papers

Publications (53)

cs.CV2026

CapRiCorn-1K: A Comprehensive Benchmark for Video Captioning and Subject Referential Consistency Across Temporal Scales

Xinlong Chen, Jiafu Tang, Yue Ding +12

Accurate and comprehensive video captions with consistent subject references are critical for downstream understanding and generation tasks. However, few existing benchmarks can ob…

cs.AI2025

DataGovBench: Benchmarking LLM Agents for Real-World Data Governance Workflows

Zhou Liu, Zhaoyang Han, Guochen Yan +5

Data governance ensures data quality, security, and compliance through policies and standards, a critical foundation for scaling modern AI development. Recently, large language mod…

cs.CV2022

TerViT: An Efficient Ternary Vision Transformer

Sheng Xu, Yanjing Li, Teli Ma +4

Vision transformers (ViTs) have demonstrated great potential in various visual tasks, but suffer from expensive computational and memory cost problems when deployed on resource-con…

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.CV2025

VidBridge-R1: Bridging QA and Captioning for RL-based Video Understanding Models with Intermediate Proxy Tasks

Xinlong Chen, Yuanxing Zhang, Yushuo Guan +9

The "Reason-Then-Respond" paradigm, enhanced by Reinforcement Learning, has shown great promise in advancing Multimodal Large Language Models. However, its application to the video…

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…