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arXiv:2604.01202v2 Announce Type: new Abstract: We consider the question: when a large language reasoning model makes a choice, did it think first and then decide …
arXiv:2604.00261v2 Announce Type: new Abstract: Large language models (LLMs) have achieved strong performance on medical question answering (medical QA), and chain-of-thought (CoT) prompting has further …
arXiv:2604.01378v1 Announce Type: new Abstract: Offline reinforcement learning (RL) has received increasing attention for learning policies from previously collected data without interaction with the real …
Anthropic executives said it was an accident and retracted the bulk of the takedown notices.
Oral arguments in Trump v. Barbara, on the constitutionality of President Donald Trump’s executive order on birthright citizenship, have concluded, but the conversation isn’t over. …
April 2 2026 Announcing the ICML 2026 Tutorials Gautam Kamath ICML 2026 By ICML 2026 Tutorial Chairs Claire Vernade and Adam White. Tutorials are a …
arXiv:2604.01349v1 Announce Type: new Abstract: Reservoir simulation workflows face a fundamental data asymmetry: input parameter fields (geostatistical permeability realizations, porosity distributions) are free to generate …
arXiv:2604.00890v1 Announce Type: new Abstract: Geometric Problem Solving (GPS) remains at the heart of enhancing mathematical reasoning in large language models because it requires the …
arXiv:2604.01337v1 Announce Type: new Abstract: While deep learning has significantly advanced accident anticipation, the robustness of these safety-critical systems against real-world perturbations remains a major …
NeurIPS 2026 Call for Position Papers We invite the submission of position papers to be published at the NeurIPS 2026 conference. Position papers argue for …
arXiv:2604.00026v1 Announce Type: new Abstract: When multiple large language models interact in a shared conversation, do they develop differentiated social roles or converge toward uniform …
arXiv:2604.00901v1 Announce Type: new Abstract: Multi-agent Retrieval-Augmented Generation (RAG), wherein each agent takes on a specific role, supports hard queries that require multiple steps and …