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20212026
most citedA Preliminary Evaluation of ChatGPT for Zero-shot Dialogue Understanding

21 citations · 83 across the 49 of their papers we have counts for

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12 papers · 1 filter

cs.CL2026

Unfolding Scientific Papers into Multi-Turn Generation Trajectories for Continued Pre-Training

Qiankai Xu, Qiguang Chen, Zixin Su +4

A recent line of synthetic-data work reconstructs the thinking behind existing text rather than rewriting the text itself, but it operates on short web passages, recovers only loca…

cs.CV2026

Thinking in Video: Can Video Generators Really Reason About the Real World?

Yongheng Zhang, Guang Yang, Ruihan Hou +12

Recent advances in world models and video generation have given rise to an emerging reasoning paradigm that leverages video generative models to simulate, predict, and reason about…

cs.SE2026

Dashboard2Code: Evaluating Multimodal Models on Reconstructing Interactive Dashboards

Tianhao Niu, Ziyu Han, Qiguang Chen +5

Automatic data visualization generation has advanced rapidly with multi-modal large language models, yet existing efforts largely focus on static charts and overlook the interactiv…

cs.CL2026

The Scaling Laws of Skills in LLM Agent Systems

Charles Chen, Qiming Yu, Yuhang Gu +12

As agent systems scale, skills accumulate into large reusable libraries, yet their scaling laws remain poorly understood. Across 15 frontier LLMs, 1,141 real-world skills, and over…

cs.CR2026

Do Coding Agents Understand Least-Privilege Authorization?

Zheng Yan, Jingxiang Weng, Charles Chen +9

As coding agents gain access to shells, repositories, and user files, least-privilege authorization becomes a prerequisite for safe deployment: an agent should receive enough autho…

cs.CV2026

ClawMark: A Living-World Benchmark for Multi-Turn, Multi-Day, Multimodal Coworker Agents

Fanqing Meng, Lingxiao Du, Zijian Wu +46

Language-model agents are increasingly used as persistent coworkers that assist users across multiple working days. During such workflows, the surrounding environment may change in…

cs.CV2026

OMIBench: Benchmarking Olympiad-Level Multi-Image Reasoning in Large Vision-Language Model

Qiguang Chen, Chengyu Luan, Jiajun Wu +7

Large vision-language models (LVLMs) have made substantial advances in reasoning tasks at the Olympiad level. Nevertheless, current Olympiad-level multimodal reasoning benchmarks f…

cs.CL2026

Less Languages, Less Tokens: An Efficient Unified Logic Cross-lingual Chain-of-Thought Reasoning Framework

Chenyuan Zhang, Qiguang Chen, Xie Chen +6

Cross-lingual chain-of-thought (XCoT) with self-consistency markedly enhances multilingual reasoning, yet existing methods remain costly due to extensive sampling of full trajector…

cs.CV2026

Let's Think with Images Efficiently! An Interleaved-Modal Chain-of-Thought Reasoning Framework with Dynamic and Precise Visual Thoughts

Xu Liu, Yongheng Zhang, Qiguang Chen +3

Recently, Interleaved-modal Chain-of-Thought (ICoT) reasoning has achieved remarkable success by leveraging both multimodal inputs and outputs, attracting increasing attention. Whi…

cs.AI2026

BABE: Biology Arena BEnchmark

Junting Zhou, Jin Chen, Linfeng Hao +10

The rapid evolution of large language models (LLMs) has expanded their capabilities from basic dialogue to advanced scientific reasoning. However, existing benchmarks in biology of…

cs.CL2026

Learning the Boundary of Solvability: Aligning LLMs to Detect Unsolvable Problems

Dengyun Peng, Qiguang Chen, Bofei Liu +6

Ensuring large language model (LLM) reliability requires distinguishing objective unsolvability (inherent contradictions) from subjective capability limitations (tasks exceeding mo…

cs.CL2026

The Molecular Structure of Thought: Mapping the Topology of Long Chain-of-Thought Reasoning

Qiguang Chen, Yantao Du, Ziniu Li +10

Large language models (LLMs) often fail to learn effective long chain-of-thought (Long CoT) reasoning from human or non-Long-CoT LLMs imitation. To understand this, we propose that…