383 citations · 1.9k across the 48 of their papers we have counts for
48 papers
Rationales Are Not Silver Bullets: Measuring the Impact of Rationales on Model Performance and Reliability
Chiwei Zhu, Benfeng Xu, An Yang +4
Training language models with rationales augmentation has been shown to be beneficial in many existing works. In this paper, we identify that such a prevailing view does not hold c…
Qwen2-Audio Technical Report
Yunfei Chu, Jin Xu, Qian Yang +9
We introduce the latest progress of Qwen-Audio, a large-scale audio-language model called Qwen2-Audio, which is capable of accepting various audio signal inputs and performing audi…
Qwen2 Technical Report
An Yang, Baosong Yang, Binyuan Hui +59
This report introduces the Qwen2 series, the latest addition to our large language models and large multimodal models. We release a comprehensive suite of foundational and instruct…
Can Large Language Models Always Solve Easy Problems if They Can Solve Harder Ones?
Zhe Yang, Yichang Zhang, Tianyu Liu +4
Large language models (LLMs) have demonstrated impressive capabilities, but still suffer from inconsistency issues (e.g. LLMs can react differently to disturbances like rephrasing…
LLM Critics Help Catch Bugs in Mathematics: Towards a Better Mathematical Verifier with Natural Language Feedback
Bofei Gao, Zefan Cai, Runxin Xu +10
In recent progress, mathematical verifiers have achieved success in mathematical reasoning tasks by validating the correctness of solutions generated by policy models. However, exi…
An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language Models
Liang Chen, Haozhe Zhao, Tianyu Liu +4
In this study, we identify the inefficient attention phenomena in Large Vision-Language Models (LVLMs), notably within prominent models like LLaVA-1.5, QwenVL-Chat and Video-LLaVA.…