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

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG2026

DivOPD: Spread Wide, Look Close for Asynchronous On-Policy Distillation of Multi-turn Agents

Hanyang Wang, Zeyuan Liu, Zhengyu Chen +7

On-policy distillation (OPD) trains student agents through teacher supervision on their own interactions with an environment. However, in asynchronous multi-turn training, arrival-…

cs.CV2026

VI-Bench: Benchmarking Prompt Inversion from AIGC Videos

Wulin Xie, Rui Zhao, Kecen Li +5

Recent advances in video generation have made prompt-based control increasingly central to AIGC video generation. Prompts specify what a video should depict and how it should be re…

cs.CV2025

MME-VideoOCR: Evaluating OCR-Based Capabilities of Multimodal LLMs in Video Scenarios

Yang Shi, Huanqian Wang, Wulin Xie +20

Multimodal Large Language Models (MLLMs) have achieved considerable accuracy in Optical Character Recognition (OCR) from static images. However, their efficacy in video OCR is sign…

cs.CV2025

MME-Unify: A Comprehensive Benchmark for Unified Multimodal Understanding and Generation Models

Wulin Xie, Yi-Fan Zhang, Chaoyou Fu +6

Existing MLLM benchmarks face significant challenges in evaluating Unified MLLMs (U-MLLMs) due to: 1) lack of standardized benchmarks for traditional tasks, leading to inconsistent…

cs.CL2025★ 1 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…