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arXiv:2603.20267v1 Announce Type: new Abstract: While Large Language Models (LLMs) have advanced complex reasoning, prominent methods like the Tree of Thoughts (ToT) framework face a …
arXiv:2603.20210v1 Announce Type: new Abstract: Masked Diffusion Models (MDMs) provide an efficient non-causal alternative to autoregressive generation but often struggle with token dependencies and semantic …
arXiv:2603.21272v1 Announce Type: new Abstract: Externalized reasoning is already exploited by transformer-based agents through chain-of-thought, but structured retrieval -- indexing over one's own reasoning state …
arXiv:2603.20724v1 Announce Type: new Abstract: Multi-RF Fusion achieves a test ROC-AUC of 0.8476 +/- 0.0002 on ogbg-molhiv (10 seeds), placing #1 on the OGB leaderboard …
arXiv:2603.20619v1 Announce Type: new Abstract: Artificial intelligence (AI) is poised to profoundly reshape how work is executed and organized, but we do not yet have …
arXiv:2603.21344v1 Announce Type: new Abstract: In this short note we propose using agentic swarms of virtual labs as a model of an AI Science Community. …
December 15 2025 Supporting Our Community’s Infrastructure: NeurIPS Foundation’s Donation to OpenReview Communications Chairs 2025 General By Foundation Board The Neural Information Processing Systems Foundation …
arXiv:2603.20255v1 Announce Type: new Abstract: Speech-based AI educational applications have gained significant interest in recent years, particularly for children. However, children speech research remains limited …
arXiv:2603.20670v1 Announce Type: new Abstract: The rapid growth in the volume, variety, and velocity of geospatial data has created data ecosystems that are highly distributed, …
arXiv:2603.21237v1 Announce Type: new Abstract: Large language models (LLMs) deliver impressive capabilities but incur substantial inference latency and cost, which hinders their deployment in latency-sensitive …
arXiv:2603.20213v1 Announce Type: new Abstract: Generative search engines represent a transition from traditional ranking-based retrieval to Large Language Model (LLM)-based synthesis, transforming optimization goals from …
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