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20242026
most citedMMLongBench-Doc: Benchmarking Long-context Document Understanding with Visualizations

1 citations · 1 across the 11 of their papers we have counts for

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cs.CV2025

Visual Programmability: A Guide for Code-as-Thought in Chart Understanding

Bohao Tang, Yan Ma, Fei Zhang +6

Chart understanding presents a critical test to the reasoning capabilities of Vision-Language Models (VLMs). Prior approaches face critical limitations: some rely on external tools…

cs.CL2025

Interaction as Intelligence: Deep Research With Human-AI Partnership

Lyumanshan Ye, Xiaojie Cai, Xinkai Wang +23

This paper introduces "Interaction as Intelligence" research series, presenting a reconceptualization of human-AI relationships in deep research tasks. Traditional approaches treat…

cs.CV2025

Thinking with Images for Multimodal Reasoning: Foundations, Methods, and Future Frontiers

Zhaochen Su, Peng Xia, Hangyu Guo +12

Recent progress in multimodal reasoning has been significantly advanced by textual Chain-of-Thought (CoT), a paradigm where models conduct reasoning within language. This text-cent…

cs.CV2025

Thinking with Generated Images

Ethan Chern, Zhulin Hu, Steffi Chern +5

We present Thinking with Generated Images, a novel paradigm that fundamentally transforms how large multimodal models (LMMs) engage with visual reasoning by enabling them to native…

cs.CV2025

One RL to See Them All: Visual Triple Unified Reinforcement Learning

Yan Ma, Linge Du, Xuyang Shen +7

Reinforcement learning (RL) is becoming an important direction for post-training vision-language models (VLMs), but public training methodologies for unified multimodal RL remain m…

cs.CL2025

Generative AI Act II: Test Time Scaling Drives Cognition Engineering

Shijie Xia, Yiwei Qin, Xuefeng Li +11

The first generation of Large Language Models - what might be called "Act I" of generative AI (2020-2023) - achieved remarkable success through massive parameter and data scaling,…

cs.LG2025

Rethinking RL Scaling for Vision Language Models: A Transparent, From-Scratch Framework and Comprehensive Evaluation Scheme

Yan Ma, Steffi Chern, Xuyang Shen +2

Reinforcement learning (RL) has recently shown strong potential in improving the reasoning capabilities of large language models and is now being actively extended to vision-langua…