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arXiv:2603.22871v1 Announce Type: new Abstract: Current large language models (LLMs) primarily rely on linear sequence generation and massive parameter counts, yet they severely struggle with …
arXiv:2603.22829v1 Announce Type: new Abstract: With the rapid development and widespread application of Large Language Models (LLMs), their potential safety risks have attracted widespread attention. …
arXiv:2603.22453v1 Announce Type: new Abstract: Community Notes have emerged as an effective crowd-sourced mechanism for combating online deception on social media platforms. However, its reliance …
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:2603.22813v1 Announce Type: new Abstract: Humans often juggle multiple, sometimes conflicting objectives and shift their priorities as circumstances change, rather than following a fixed objective …
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:2603.22642v1 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:2603.22350v1 Announce Type: new Abstract: Deterministic pre-execution safety gates evaluate whether individual agent actions are compatible with their assigned roles. While effective at per-action authorization, …
arXiv:2603.22791v1 Announce Type: new Abstract: How should multi-agent systems be designed, and can that design knowledge be captured in a form that is inspectable, revisable, …
arXiv:2603.22869v1 Announce Type: new Abstract: Large Language Models (LLMs) have become core cognitive components in modern artificial intelligence (AI) systems, combining internal knowledge with external …
arXiv:2603.22934v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) improves the reliability of large language model applications by grounding generation in retrieved evidence, but it also …