources_cited":["https://home-affairs.ec.europa.eu/news/bulgaria-and-romania-join-schengen-area-2025-01-03_en"],"answer_eligible":true,"contains_disputed_claims":false,"reliability_tier":"high","reliability_reasons":["specific_source"],"source_url_specificity":"specific_source","requires_reverification":false,"content_hash":"964ed8bf250dae538436aeb4c835999e8cbb63d991200902d94ec2ba8fcc0442","owner":"system","created_at":"2026-05-21T11:22:30.732Z","snippet":"The European Commission Schengen membership note records the final land-border step in Romania's Schengen integration. Romania and Bulgaria had already entered Schengen arrangements for air and sea travel in 2024; beginning 1 January 2025, checks at internal land borders with and between the two countries were lifted.\n\nStudent takeaway: This source anchor shows where readers can verify the facts before repeating them.\n\nTeacher note: Ask learners which claim this source can support and which questions need a different source.","content_length":530,"entry_protection":{"status":"protected","label":"ATIS + seven-phase checked","message":"This capsule has persisted ATIS and seven-phase entry-pipeline markers.","pipeline_required":true,"atis_required":true,"pipeline":{"completed":true,"phase_count":7,"required_phase_count":7,"phases":["ingestion","analysis","validation","consensus","execution","propagation","settlement"],"completed_at":"2026-06-01T13:17:41.969463+00:00"},"atis":{"checked":true,"decision":"allow","checked_at":"2026-06-01T13:17:41.967697+00:00"}},"preview_is_truncated":false,"freshness_status":"current"},{"id":"f93585f9-dc89-4f07-bf5b-de2dbdfe4e50","title":"Agent JIT Compilation for Latency-Optimizing Web Agent Planning and Scheduling","type":null,"tags":["cs.LG","cs.AI"],"trust_level":40,"trust_score":0.4,"verification_status":"source_linked","evidence_level":"primary_source","quality_status":"source_backed","curation_status":null,"provenance_status":null,"valid_until":"2026-08-30T05:12:35.813944+00:00","source_url":"https://arxiv.org/abs/2605.21470v1","sources_cited":["https://arxiv.org/abs/2605.21470v1"],"answer_eligible":true,"contains_disputed_claims":false,"reliability_tier":"medium","reliability_reasons":["specific_source"],"source_url_specificity":"specific_source","requires_reverification":false,"content_hash":null,"owner":"system:arxiv-ingestion","created_at":"2026-05-21T06:00:06.286Z","snippet":"# Agent JIT Compilation for Latency-Optimizing Web Agent Planning and Scheduling\n\n**Authors:** Caleb Winston, Ron Yifeng Wang, Azalia Mirhoseini, Christos Kozyrakis\n**arXiv:** https://arxiv.org/abs/2605.21470v1\n**Published:** 2026-05-20T17:54:27Z\n\n## Abstract\nComputer-use agents (CUA) automate tasks specified with natural language such as \"order the cheapest item from Taco Bell\" by generating sequences of calls to tools such as click, type, and scroll on a browser. Current implementations follow a sequential fetch-screenshot-execute loop where each iteration requires an LLM call, resulting in high latency and frequent errors from incorrect tool use. We present agent just-in-time (JIT) compilation, an alternative that compiles task descriptions directly into executable code that is free to ","content_length":1525,"entry_protection":{"status":"legacy_public","label":"Legacy public-safe capsule","message":"This capsule is eligible for public retrieval, but it predates persisted ATIS and seven-phase entry markers. New capsule entries require both.","pipeline_required":true,"atis_required":true,"pipeline":{"completed":false,"phase_count":0,"required_phase_count":7,"phases":["ingestion","analysis","validation","consensus","execution","propagation","settlement"],"completed_at":null},"atis":{"checked":false,"decision":null,"checked_at":null}},"preview_is_truncated":true,"freshness_status":"current"},{"id":"c8d79860-ff62-4a89-aa55-4c59190c3d93","title":"Is Fixing Schema Graphs Necessary? Full-Resolution Graph Structure Learning for Relational Deep Learning","type":null,"tags":["cs.LG"],"trust_level":75,"trust_score":0.75,"verification_status":"source_linked","evidence_level":"primary_source","quality_status":"source_backed","curation_status":null,"provenance_status":null,"valid_until":"2026-08-30T05:12:35.686160+00:00","source_url":"https://arxiv.org/abs/2605.21475v1","sources_cited":["https://arxiv.org/abs/2605.21475v1"],"answer_eligible":true,"contains_disputed_claims":false,"reliability_tier":"medium","reliability_reasons":["specific_source"],"source_url_specificity":"specific_source","requires_reverification":false,"content_hash":null,"owner":"system:arxiv-ingestion","created_at":"2026-05-21T06:00:06.275Z","snippet":"# Is Fixing Schema Graphs Necessary? Full-Resolution Graph Structure Learning for Relational Deep Learning\n\n**Authors:** Yi Huang, Qingyun Sun, Jia Li, Xingcheng Fu, Jianxin Li\n**arXiv:** https://arxiv.org/abs/2605.21475v1\n**Published:** 2026-05-20T17:56:09Z\n\n## Abstract\nRelational prediction tasks are fundamental in many real-world applications, where data are naturally stored in relational databases (RDBs). Relational Deep Learning (RDL) addresses this problem by modeling RDBs as graphs and applying graph neural networks (GNNs) for end-to-end learning. However, the full-resolution property is commonly adopted as a design principle in graph construction for RDBs to preserve relational semantics, which leads most existing methods to rely on fixed graph structures. In this paper, we propose","content_length":1536,"entry_protection":{"status":"legacy_public","label":"Legacy public-safe capsule","message":"This capsule is eligible for public retrieval, but it predates persisted ATIS and seven-phase entry markers. New capsule entries require both.","pipeline_required":true,"atis_required":true,"pipeline":{"completed":false,"phase_count":0,"required_phase_count":7,"phases":["ingestion","analysis","validation","consensus","execution","propagation","settlement"],"completed_at":null},"atis":{"checked":false,"decision":null,"checked_at":null}},"preview_is_truncated":true,"freshness_status":"current"},{"id":"fd31e8fe-f442-41aa-9655-f06320c7c5a9","title":"WikiVQABench: A Knowledge-Grounded Visual Question Answering Benchmark from Wikipedia and Wikidata","type":null,"tags":["cs.CV","cs.AI"],"trust_level":80,"trust_score":0.8,"verification_status":"source_linked","evidence_level":"primary_source","quality_status":"source_backed","curation_status":null,"provenance_status":null,"valid_until":"2026-08-30T05:12:35.553089+00:00","source_url":"https://arxiv.org/abs/2605.21479v1","sources_cited":["https://arxiv.org/abs/2605.21479v1"],"answer_eligible":true,"contains_disputed_claims":false,"reliability_tier":"medium","reliability_reasons":["specific_source"],"source_url_specificity":"specific_source","requires_reverification":false,"content_hash":null,"owner":"system:arxiv-ingestion","created_at":"2026-05-21T06:00:06.267Z","snippet":"# WikiVQABench: A Knowledge-Grounded Visual Question Answering Benchmark from Wikipedia and Wikidata\n\n**Authors:** Basel Shbita, Pengyuan Li, Anna Lisa Gentile\n**arXiv:** https://arxiv.org/abs/2605.21479v1\n**Published:** 2026-05-20T17:58:24Z\n\n## Abstract\nVisual Question Answering (VQA) benchmarks have largely emphasized perception-based tasks that can be solved from visual content alone. In contrast, many real-world scenarios require external knowledge that is not directly observable in the image to answer correctly. We introduce WikiVQABench, a human-curated knowledge-grounded VQA benchmark constructed by systematically combining Wikipedia images, their associated article captions, and structured knowledge from Wikidata. Our pipeline uses large language models (LLMs) to generate candidate","content_length":1540,"entry_protection":{"status":"legacy_public","label":"Legacy public-safe capsule","message":"This capsule is eligible for public retrieval, but it predates persisted ATIS and seven-phase entry markers. New capsule entries require both.","pipeline_required":true,"atis_required":true,"pipeline":{"completed":false,"phase_count":0,"required_phase_count":7,"phases":["ingestion","analysis","validation","consensus","execution","propagation","settlement"],"completed_at":null},"atis":{"checked":false,"decision":null,"checked_at":null}},"preview_is_truncated":true,"freshness_status":"current"},{"id":"3e82f301-2023-4c1a-9ab0-b4ca864f538e","title":"AiraXiv: An AI-Driven Open-Access Platform for Human and AI Scientists","type":null,"tags":["cs.AI","cs.CL","cs.LG"],"trust_level":40,"trust_score":0.4,"verification_status":"source_linked","evidence_level":"primary_source","quality_status":"source_backed","curation_status":null,"provenance_status":null,"valid_until":"2026-08-30T05:12:35.388520+00:00","source_url":"https://arxiv.org/abs/2605.21481v1","sources_cited":["https://arxiv.org/abs/2605.21481v1","https://airaxiv.com"],"answer_eligible":true,"contains_disputed_claims":false,"reliability_tier":"medium","reliability_reasons":["specific_source"],"source_url_specificity":"specific_source","requires_reverification":false,"content_hash":null,"owner":"system:arxiv-ingestion","created_at":"2026-05-21T06:00:06.253Z","snippet":"# AiraXiv: An AI-Driven Open-Access Platform for Human and AI Scientists\n\n**Authors:** Junshu Pan, Panzhong Lu, Yixuan Weng, Qiyao Sun, Fang Guo\n**arXiv:** https://arxiv.org/abs/2605.21481v1\n**Published:** 2026-05-20T17:59:03Z\n\n## Abstract\nRecent advances in artificial intelligence (AI) have accelerated the growth of both human-authored and AI-generated research outputs, placing increasing strain on traditional academic publishing systems and challenging the scalability of conference- and journal-centered paradigms amid rising submission volumes, reviewer workload, and venue size. To address these challenges, we explore an AI-era publishing paradigm in which both human and AI scientists participate as authors and readers, and papers evolve through continuous, feedback-driven iteration. We ","content_length":1335,"entry_protection":{"status":"legacy_public","label":"Legacy public-safe capsule","message":"This capsule is eligible for public retrieval, but it predates persisted ATIS and seven-phase entry markers. New capsule entries require both.","pipeline_required":true,"atis_required":true,"pipeline":{"completed":false,"phase_count":0,"required_phase_count":7,"phases":["ingestion","analysis","validation","consensus","execution","propagation","settlement"],"completed_at":null},"atis":{"checked":false,"decision":null,"checked_at":null}},"preview_is_truncated":true,"freshness_status":"current"},{"id":"13ade54f-3eff-49cb-a976-c4749d2d5a16","title":"DeepWeb-Bench: A Deep Research Benchmark Demanding Massive Cross-Source Evidence and Long-Horizon Derivation","type":null,"tags":["cs.AI"],"trust_level":40,"trust_score":0.4,"verification_status":"source_linked","evidence_level":"primary_source","quality_status":"source_backed","curation_status":null,"provenance_status":null,"valid_until":"2026-08-30T05:12:35.261681+00:00","source_url":"https://arxiv.org/abs/2605.21482v1","sources_cited":["https://arxiv.org/abs/2605.21482v1"],"answer_eligible":true,"contains_disputed_claims":false,"reliability_tier":"medium","reliability_reasons":["specific_source"],"source_url_specificity":"specific_source","requires_reverification":false,"content_hash":null,"owner":"system:arxiv-ingestion","created_at":"2026-05-21T06:00:06.242Z","snippet":"# DeepWeb-Bench: A Deep Research Benchmark Demanding Massive Cross-Source Evidence and Long-Horizon Derivation\n\n**Authors:** Sixiong Xie, Zhuofan Shi, Haiyang Shen, Jiuzheng Wang, Siqi Zhong\n**arXiv:** https://arxiv.org/abs/2605.21482v1\n**Published:** 2026-05-20T17:59:03Z\n\n## Abstract\nDeep research, in which an agent searches the open web, collects evidence, and derives an answer through extended reasoning, is a prominent use case for frontier language models. Frontier deep research products score high on existing benchmarks, making it difficult to distinguish their capabilities from current evaluation data alone. We introduce DeepWeb-Bench, a deep research benchmark that is substantially harder than existing benchmarks for the current frontier. Difficulty comes from three properties of th","content_length":1945,"entry_protection":{"status":"legacy_public","label":"Legacy public-safe capsule","message":"This capsule is eligible for public retrieval, but it predates persisted ATIS and seven-phase entry markers. 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The signal-to-noise ratio (SNR) of kSZ measurements scales directly with the correlation coefficient $r$ between reconstructed and true velocities. We introduce Velocityformer, an equivariant graph transformer architecture designed to match the specific symm","content_length":1779,"entry_protection":{"status":"legacy_public","label":"Legacy public-safe capsule","message":"This capsule is eligible for public retrieval, but it predates persisted ATIS and seven-phase entry markers. New capsule entries require both.","pipeline_required":true,"atis_required":true,"pipeline":{"completed":false,"phase_count":0,"required_phase_count":7,"phases":["ingestion","analysis","validation","consensus","execution","propagation","settlement"],"completed_at":null},"atis":{"checked":false,"decision":null,"checked_at":null}},"preview_is_truncated":true,"freshness_status":"current"},{"id":"9a72fbcc-2385-4ec5-be49-b04386e7edf7","title":"EvoStruct: Bridging Evolutionary and Structural Priors for Antibody CDR Design via Protein Language Model Adaptation","type":null,"tags":["cs.LG"],"trust_level":40,"trust_score":0.4,"verification_status":"source_linked","evidence_level":"primary_source","quality_status":"source_backed","curation_status":null,"provenance_status":null,"valid_until":"2026-08-30T05:12:34.977643+00:00","source_url":"https://arxiv.org/abs/2605.21485v1","sources_cited":["https://arxiv.org/abs/2605.21485v1"],"answer_eligible":true,"contains_disputed_claims":false,"reliability_tier":"medium","reliability_reasons":["specific_source"],"source_url_specificity":"specific_source","requires_reverification":false,"content_hash":null,"owner":"system:arxiv-ingestion","created_at":"2026-05-21T06:00:06.208Z","snippet":"# EvoStruct: Bridging Evolutionary and Structural Priors for Antibody CDR Design via Protein Language Model Adaptation\n\n**Authors:** Mansoor Ahmed, Sujin Lee, Umar Khayaz, Murray Patterson\n**arXiv:** https://arxiv.org/abs/2605.21485v1\n**Published:** 2026-05-20T17:59:16Z\n\n## Abstract\nEquivariant graph neural network (GNN) methods for antibody complementarity-determining region (CDR) design achieve the highest sequence recovery but suffer from severe vocabulary collapse. The current best GNN methods over-predict very few amino acids, such as tyrosine and glycine, while ignoring functionally important residues. We trace this failure to GNN encoders learning amino acid distributions de novo from limited structural data, discarding substitution patterns encoded in evolutionary databases. To res","content_length":1537,"entry_protection":{"status":"legacy_public","label":"Legacy public-safe capsule","message":"This capsule is eligible for public retrieval, but it predates persisted ATIS and seven-phase entry markers. New capsule entries require both.","pipeline_required":true,"atis_required":true,"pipeline":{"completed":false,"phase_count":0,"required_phase_count":7,"phases":["ingestion","analysis","validation","consensus","execution","propagation","settlement"],"completed_at":null},"atis":{"checked":false,"decision":null,"checked_at":null}},"preview_is_truncated":true,"freshness_status":"current"},{"id":"6e41e1e7-391c-471a-b571-845ff65e6296","title":"Quantifying Hyperparameter Transfer and the Importance of Embedding Layer Learning Rate","type":null,"tags":["cs.LG","cond-mat.dis-nn","cs.AI","stat.ML"],"trust_level":85,"trust_score":0.85,"verification_status":"source_linked","evidence_level":"primary_source","quality_status":"source_backed","curation_status":null,"provenance_status":null,"valid_until":"2026-08-30T05:12:34.792159+00:00","source_url":"https://arxiv.org/abs/2605.21486v1","sources_cited":["https://arxiv.org/abs/2605.21486v1"],"answer_eligible":true,"contains_disputed_claims":false,"reliability_tier":"medium","reliability_reasons":["specific_source"],"source_url_specificity":"specific_source","requires_reverification":false,"content_hash":null,"owner":"system:arxiv-ingestion","created_at":"2026-05-21T06:00:06.188Z","snippet":"# Quantifying Hyperparameter Transfer and the Importance of Embedding Layer Learning Rate\n\n**Authors:** Dayal Singh Kalra, Maissam Barkeshli\n**arXiv:** https://arxiv.org/abs/2605.21486v1\n**Published:** 2026-05-20T17:59:40Z\n\n## Abstract\nHyperparameter transfer allows extrapolating optimal optimization hyperparameters from small to large scales, making it critical for training large language models (LLMs). This is done either by fitting a scaling law to the hyperparameters or by a judicious choice of parameterization, such as Maximal Update ($μ$P), that renders optimal hyperparameters approximately scale invariant. In this paper, we first develop a framework to quantify hyperparameter transfer through three metrics: (1) the quality of the scaling law fit, (2) the robustness to extrapolation ","content_length":1621,"entry_protection":{"status":"legacy_public","label":"Legacy public-safe capsule","message":"This capsule is eligible for public retrieval, but it predates persisted ATIS and seven-phase entry markers. New capsule entries require both.","pipeline_required":true,"atis_required":true,"pipeline":{"completed":false,"phase_count":0,"required_phase_count":7,"phases":["ingestion","analysis","validation","consensus","execution","propagation","settlement"],"completed_at":null},"atis":{"checked":false,"decision":null,"checked_at":null}},"preview_is_truncated":true,"freshness_status":"current"},{"id":"f589a564-4cc3-4b29-9169-a4569b86b6bc","title":"Equilibrium Reasoners: Learning Attractors Enables Scalable Reasoning","type":null,"tags":["cs.LG"],"trust_level":75,"trust_score":0.75,"verification_status":"source_linked","evidence_level":"primary_source","quality_status":"source_backed","curation_status":null,"provenance_status":null,"valid_until":"2026-08-30T05:12:34.619002+00:00","source_url":"https://arxiv.org/abs/2605.21488v1","sources_cited":["https://arxiv.org/abs/2605.21488v1"],"answer_eligible":true,"contains_disputed_claims":false,"reliability_tier":"medium","reliability_reasons":["specific_source"],"source_url_specificity":"specific_source","requires_reverification":false,"content_hash":null,"owner":"system:arxiv-ingestion","created_at":"2026-05-21T06:00:06.175Z","snippet":"# Equilibrium Reasoners: Learning Attractors Enables Scalable Reasoning\n\n**Authors:** Benhao Huang, Zhengyang Geng, Zico Kolter\n**arXiv:** https://arxiv.org/abs/2605.21488v1\n**Published:** 2026-05-20T17:59:48Z\n\n## Abstract\nScaling test-time compute by iteratively updating a latent state has emerged as a powerful paradigm for reasoning. Yet the internal mechanisms that enable these iterative models to generalize beyond memorized patterns remain unclear. We hypothesize that generalizable reasoning arises from learning task-conditioned attractors: latent dynamical systems whose stable fixed points correspond to valid solutions.   We formalize this process through Equilibrium Reasoners (EqR), which enable test-time scaling without external verifiers or task-specific priors. EqR scales internal","content_length":1611,"entry_protection":{"status":"legacy_public","label":"Legacy public-safe capsule","message":"This capsule is eligible for public retrieval, but it predates persisted ATIS and seven-phase entry markers. New capsule entries require both.","pipeline_required":true,"atis_required":true,"pipeline":{"completed":false,"phase_count":0,"required_phase_count":7,"phases":["ingestion","analysis","validation","consensus","execution","propagation","settlement"],"completed_at":null},"atis":{"checked":false,"decision":null,"checked_at":null}},"preview_is_truncated":true,"freshness_status":"current"},{"id":"3f4a48f3-2371-4101-ae65-8a3207a95e52","title":"Variance Reduction for Expectations with Diffusion Teachers","type":null,"tags":["cs.LG","cs.AI","cs.CV","stat.CO","stat.ML"],"trust_level":40,"trust_score":0.4,"verification_status":"source_linked","evidence_level":"primary_source","quality_status":"source_backed","curation_status":null,"provenance_status":null,"valid_until":"2026-08-30T05:12:34.410369+00:00","source_url":"https://arxiv.org/abs/2605.21489v1","sources_cited":["https://arxiv.org/abs/2605.21489v1"],"answer_eligible":true,"contains_disputed_claims":false,"reliability_tier":"medium","reliability_reasons":["specific_source"],"source_url_specificity":"specific_source","requires_reverification":false,"content_hash":null,"owner":"system:arxiv-ingestion","created_at":"2026-05-21T06:00:06.165Z","snippet":"# Variance Reduction for Expectations with Diffusion Teachers\n\n**Authors:** Jesse Bettencourt, Xindi Wu, Matan Atzmon, James Lucas, Jonathan Lorraine\n**arXiv:** https://arxiv.org/abs/2605.21489v1\n**Published:** 2026-05-20T17:59:52Z\n\n## Abstract\nPretrained diffusion models serve as frozen teachers feeding downstream pipelines such as text-to-3D, single-step distillation, and data attribution. The teacher gradients these pipelines consume are Monte Carlo (MC) expectations over noise levels and Gaussian noise samples; their estimator variance dominates compute cost because each draw requires expensive upstream work (rendering, simulation, encoding). We introduce CARV, a compute-aware variance-accounting framework that motivates a hierarchical MC estimator: amortize the expensive upstream comp","content_length":1336,"entry_protection":{"status":"legacy_public","label":"Legacy public-safe capsule","message":"This capsule is eligible for public retrieval, but it predates persisted ATIS and seven-phase entry markers. New capsule entries require both.","pipeline_required":true,"atis_required":true,"pipeline":{"completed":false,"phase_count":0,"required_phase_count":7,"phases":["ingestion","analysis","validation","consensus","execution","propagation","settlement"],"completed_at":null},"atis":{"checked":false,"decision":null,"checked_at":null}},"preview_is_truncated":true,"freshness_status":"current"},{"id":"d78feeba-4461-4a9b-a77f-4bb62c1bfa29","title":"Predictable Confabulations: Factual Recall by LLMs Scales with Model Size and Topic Frequency","type":null,"tags":["cs.CL","cs.AI","cs.LG"],"trust_level":80,"trust_score":0.8,"verification_status":"source_linked","evidence_level":"primary_source","quality_status":"source_backed","curation_status":null,"provenance_status":null,"valid_until":"2026-08-30T06:05:32.617164+00:00","source_url":"https://arxiv.org/abs/2605.18732v1","sources_cited":["https://arxiv.org/abs/2605.18732v1"],"answer_eligible":true,"contains_disputed_claims":false,"reliability_tier":"medium","reliability_reasons":["specific_source"],"source_url_specificity":"specific_source","requires_reverification":false,"content_hash":null,"owner":"system:arxiv-ingestion","created_at":"2026-05-19T06:00:07.293Z","snippet":"# Predictable Confabulations: Factual Recall by LLMs Scales with Model Size and Topic Frequency\n\n**Authors:** Matthew L. Smith, Jonathan P. Shock, Samuel T. Segun, Iyiola E. Olatunji, Tegawendé F. Bissyandé\n**arXiv:** https://arxiv.org/abs/2605.18732v1\n**Published:** 2026-05-18T17:53:44Z\n\n## Abstract\nWhile scaling laws govern aggregate large language model performance, no scaling law has linked factual recall to both model size and training-data composition. We evaluated 38 models on over 8,900 scholarly references evaluated by an automated reference verification system. Recall quality follows a sigmoid in the log-linear combination of model parameter count and topic representation in training data. These two variables alone explain 60% of the variance across 16 dense models from four fami","content_length":1040,"entry_protection":{"status":"legacy_public","label":"Legacy public-safe capsule","message":"This capsule is eligible for public retrieval, but it predates persisted ATIS and seven-phase entry markers. New capsule entries require both.","pipeline_required":true,"atis_required":true,"pipeline":{"completed":false,"phase_count":0,"required_phase_count":7,"phases":["ingestion","analysis","validation","consensus","execution","propagation","settlement"],"completed_at":null},"atis":{"checked":false,"decision":null,"checked_at":null}},"preview_is_truncated":true,"freshness_status":"current"}],"offset":0,"limit":20,"total":123,"has_more":true,"query":"","default_policy":"source_backed_verified","include_exploratory":false,"browse_topic_limit":2,"deduplicated_count":0,"policy_filtered_count":0,"commercial":{"marketplace":"https://forgecascade.org/marketplace","pricing":"https://forgecascade.org/pricing","enterpriseAnnualCheckout":"https://buy.stripe.com/8x2fZjfF622r09ZgU708g0c","priorityRetainerCheckout":"https://buy.stripe.com/dRmaEZ9gIdL91e3cDR08g0g","deploymentDepositCheckout":"https://buy.stripe.com/eVqfZjgJa6iH2i733h08g0f","rushPilotCheckout":"https://buy.stripe.com/6oUbJ3boQ5eD1e39rF08g0d","enterpriseInvoiceRequest":"mailto:hello@forgecascade.org?subject=Forge%20enterprise%20invoice%20request&body=Organization%3A%0AProcurement%20owner%3A%0ASecurity%20owner%3A%0ATeam%20size%3A%0ACorpus%20type%3A%0ATarget%20offer%3A%20%2425k%20deposit%20%2F%20%2425k%2Fmo%20retainer%20%2F%20%24120k%20annual%20%2F%20%245k%20rush%20pilot%0ATimeline%3A%0AInvoice%20or%20PO%20requirements%3A","capsuleCoreCheckout":"https://buy.stripe.com/4gM14p2SkfThg8X8nB08g04","paidPilotCheckout":"https://buy.stripe.com/eVq6oJgJa0YnaOD8nB08g00","staticCheckoutFallback":"https://sunflash12.github.io/ForgeV3/"}}