activity
20242026
most citedMTVQA: Benchmarking Multilingual Text-Centric Visual Question Answering

5 citations · 8 across the 9 of their papers we have counts for

collaborators

10 papers

cs.AI2026

When Teachers Mislead: Spurious-Signal-Aware On-Policy Distillation

Yinuo Jiang, Yongjie Ye, Zhou Tao +4

On-Policy distillation (OPD) transfers teacher capabilities by supervising student-sampled trajectories with dense token-level teacher signals. Recent selective OPD methods improve…

cs.CV2025

ChineseVideoBench: Benchmarking Multi-modal Large Models for Chinese Video Question Answering

Yuxiang Nie, Han Wang, Yongjie Ye +15

This paper introduces ChineseVideoBench, a pioneering benchmark specifically designed for evaluating Multimodal Large Language Models (MLLMs) in Chinese Video Question Answering. T…

cs.CV2025

SAIL-RL: Guiding MLLMs in When and How to Think via Dual-Reward RL Tuning

Fangxun Shu, Yongjie Ye, Yue Liao +6

We introduce SAIL-RL, a reinforcement learning (RL) post-training framework that enhances the reasoning capabilities of multimodal large language models (MLLMs) by teaching them wh…

cs.CV2025★ 1 cited

SAIL-VL2 Technical Report

Weijie Yin, Yongjie Ye, Fangxun Shu +11

We introduce SAIL-VL2, an open-suite vision-language foundation model (LVM) for comprehensive multimodal understanding and reasoning. As the successor to SAIL-VL, SAIL-VL2 achieves…

cs.CV2025

Vision as LoRA

Han Wang, Yongjie Ye, Bingru Li +5

We introduce Vision as LoRA (VoRA), a novel paradigm for transforming an LLM into an MLLM. Unlike prevalent MLLM architectures that rely on external vision modules for vision encod…

cs.CV2024

Dynamic-VLM: Simple Dynamic Visual Token Compression for VideoLLM

Han Wang, Yuxiang Nie, Yongjie Ye +6

The application of Large Vision-Language Models (LVLMs) for analyzing images and videos is an exciting and rapidly evolving field. In recent years, we've seen significant growth in…

cs.CL2024

A Bounding Box is Worth One Token: Interleaving Layout and Text in a Large Language Model for Document Understanding

Jinghui Lu, Haiyang Yu, Yanjie Wang +9

Recently, many studies have demonstrated that exclusively incorporating OCR-derived text and spatial layouts with large language models (LLMs) can be highly effective for document…

cs.CV2024★ 1 cited

TabPedia: Towards Comprehensive Visual Table Understanding with Concept Synergy

Weichao Zhao, Hao Feng, Qi Liu +9

Tables contain factual and quantitative data accompanied by various structures and contents that pose challenges for machine comprehension. Previous methods generally design task-s…

cs.CV2024★ 5 cited

MTVQA: Benchmarking Multilingual Text-Centric Visual Question Answering

Jingqun Tang, Qi Liu, Yongjie Ye +14

Text-Centric Visual Question Answering (TEC-VQA) in its proper format not only facilitates human-machine interaction in text-centric visual environments but also serves as a de fac…

cs.CV2024★ 1 cited

Elysium: Exploring Object-level Perception in Videos via MLLM

Han Wang, Yanjie Wang, Yongjie Ye +2

Multi-modal Large Language Models (MLLMs) have demonstrated their ability to perceive objects in still images, but their application in video-related tasks, such as object tracking…