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arXiv:2603.20206v1 Announce Type: new Abstract: Large language models (LLMs) have achieved impressive capabilities, yet ensuring their safety against harmful prompts remains a critical challenge. Recent …
arXiv:2603.20510v1 Announce Type: new Abstract: Language models often lack grounded reasoning capabilities in specialized domains where training data is scarce but bespoke systems excel. We …
arXiv:2603.21228v1 Announce Type: new Abstract: While AI-assisted writing has been widely reported to improve essay quality, its impact on the structural diversity of student thinking …
arXiv:2603.21162v1 Announce Type: new Abstract: Neural tree search is a powerful decision-making algorithm widely used in complex domains such as game playing and model-based reinforcement …
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:2603.21237v1 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:2603.21272v1 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:2603.20216v1 Announce Type: new Abstract: Diffusion language models (DLMs) have emerged as a promising alternative to autoregressive (AR) models, offering sub-linear generation latency and bidirectional …
arXiv:2603.21155v1 Announce Type: new Abstract: Text-attributed graphs (TAGs) enhance graph learning by integrating rich textual semantics and topological context for each node. While boosting expressiveness, …
arXiv:2603.21341v1 Announce Type: new Abstract: Improving embodied reasoning in multimodal-large-language models (MLLMs) is essential for building vision-language-action models (VLAs) on top of them to readily …
Call For Papers 2026 The Fortieth Annual Conference on Neural Information Processing Systems (NeurIPS 2026) is an interdisciplinary conference that brings together researchers in deep …
arXiv:2603.20222v1 Announce Type: new Abstract: Emotion detection is a central problem in NLP, with recent progress driven by transformer-based models trained on established datasets. However, …
