activity
20242026
most citedLLaVA-CoT: Let Vision Language Models Reason Step-by-Step

4 citations · 5 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CL2026

PremiseCheck: Efficient Fact-Checking of Human and AI Peer Reviews

Dingjie Song, Zhiling Yan, Ziqian Zhang +2

Peer review is under strain from the growth of submissions, and review comments written by humans or AI can misstate what a paper says. We introduce ReviewFact, a benchmark that la…

cs.AI2026

LEV: Thinking Fast and Deep with Looped Decision Models

Dingjie Song, Zhiling Yan, Yuxuan Zhang +1

Decision models answer typed questions about an input with one probability per option, computed in a single forward pass without generating text. Like the fast System 1 of dual-pro…

cs.AI2026

Agents' Last Exam

Yiyou Sun, Xinyang Han, Weichen Zhang +355

Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful deployment across many professional d…

cs.AI2026

Towards a Medical AI Scientist

Hongtao Wu, Boyun Zheng, Dingjie Song +5

Autonomous systems that generate scientific hypotheses, conduct experiments, and draft manuscripts have recently emerged as a promising paradigm for accelerating discovery. However…

cs.AI2026

Can MLLMs Read Students' Minds? Unpacking Multimodal Error Analysis in Handwritten Math

Dingjie Song, Tianlong Xu, Yi-Fan Zhang +6

Assessing student handwritten scratchwork is crucial for personalized educational feedback but presents unique challenges due to diverse handwriting, complex layouts, and varied pr…

cs.CV2025★ 1 cited

From Correctness to Comprehension: AI Agents for Personalized Error Diagnosis in Education

Yi-Fan Zhang, Hang Li, Dingjie Song +3

Large Language Models (LLMs), such as GPT-4, have demonstrated impressive mathematical reasoning capabilities, achieving near-perfect performance on benchmarks like GSM8K. However,…

cs.CV2024★ 4 cited

LLaVA-CoT: Let Vision Language Models Reason Step-by-Step

Guowei Xu, Peng Jin, Ziang Wu +4

Large language models have demonstrated substantial advancements in reasoning capabilities. However, current Vision-Language Models (VLMs) often struggle to perform systematic and…

cs.CV2024

Both Text and Images Leaked! A Systematic Analysis of Data Contamination in Multimodal LLM

Dingjie Song, Sicheng Lai, Mingxuan Wang +3

The rapid advancement of multimodal large language models (MLLMs) has significantly enhanced performance across benchmarks. However, data contamination-unintentional memorization o…