BrainAgent: A Large Language Model-Driven Multi-Agent Framework for Autonomous Brain Signal Understanding

Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Yangxuan Zhou [ view email ] [v1] Wed, 24 Jun 2026 04:54:26 UTC (1,362 KB) Full-text links: Access Paper: View a PDF of the paper titled BrainAgent: A Large Language Model-Driven Multi-Agent Framework for Autonomous Brain Signal Understanding, by Yangxuan Zhou and 4 other authors View PDF HTML (experimental) TeX Source view license Current browse context: < prev | next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliograp

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Long-Term Simulation Exposes Cognitive-Developmental Risks in AI Companions

Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Kaicheng Shen [ view email ] [v1] Wed, 24 Jun 2026 04:46:42 UTC (6,662 KB) Full-text links: Access Paper: View a PDF of the paper titled Long-Term Simulation Exposes Cognitive-Developmental Risks in AI Companions, by Kaicheng Shen and 5 other authors View PDF HTML (experimental) TeX Source view license Current browse context: < prev | next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Togg

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Offline Multi-agent Continual Cooperation via Skill Partition and Reuse

Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Yuchen Xiao [ view email ] [v1] Wed, 24 Jun 2026 04:40:21 UTC (6,016 KB) Full-text links: Access Paper: View a PDF of the paper titled Offline Multi-agent Continual Cooperation via Skill Partition and Reuse, by Yuchen Xiao and 4 other authors View PDF HTML (experimental) TeX Source view license Current browse context: < prev | next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected

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What Actually Works for Spacecraft Fault-Tolerant Control: An Honest Settled-Gate Benchmark of Learned and Classical Methods

Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Alireza Shojaei [ view email ] [v1] Wed, 24 Jun 2026 04:08:39 UTC (32 KB) Full-text links: Access Paper: View a PDF of the paper titled What Actually Works for Spacecraft Fault-Tolerant Control: An Honest Settled-Gate Benchmark of Learned and Classical Methods, by Alireza Shojaei View PDF HTML (experimental) TeX Source view license Current browse context: < prev | next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explore

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Agentic Knowledge Tracing: A Multi-Agent LLM Architecture for Stealth Assessment of Financial Literacy in Serious Games

Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Gabriel Santos [ view email ] [v1] Wed, 24 Jun 2026 03:43:59 UTC (5,816 KB) Full-text links: Access Paper: View a PDF of the paper titled Agentic Knowledge Tracing: A Multi-Agent LLM Architecture for Stealth Assessment of Financial Literacy in Serious Games, by Gabriel Santos and 2 other authors View PDF HTML (experimental) TeX Source view license Current browse context: < prev | next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliograp

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Omni-Perception Policy Optimization for Multimodal Emotion Reasoning

Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Zhiyuan Han [ view email ] [v1] Wed, 24 Jun 2026 02:43:26 UTC (7,878 KB) Full-text links: Access Paper: View a PDF of the paper titled Omni-Perception Policy Optimization for Multimodal Emotion Reasoning, by Zhiyuan Han and 8 other authors View PDF HTML (experimental) TeX Source view license Current browse context: < prev | next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Paper

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Heuresis: Search Strategies for Autonomous AI Research Agents Across Quality, Diversity and Novelty

Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Antonis Antoniades [ view email ] [v1] Tue, 23 Jun 2026 21:44:08 UTC (6,269 KB) Full-text links: Access Paper: View a PDF of the paper titled Heuresis: Search Strategies for Autonomous AI Research Agents Across Quality, Diversity and Novelty, by Antonis Antoniades and 8 other authors View PDF HTML (experimental) TeX Source view license Current browse context: < prev | next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographi

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To Isolate or to Score? Model-Adaptive Assessment for Cost-Efficient Multi

Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Jungseob Lee [ view email ] [v1] Tue, 23 Jun 2026 21:34:23 UTC (281 KB) Full-text links: Access Paper: View a PDF of the paper titled To Isolate or to Score? Model-Adaptive Assessment for Cost-Efficient Multi-Agent RAG, by Jungseob Lee and 2 other authors View PDF HTML (experimental) TeX Source view license Current browse context: < prev | next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers

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Transferability for General Reasoning: An Automated Curriculum for Multi

Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Yongjin Yang [ view email ] [v1] Tue, 23 Jun 2026 21:10:29 UTC (670 KB) Full-text links: Access Paper: View a PDF of the paper titled Transferability for General Reasoning: An Automated Curriculum for Multi-Domain RLVR, by Yongjin Yang and 5 other authors View PDF HTML (experimental) TeX Source view license Current browse context: < prev | next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers To

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研究提出基于等级分的棋手风格嵌入模型

一篇名为《基于等级分条件残差移动模型的人类国际象棋棋手风格嵌入》的论文在arXiv上发布。该研究由Jason Carlson完成，旨在通过等级分（Elo rating）条件残差移动模型，从人类对局数据中解耦并学习棋手的个性化风格嵌入。传统方法通常将棋手水平与风格混合建模，而新模型通过条件化等级分，分离出风格特征，有助于更精细地分析人类棋手的决策模式与棋风差异。该工作为棋类AI与人类行为理解提供了新视角，相关代码与数据已开放。 #arXiv #国际象棋 #棋手风格 #AI #机器学习 #论文

TRUSTMEM：为长时记忆LLM智能体学习可信记忆巩固方法

研究人员提出名为TRUSTMEM的新型框架，旨在解决大语言模型（LLM）智能体在长期记忆中存在的可信度问题。该框架通过强化学习机制，使智能体能够自主筛选、整合和巩固重要信息，避免存储错误或无关记忆。实验表明，TRUSTMEM在多个长时交互任务中显著提升了记忆的准确性和模型决策的可靠性，为构建更安全、可信的自主智能体提供了新思路。论文作者来自相关研究机构，目前该工作已在arXiv上公开，并将进一步探索与知识图谱的结合。 #AI #LLM #长期记忆 #可信人工智能 #智能体 #机器学习 #记忆巩固

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