{"total":10,"items":[{"citing_arxiv_id":"2606.31273","ref_index":9,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"The Calibration Turn in AI-Assisted Research: A Conceptual and Methodological Framework for Evidence-Licensed Claims","primary_cat":"cs.LG","submitted_at":"2026-06-30T07:46:54+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":4.0,"formal_verification":"none","one_line_summary":"Develops a framework representing AI-assisted research via five operators and principles for evidence-licensed claims, distinguishing claim semantics and introducing epistemic debt.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2606.29981","ref_index":19,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Hephaestus: Toward a Cybersecurity AI 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papers under web-search-disabled conditions and finds the strongest agent surpasses published SOTA on only 17.8% of tasks, succeeding mainly by translating problems into familiar supervised learning setups.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2606.22731","ref_index":19,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Closed-loop Auto Research for Molecular Property Prediction: Discovering and Certifying Generalizable Improvements","primary_cat":"cs.AI","submitted_at":"2026-06-22T00:18:27+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"Closed-loop LM-agent auto research finds some transferable gains on molecular property prediction benchmarks via external data but shows non-transfer for model and feature edits selected on validation.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2606.24899","ref_index":14,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"From Meta Idea to Advanced Mathematical Discovery -- Human-AI Co-Discovery of Sign-Embedding Quantum Algorithms","primary_cat":"cs.LG","submitted_at":"2026-06-12T13:30:59+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":5.0,"formal_verification":"none","one_line_summary":"Human-AI collaboration expanded a meta-idea on rational approximation into sign-embedding quantum algorithms for matrix problems, with humans retaining final judgment on routes and refinements.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2606.09500","ref_index":18,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Deterministic Integrity Gates for LLM-Assisted Clinical Manuscript 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philosophy-of-science accounts to direct LLMs toward principle-based hypothesis generation, claims superior performance over direct prompting, and derives two new transformer algorithms from the resulting hypotheses.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2605.27643","ref_index":46,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Agentic Language-to-Objective Synthesis for Optofluidic Assembly","primary_cat":"cs.RO","submitted_at":"2026-05-26T20:03:54+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"Speak-to-Objective is a modular agentic pipeline that translates spoken or written commands into fully differentiable objective functions for optofluidic microparticle assembly using LLMs, inverse solvers, and experimental 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