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arXiv:2603.10195v1 Announce Type: new Abstract: Large Language Models frequently generate fluent but factually incorrect text. We propose Adaptive Activation Cancellation (AAC), a real-time inference-time framework …
arXiv:2603.10211v1 Announce Type: new Abstract: Vietnamese exhibits extensive dialectal variation, posing challenges for NLP systems trained predominantly on standard Vietnamese. Such systems often underperform on …
arXiv:2603.10213v1 Announce Type: new Abstract: This technical report presents Sabi\'a-4 and Sabiazinho-4, a new generation of Portuguese language models with a focus on Brazilian Portuguese …
arXiv:2603.10233v1 Announce Type: new Abstract: Evaluating student responses, from long essays to short factual answers, is a key challenge in educational NLP. Automated Essay Scoring …
arXiv:2603.10243v1 Announce Type: new Abstract: Recent studies show that the safety alignment of large language models (LLMs) can be easily compromised even by seemingly non-adversarial …
arXiv:2603.10303v1 Announce Type: new Abstract: Judging the novelty of research ideas is crucial for advancing science, enabling the identification of unexplored directions, and ensuring contributions …
arXiv:2603.10313v1 Announce Type: new Abstract: Social media text shows promise for monitoring trends in the opioid overdose crisis; however, the overwhelming majority of social media …
arXiv:2603.10351v1 Announce Type: new Abstract: Large language models (LLMs) have become a standard for multilingual evaluation, yet they exhibit a severe systematic translationese bias. In …
arXiv:2603.10367v1 Announce Type: new Abstract: The performance of task-oriented dialogue models is strongly tied to how well they track dialogue states, which records and updates …
arXiv:2603.10473v1 Announce Type: new Abstract: The paradigm shift from item-centric ranking to answer-centric synthesis is redefining the role of search engines. While recent industrial progress …
arXiv:2603.10476v1 Announce Type: new Abstract: The alignment of large language models (LLMs) has progressed substantially in single-agent settings through paradigms such as RLHF and Constitutional …
arXiv:2603.10024v1 Announce Type: new Abstract: LWM-Temporal is a new member of the Large Wireless Models (LWM) family that targets the spatiotemporal nature of wireless channels. …