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20242026
most citedRoVRM: A Robust Visual Reward Model Optimized via Auxiliary Textual Preference Data

1 citations · 1 across the 7 of their papers we have counts for

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cs.CL2025

Probing Preference Representations: A Multi-Dimensional Evaluation and Analysis Method for Reward Models

Chenglong Wang, Yifu Huo, Yang Gan +10

Previous methods evaluate reward models by testing them on a fixed pairwise ranking test set, but they typically do not provide performance information on each preference dimension…

cs.CL2025

MRO: Enhancing Reasoning in Diffusion Language Models via Multi-Reward Optimization

Chenglong Wang, Yang Gan, Hang Zhou +10

Recent advances in diffusion language models (DLMs) have presented a promising alternative to traditional autoregressive large language models (LLMs). However, DLMs still lag behin…

cs.CL2025

Higher Satisfaction, Lower Cost: A Technical Report on How LLMs Revolutionize Meituan's Intelligent Interaction Systems

Xuxin Cheng, Ke Zeng, Zhiquan Cao +65

Enhancing customer experience is essential for business success, particularly as service demands grow in scale and complexity. Generative artificial intelligence and Large Language…

cs.DC2025

Huawei Cloud Model-as-a-Service on the CloudMatrix384 SuperPod

Ao Xiao, Bangzheng He, Baoquan Zhang +125

Scaled-out MoE LLMs and scaled-up SuperPods create new systems challenges for production Model-as-a-Service (MaaS), requiring disaggregation, low-latency communication, and decentr…

cs.CL2025

GRAM: A Generative Foundation Reward Model for Reward Generalization

Chenglong Wang, Yang Gan, Yifu Huo +8

In aligning large language models (LLMs), reward models have played an important role, but are standardly trained as discriminative models and rely only on labeled human preference…