5 papers
VL-RewardBench: A Challenging Benchmark for Vision-Language Generative Reward Models
Lei Li, Yuancheng Wei, Zhihui Xie +9
Vision-language generative reward models (VL-GenRMs) play a crucial role in aligning and evaluating multimodal AI systems, yet their own evaluation remains under-explored. Current…
VLFeedback: A Large-Scale AI Feedback Dataset for Large Vision-Language Models Alignment
Lei Li, Zhihui Xie, Mukai Li +7
As large vision-language models (LVLMs) evolve rapidly, the demand for high-quality and diverse data to align these models becomes increasingly crucial. However, the creation of su…
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…
DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence
DeepSeek-AI, Qihao Zhu, Daya Guo +37
We present DeepSeek-Coder-V2, an open-source Mixture-of-Experts (MoE) code language model that achieves performance comparable to GPT4-Turbo in code-specific tasks. Specifically, D…
Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models
Lei Li, Yuqi Wang, Runxin Xu +4
Large vision-language models (LVLMs) excel across diverse tasks involving concrete images from natural scenes. However, their ability to interpret abstract figures, such as geometr…