Summary of Vision-language Models Can Self-improve Reasoning Via Reflection, by Kanzhi Cheng et al.
Vision-Language Models Can Self-Improve Reasoning via Reflectionby Kanzhi Cheng, Yantao Li, Fangzhi Xu, Jianbing Zhang,…
Vision-Language Models Can Self-Improve Reasoning via Reflectionby Kanzhi Cheng, Yantao Li, Fangzhi Xu, Jianbing Zhang,…
SelfCodeAlign: Self-Alignment for Code Generationby Yuxiang Wei, Federico Cassano, Jiawei Liu, Yifeng Ding, Naman Jain,…
Unified Triplet-Level Hallucination Evaluation for Large Vision-Language Modelsby Junjie Wu, Tsz Ting Chung, Kai Chen,…
Auto-Intent: Automated Intent Discovery and Self-Exploration for Large Language Model Web Agentsby Jaekyeom Kim, Dong-Ki…
SceneGenAgent: Precise Industrial Scene Generation with Coding Agentby Xiao Xia, Dan Zhang, Zibo Liao, Zhenyu…
Mitigating Paraphrase Attacks on Machine-Text Detectors via Paraphrase Inversionby Rafael Rivera Soto, Barry Chen, Nicholas…
Sequential choice in ordered bundlesby Rajeev Kohli, Kriste Krstovski, Hengyu Kuang, Hengxu LinFirst submitted to…
CFSafety: Comprehensive Fine-grained Safety Assessment for LLMsby Zhihao Liu, Chenhui HuFirst submitted to arxiv on:…
MultiTok: Variable-Length Tokenization for Efficient LLMs Adapted from LZW Compressionby Noel Elias, Homa Esfahanizadeh, Kaan…