activity
20242026
most citedStructEval: Benchmarking LLMs' Capabilities to Generate Structural Outputs

2 citations · 4 across the 16 of their papers we have counts for

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Showing 2025Show all

9 papers · 1 filter

cs.AI2025

VerlTool: Towards Holistic Agentic Reinforcement Learning with Tool Use

Dongfu Jiang, Yi Lu, Zhuofeng Li +9

Reinforcement Learning with Verifiable Rewards (RLVR) has demonstrated success in enhancing LLM reasoning capabilities, but remains limited to single-turn interactions without tool…

cs.CV2025

OpusAnimation: Code-Based Dynamic Chart Generation

Bozheng Li, Miao Yang, Zhenhan Chen +9

Dynamic Chart Generation (DCG) involves producing code-rendered animated visualizations as charts. While recent advances in multi-modal large language models (MLLMs) have significa…

cs.AI2025

Dr. Bench: A Multidimensional Evaluation for Deep Research Agents, from Answers to Reports

Yang Yao, Yixu Wang, Yuxuan Zhang +9

As an embodiment of intelligence evolution toward interconnected architectures, Deep Research Agents (DRAs) systematically exhibit the capabilities in task decomposition, cross-sou…

cs.CV2025

VideoScore2: Think before You Score in Generative Video Evaluation

Xuan He, Dongfu Jiang, Ping Nie +21

Recent advances in text-to-video generation have produced increasingly realistic and diverse content, yet evaluating such videos remains a fundamental challenge due to their multi-…

cs.CV2025

SoccerNet 2025 Challenges Results

Silvio Giancola, Anthony Cioppa, Marc Gutiérrez-Pérez +115

The SoccerNet 2025 Challenges mark the fifth annual edition of the SoccerNet open benchmarking effort, dedicated to advancing computer vision research in football video understandi…

cs.CV2025

RSVP: Reasoning Segmentation via Visual Prompting and Multi-modal Chain-of-Thought

Yi Lu, Jiawang Cao, Yongliang Wu +6

Multi-modal Large Language Models (MLLMs) have demonstrated remarkable reasoning capability while lack explicit mechanisms for visual grounding and segmentation, creating a gap bet…

cs.SE2025★ 2 cited

StructEval: Benchmarking LLMs' Capabilities to Generate Structural Outputs

Jialin Yang, Dongfu Jiang, Lipeng He +17

As Large Language Models (LLMs) become integral to software development workflows, their ability to generate structured outputs has become critically important. We introduce Struct…

cs.CV2025

VEU-Bench: Towards Comprehensive Understanding of Video Editing

Bozheng Li, Yongliang Wu, Yi Lu +7

Widely shared videos on the internet are often edited. Recently, although Video Large Language Models (Vid-LLMs) have made great progress in general video understanding tasks, thei…

cs.CL2025★ 1 cited

ScholarCopilot: Training Large Language Models for Academic Writing with Accurate Citations

Yubo Wang, Xueguang Ma, Ping Nie +7

Academic writing requires both coherent text generation and precise citation of relevant literature. Although recent Retrieval-Augmented Generation (RAG) systems have significantly…