most citedDataGovBench: Benchmarking LLM Agents for Real-World Data Governance Workflows

1 citations · 1 across the 8 of their papers we have counts for

collaborators

9 papers

cs.AI2026

SkillLens: Visual Skill Cards for Retrieval-Augmented GUI Action Prediction and On-Policy Distillation

Zhou Liu, Ligang Huang, Zeli Su +5

Computer-using agents can perceive rich software interfaces, yet their decisions often lack visual procedural memory: they may recognize individual controls without identifying whi…

cs.LG2026

DataPrep-Bench: Benchmarking LLMs as Training Data Preparators

Hao Liang, Qifeng Cai, Yibo Lin +11

The quality of training data fundamentally determines the capabilities of large language models (LLMs), yet no unified benchmark exists to measure how well LLMs, agents, and data-c…

cs.CL2026

K12-KGraph: A Curriculum-Aligned Knowledge Graph for Benchmarking and Training Educational LLMs

Hao Liang, Qihan Lin, Zhaoyang Han +5

Large language models are increasingly used in K-12 education, but existing benchmarks mainly test exam question answering rather than understanding how curriculum knowledge is str…

cs.LG2026

DataFlex: A Unified Framework for Data-Centric Dynamic Training of Large Language Models

Hao Liang, Zhengyang Zhao, Meiyi Qiang +22

Data-centric training has emerged as a promising direction for improving large language models (LLMs) by optimizing not only model parameters but also the selection, composition, a…

cs.CL2026

Towards Next-Generation LLM Training: From the Data-Centric Perspective

Hao Liang, Zhengyang Zhao, Zhaoyang Han +8

Large language models (LLMs) have demonstrated remarkable performance across a wide range of tasks and domains, with data playing a central role in enabling these advances. Despite…

cs.CV2026

LoVR: A Benchmark for Long Video Retrieval in Multimodal Contexts

Qifeng Cai, Hao Liang, Zhaoyang Han +6

Long videos contain a vast amount of information, making video-text retrieval an essential and challenging task in multimodal learning. However, existing benchmarks suffer from lim…