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arXiv:2603.09185v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) have enabled diverse retrieval methods. However, existing retrieval methods …
arXiv:2603.09180v1 Announce Type: new Abstract: Spoken dialog systems with cascaded ASR-LLM-TTS modules retain strong LLM intelligence, but VAD segmentation often forces half-duplex turns and brittle …
arXiv:2603.09154v1 Announce Type: new Abstract: Large language models (LLMs) trained on internet-scale corpora can exhibit systematic biases that increase the probability of unwanted behavior. In …
arXiv:2603.09095v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) can process text presented as images, yet they often perform worse than when the same …
arXiv:2603.08999v1 Announce Type: new Abstract: Large language models (LLMs) achieve strong reasoning performance through chain-of-thought (CoT) reasoning, yet often generate unnecessarily long reasoning paths that …
arXiv:2603.08989v1 Announce Type: new Abstract: Thematic analysis (TA) is widely used in health research to extract patterns from patient interviews, yet manual TA faces challenges …
arXiv:2603.08910v1 Announce Type: new Abstract: We introduce SciTaRC, an expert-authored benchmark of questions about tabular data in scientific papers requiring both deep language reasoning and …
arXiv:2603.08899v1 Announce Type: new Abstract: Speculative decoding has emerged as a powerful approach to accelerate large language model (LLM) inference by employing lightweight draft models …
arXiv:2603.08879v1 Announce Type: new Abstract: Accessing sensitive patient data for machine learning is challenging due to privacy concerns. Datasets with annotations of personally identifiable information …
arXiv:2603.08869v1 Announce Type: new Abstract: Do the features learned by Sparse Autoencoders (SAEs) represent abstract meaning, or are they tied to how text is written? …
arXiv:2505.13903v1 Announce Type: cross Abstract: Large Language Models (LLMs) have recently achieved remarkable progress in mathematical reasoning. To enable such capabilities, many existing works distill …
arXiv:2603.09957v1 Announce Type: new Abstract: While existing evaluations of large language models (LLMs) measure deception rates, the underlying conditions that give rise to deceptive behavior …