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arXiv:2603.22665v1 Announce Type: new Abstract: The standard practice in Large Language Models (LLMs) is to base predictions on the final-layer token representations. Recent studies, however, …
arXiv:2603.22943v1 Announce Type: new Abstract: Personalized text-to-image generation lets users fine-tune diffusion models into repositories of concept-specific checkpoints, but serving these repositories efficiently is difficult …
arXiv:2603.22823v1 Announce Type: new Abstract: Context. Nowadays, artificial intelligence agent systems are transforming from single-tool interactions to complex multi-agent orchestrations. As a result, two competing …
arXiv:2603.23004v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated great capabilities across diverse natural language tasks; yet their ability to solve abstraction and …
arXiv:2603.23346v1 Announce Type: new Abstract: Real-time spoken dialogue systems face a fundamental tension between latency and response quality. End-to-end speech-to-speech (S2S) models respond immediately and …
arXiv:2603.22935v1 Announce Type: new Abstract: Chest X-ray report generation and automated evaluation are limited by poor recognition of low-prevalence abnormalities and inadequate handling of clinically …
arXiv:2603.22677v1 Announce Type: new Abstract: Distributional metrics such as Fr\'echet Audio Distance cannot score individual music clips and correlate poorly with human judgments, while the …
arXiv:2603.22629v1 Announce Type: new Abstract: Adapting pretrained language models to low-resource, morphologically rich languages remains a significant challenge. Existing vocabulary expansion methods typically rely on …
arXiv:2603.22312v1 Announce Type: new Abstract: This paper computationally investigates whether thought requires a language-like format, as posited by the Language of Thought (LoT) hypothesis. We …
arXiv:2603.22642v1 Announce Type: new Abstract: Language barriers affect 27.3 million U.S. residents with non-English language preference, yet professional medical translation remains costly and often unavailable. …
arXiv:2603.22744v1 Announce Type: new Abstract: Large language models excel on objectively verifiable tasks such as math and programming, where evaluation reduces to unit tests or …
arXiv:2603.22561v1 Announce Type: new Abstract: This paper asks whether a bounded neural architecture can exhibit a meaningful division of labor between intuition and deliberation on …
