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cs.CL2026
Multimodal RewardBench 2: Evaluating Omni Reward Models for Interleaved Text and Image
Yushi Hu, Reyhane Askari-Hemmat, Melissa Hall +3
Reward models (RMs) are essential for training large language models (LLMs), but remain underexplored for omni models that handle interleaved image and text sequences. We introduce…
cs.CL2024★ 1 cited
Training Language Models to Generate Text with Citations via Fine-grained Rewards
Chengyu Huang, Zeqiu Wu, Yushi Hu +1
While recent Large Language Models (LLMs) have proven useful in answering user queries, they are prone to hallucination, and their responses often lack credibility due to missing r…