240 citations · 1.3k across the 195 of their papers we have counts for
6 papers · 1 filter
TREND-10K: A Comprehensive Dataset for Next-Generation Video Quality Assessment Based on Preference-Driven Media
Ziheng Jia, Zicheng Zhang, Junqi Zhang +4
The increasing prominence of short-video platforms, coupled with the advanced commercialization of AI-generated content (AIGC) videos, has led to a shift in the types of video medi…
RAVEN-Eval: Rubric-Guided Automatic Evaluation for AI Video Generation Models Based on LMM Preference Judgement
Ziheng Jia, Jiaying Qian, Zicheng Zhang +3
AI video generation has advanced rapidly and entered widespread commercial use. As a result, quality differences among videos produced by state-of-the-art AI video generation model…
Market-Bench: Benchmarking Large Language Models on Economic and Trade Competition
Yushuo Zheng, Huiyu Duan, Zicheng Zhang +3
The ability of large language models (LLMs) to manage and acquire economic resources remains unclear. In this paper, we introduce \textbf{Market-Bench}, a comprehensive benchmark t…
LifeEval: A Multimodal Benchmark for Assistive AI in Egocentric Daily Life Tasks
Hengjian Gao, Kaiwei Zhang, Shibo Wang +8
The rapid progress of Multimodal Large Language Models (MLLMs) marks a significant step toward artificial general intelligence, offering great potential for augmenting human capabi…
LM Fight Arena: Benchmarking Large Multimodal Models via Game Competition
Yushuo Zheng, Zicheng Zhang, Tongrui Ye +3
Existing benchmarks for large multimodal models (LMMs) often fail to capture their performance in real-time, adversarial environments. We introduce LM Fight Arena (Large Model Figh…
Who is a Better Player: LLM against LLM
Yingjie Zhou, Jiezhang Cao, Farong Wen +10
Adversarial board games, as a paradigmatic domain of strategic reasoning and intelligence, have long served as both a popular competitive activity and a benchmark for evaluating ar…