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arXiv:2602.12635v1 Announce Type: new Abstract: As LLMs scale, low-bit floating-point formats like MXFP and NVFP4 offer new opportunities for precision and efficiency. In this work, …
arXiv:2602.12639v1 Announce Type: new Abstract: Legal text generated by large language models (LLMs) can usually achieve reasonable factual accuracy, but it frequently fails to adhere …
arXiv:2602.12642v1 Announce Type: new Abstract: Reward-maximizing RL methods enhance the reasoning performance of LLMs, but often reduce the diversity among outputs. Recent works address this …
arXiv:2602.12660v1 Announce Type: new Abstract: Reward models are crucial for aligning large language models (LLMs) with human values and intentions. Existing approaches follow either Generative …
arXiv:2602.12674v1 Announce Type: new Abstract: Knowledge Distillation (KD) for Large Language Models (LLMs) has become increasingly important as models grow in size and complexity. While …
arXiv:2602.12709v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) has become a dominant paradigm for grounding large language models (LLMs) with external evidence in knowledge-intensive question …
arXiv:2602.12746v1 Announce Type: new Abstract: Despite their impressive performance, self-supervised speech models often struggle to generalize to new languages and tend to forget previously acquired …
arXiv:2602.12759v1 Announce Type: new Abstract: Standard evaluation in NLP typically indicates that system A is better on average than system B, but it provides little …
arXiv:2602.12778v1 Announce Type: new Abstract: This study advances aspect-based sentiment analysis (ABSA) for Persian-language user reviews in the tourism domain, addressing challenges of low-resource languages. …
arXiv:2602.12806v1 Announce Type: new Abstract: Data containing personal information is increasingly used to train, fine-tune, or query Large Language Models (LLMs). Text is typically scrubbed …
arXiv:2602.12811v1 Announce Type: new Abstract: When humans and large language models (LLMs) process the same text, activations in the LLMs correlate with brain activity measured, …
arXiv:2602.12818v1 Announce Type: new Abstract: Detecting reclaimed slurs represents a fundamental challenge for hate speech detection systems, as the same lexcal items can function either …