2 citations · 2 across the 8 of their papers we have counts for
8 papers
ReviewGrounder: Improving Review Substantiveness with Rubric-Guided, Tool-Integrated Agents
Zhuofeng Li, Yi Lu, Dongfu Jiang +7
The rapid rise in AI conference submissions has driven increasing exploration of large language models (LLMs) for peer review support. However, LLM-based reviewers often generate s…
ImagenWorld: Stress-Testing Image Generation Models with Explainable Human Evaluation on Open-ended Real-World Tasks
Samin Mahdizadeh Sani, Max Ku, Nima Jamali +23
Advances in diffusion, autoregressive, and hybrid models have enabled high-quality image synthesis for tasks such as text-to-image, editing, and reference-guided composition. Yet,…
OpenResearcher: A Fully Open Pipeline for Long-Horizon Deep Research Trajectory Synthesis
Zhuofeng Li, Dongfu Jiang, Xueguang Ma +7
Training deep research agents requires long-horizon trajectories that interleave search, evidence aggregation, and multi-step reasoning. However, existing data collection pipelines…
GraphDancer: Training LLMs to Explore and Reason over Graphs via Curriculum Reinforcement Learning
Yuyang Bai, Zhuofeng Li, Ping Nie +3
Large language models (LLMs) increasingly rely on external knowledge to improve factuality, yet many knowledge sources on the Web, such as scholarly indexes and product catalogs, a…
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…
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-…
VideoEval-Pro: Robust and Realistic Long Video Understanding Evaluation
Wentao Ma, Weiming Ren, Yiming Jia +4
Large multimodal models (LMMs) have recently emerged as a powerful tool for long video understanding (LVU), prompting the development of standardized LVU benchmarks to evaluate the…
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…