most citedHALC: Object Hallucination Reduction via Adaptive Focal-Contrast Decoding

3 citations · 4 across the 8 of their papers we have counts for

collaborators

9 papers

cs.AI2025

Scaling Agent Learning via Experience Synthesis

Zhaorun Chen, Zhuokai Zhao, Kai Zhang +15

While reinforcement learning (RL) can empower autonomous agents by enabling self-improvement through interaction, its practical adoption remains challenging due to costly rollouts,…

cs.CV2025

GLIMPSE: Do Large Vision-Language Models Truly Think With Videos or Just Glimpse at Them?

Yiyang Zhou, Linjie Li, Shi Qiu +10

Existing video benchmarks often resemble image-based benchmarks, with question types like "What actions does the person perform throughout the video?" or "What color is the woman's…

cs.AI2025

From EduVisBench to EduVisAgent: A Benchmark and Multi-Agent Framework for Reasoning-Driven Pedagogical Visualization

Haonian Ji, Shi Qiu, Siyang Xin +5

While foundation models (FMs), such as diffusion models and large vision-language models (LVLMs), have been widely applied in educational contexts, their ability to generate pedago…

cs.CV2025

MJ-VIDEO: Fine-Grained Benchmarking and Rewarding Video Preferences in Video Generation

Haibo Tong, Zhaoyang Wang, Zhaorun Chen +11

Recent advancements in video generation have significantly improved the ability to synthesize videos from text instructions. However, existing models still struggle with key challe…

cs.CV2024

Fine-Grained Verifiers: Preference Modeling as Next-token Prediction in Vision-Language Alignment

Chenhang Cui, An Zhang, Yiyang Zhou +4

The recent advancements in large language models (LLMs) and pre-trained vision models have accelerated the development of vision-language large models (VLLMs), enhancing the intera…

cs.CV2024

MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation?

Zhaorun Chen, Yichao Du, Zichen Wen +16

While text-to-image models like DALLE-3 and Stable Diffusion are rapidly proliferating, they often encounter challenges such as hallucination, bias, and the production of unsafe, l…

cs.CL2024

Can Editing LLMs Inject Harm?

Canyu Chen, Baixiang Huang, Zekun Li +12

Large Language Models (LLMs) have emerged as a new information channel. Meanwhile, one critical but under-explored question is: Is it possible to bypass the safety alignment and in…

cs.CV2024★ 3 cited

HALC: Object Hallucination Reduction via Adaptive Focal-Contrast Decoding

Zhaorun Chen, Zhuokai Zhao, Hongyin Luo +3

While large vision-language models (LVLMs) have demonstrated impressive capabilities in interpreting multi-modal contexts, they invariably suffer from object hallucinations (OH). W…

cs.CL2024★ 1 cited

AutoPRM: Automating Procedural Supervision for Multi-Step Reasoning via Controllable Question Decomposition

Zhaorun Chen, Zhuokai Zhao, Zhihong Zhu +4

Recent advancements in large language models (LLMs) have shown promise in multi-step reasoning tasks, yet their reliance on extensive manual labeling to provide procedural feedback…