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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:2603.22582v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning has been proposed as a transparency mechanism for large language models in safety-critical deployments, yet its effectiveness …
arXiv:2603.22576v1 Announce Type: new Abstract: We introduce CAPITU, a benchmark for evaluating instruction-following capabilities of Large Language Models (LLMs) in Brazilian Portuguese. Unlike existing benchmarks …
arXiv:2603.22566v1 Announce Type: new Abstract: The 2022 U.S. Supreme Court decision in Dobbs v. Jackson Women's Health Organization reshaped the reproductive rights landscape, introducing new …
arXiv:2603.22497v1 Announce Type: new Abstract: Where there is growing interest in in-context language learning (ICLL) for unseen languages with large language models, such languages usually …
arXiv:2603.22473v1 Announce Type: new Abstract: Hybrid language models combining attention with state space models (SSMs) or linear attention offer improved efficiency, but whether both components …
arXiv:2603.22459v1 Announce Type: new Abstract: Enhancing reader engagement while preserving informational fidelity is a central challenge in controllable text generation for news media. Optimizing news …
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:2603.22446v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has significantly improved reasoning in large language models (LLMs), yet the token-level mechanisms underlying …
arXiv:2603.22295v1 Announce Type: new Abstract: Large language models appear to develop internal representations of emotion -- "emotion circuits," "emotion neurons," and structured emotional manifolds have …
arXiv:2603.22293v1 Announce Type: new Abstract: Search-augmented large language models (LLMs) trained with reinforcement learning (RL) have achieved strong results on open-domain question answering (QA), but …
arXiv:2603.22290v1 Announce Type: new Abstract: Low-resource languages (LRLs) often lack high-quality, large-scale datasets for training effective text embedding models, hindering their application in tasks like …
