arXiv:2502.00258v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated exceptional performance in natural language processing tasks, yet their...

arXiv:2506.19848v1 Announce Type: cross Abstract: This paper presents ScaleCap, an inference-time scalable image captioning strategy that generates comprehensive and detailed...

arXiv:2506.19835v1 Announce Type: new Abstract: Recent advancements in medical Large Language Models (LLMs) have showcased their powerful reasoning and diagnostic...

arXiv:2506.19113v1 Announce Type: new Abstract: The discourse around toxicity and LLMs in NLP largely revolves around detection tasks. This work...

July/August 25Guest edited by Edward Faulkner ’03 May/June 25Guest edited by Frank Rubin ’62 March/April 25Guest edited by Michael S....

arXiv:2408.00004v2 Announce Type: replace-cross Abstract: This paper addresses the problem of correctly formatting numeric expressions in automatic speech recognition (ASR)...

arXiv:2506.08388v2 Announce Type: replace-cross Abstract: Training reasoning language models (LMs) with reinforcement learning (RL) for one-hot correctness inherently relies on...

arXiv:2506.17863v1 Announce Type: new Abstract: Offsite marketing is essential in e-commerce, enabling businesses to reach customers through external platforms and...

arXiv:2506.17781v1 Announce Type: cross Abstract: Dense embeddings are fundamental to modern machine learning systems, powering Retrieval-Augmented Generation (RAG), information retrieval,...