most citedMM-RLHF: The Next Step Forward in Multimodal LLM Alignment

1 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SE2025

CUARewardBench: A Benchmark for Evaluating Reward Models on Computer-using Agent

Haojia Lin, Xiaoyu Tan, Yulei Qin +9

Computer-using agents (CUAs) enable task completion through natural interaction with operating systems and software interfaces. While script-based verifiers are widely adopted for…

astro-ph.IM20251 cited

AstroMMBench: A Benchmark for Evaluating Multimodal Large Language Models Capabilities in Astronomy

Jinghang Shi, Xiaoyu Tang, Yang Huang +4

Astronomical image interpretation presents a significant challenge for applying multimodal large language models (MLLMs) to specialized scientific tasks. Existing benchmarks focus…

cs.CV2025

VITA-VLA: Efficiently Teaching Vision-Language Models to Act via Action Expert Distillation

Shaoqi Dong, Chaoyou Fu, Haihan Gao +12

Vision-Language Action (VLA) models significantly advance robotic manipulation by leveraging the strong perception capabilities of pretrained vision-language models (VLMs). By inte…

cs.CV2025

Human-MME: A Holistic Evaluation Benchmark for Human-Centric Multimodal Large Language Models

Yuansen Liu, Haiming Tang, Jinlong Peng +12

Multimodal Large Language Models (MLLMs) have demonstrated significant advances in visual understanding tasks. However, their capacity to comprehend human-centric scenes has rarely…

cs.CL20251 cited

MM-RLHF: The Next Step Forward in Multimodal LLM Alignment

Yi-Fan Zhang, Tao Yu, Haochen Tian +17

Despite notable advancements in Multimodal Large Language Models (MLLMs), most state-of-the-art models have not undergone thorough alignment with human preferences. This gap exists…

cs.CL2025

LUCY: Linguistic Understanding and Control Yielding Early Stage of Her

Heting Gao, Hang Shao, Xiong Wang +12

The film Her features Samantha, a sophisticated AI audio agent who is capable of understanding both linguistic and paralinguistic information in human speech and delivering real-ti…