collaborators

7 papers

cs.CV2026

DyCo-RL: Dynamic Cross-Modal Coordination for Visual Reasoning

Hangui Lin, Yan Shu, Zhengyang Liang +6

Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a leading paradigm for enhancing visual reasoning in Multimodal Large Language Models (MLLMs). However, existin…

cs.DL2026

DeepXiv-SDK: An Agentic Data Interface for Scientific Literature

Hongjin Qian, Ziyi Xia, Ze Liu +11

LLM-agents are increasingly used to accelerate the progress of scientific research. Yet a persistent bottleneck is data access: agents not only lack readily available tools for ret…

cs.CV2026

MomentSeeker: A Task-Oriented Benchmark For Long-Video Moment Retrieval

Huaying Yuan, Jian Ni, Zheng Liu +7

Accurately locating key moments within long videos is crucial for solving long video understanding (LVU) tasks. However, existing benchmarks are either severely limited in terms of…

cs.CV2025

TimeScope: Towards Task-Oriented Temporal Grounding In Long Videos

Xiangrui Liu, Minghao Qin, Yan Shu +5

Identifying key temporal intervals within long videos, known as temporal grounding (TG), is important to video understanding and reasoning tasks. In this paper, we introduce a new…

cs.CV2025

Video-XL-2: Towards Very Long-Video Understanding Through Task-Aware KV Sparsification

Minghao Qin, Xiangrui Liu, Zhengyang Liang +6

Multi-modal large language models (MLLMs) models have made significant progress in video understanding over the past few years. However, processing long video inputs remains a majo…

cs.CV2025

Unveiling the Ignorance of MLLMs: Seeing Clearly, Answering Incorrectly

Yexin Liu, Zhengyang Liang, Yueze Wang +8

Multimodal Large Language Models (MLLMs) have displayed remarkable performance in multi-modal tasks, particularly in visual comprehension. However, we reveal that MLLMs often gener…