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arXiv:2604.00011v1 Announce Type: cross Abstract: The growing prominence of large language models (LLMs) in daily life has heightened concerns that LLMs exhibit many of the …
arXiv:2604.00010v1 Announce Type: cross Abstract: Large language models cannot estimate how long their own tasks take. We investigate this limitation through four experiments across 68 …
arXiv:2604.00009v1 Announce Type: cross Abstract: We present the design rationale, implementation attempt, and failure analysis of Eyla, a proposed identity-anchored LLM architecture that integrates biologically-inspired …
arXiv:2604.00008v1 Announce Type: cross Abstract: As qualitative researchers show growing interest in using automated tools to support interpretive analysis, a large language model (LLM) is …
arXiv:2604.00007v1 Announce Type: cross Abstract: We present Dynin-Omni, the first masked-diffusion-based omnimodal foundation model that unifies text, image, and speech understanding and generation, together with …
arXiv:2604.00004v1 Announce Type: cross Abstract: The extension of context windows in Large Language Models is typically facilitated by scaling positional encodings followed by lightweight Continual …
arXiv:2604.00003v1 Announce Type: cross Abstract: This study evaluates the reliability of information extraction approaches from KRS documents using three strategies: LLM only, Hybrid Deterministic - …
arXiv:2604.00002v1 Announce Type: cross Abstract: Here we introduce the Olfactory Perception (OP) benchmark, designed to assess the capability of large language models (LLMs) to reason …
arXiv:2604.00001v1 Announce Type: cross Abstract: Gradient-based data selection offers a principled framework for estimating sample utility in large language model (LLM) fine-tuning, but existing methods …
arXiv:2603.05735v2 Announce Type: cross Abstract: We present an AI agentic measurement of the thrust distribution in $e^{+}e^{-}$ collisions at $\sqrt{s}=91.2$~GeV using archived ALEPH data. The …
arXiv:2604.01221v1 Announce Type: new Abstract: We present HippoCamp, a new benchmark designed to evaluate agents' capabilities on multimodal file management. Unlike existing agent benchmarks that …
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 …
