1 citations · 1 across the 7 of their papers we have counts for
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ChartJudgeBench: Evaluating LMM Judges for Chart-to-Code Generation
Lijian Wu, Henry Hengyuan Zhao, Zijian Zhang +3
Building strong chart-to-code systems increasingly relies on reinforcement learning, whose effectiveness depends critically on the quality of the reward signal. Large Multimodal Mo…
TempCloze: Can Video-LLMs Identify the Missing Middle?
Wenqi Pei, Henry Hengyuan Zhao, Yilai Liu +4
Temporal reasoning benchmarks for Video-LLMs are often mediated by language, leaving room for linguistic shortcuts from option wording, answer correlations, or language priors. To…
LOVA3: Learning to Visual Question Answering, Asking and Assessment
Henry Hengyuan Zhao, Pan Zhou, Difei Gao +2
Question answering, asking, and assessment are three innate human traits crucial for understanding the world and acquiring knowledge. By enhancing these capabilities, humans can mo…
Genixer: Empowering Multimodal Large Language Models as a Powerful Data Generator
Henry Hengyuan Zhao, Pan Zhou, Mike Zheng Shou
Multimodal Large Language Models (MLLMs) demonstrate exceptional problem-solving capabilities, but few research studies aim to gauge the ability to generate visual instruction tuni…
SCT: A Simple Baseline for Parameter-Efficient Fine-Tuning via Salient Channels
Henry Hengyuan Zhao, Pichao Wang, Yuyang Zhao +3
Pre-trained vision transformers have strong representation benefits to various downstream tasks. Recently, many parameter-efficient fine-tuning (PEFT) methods have been proposed, a…