6 papers
OmniMapBench: Benchmarking Visual-Centric Reasoning on Diverse Map Documents
Yang Chen, Yunwen Li, Yufan Shen +6
Recent advancements in LVLMs necessitate robust benchmarks for complex, visually grounded reasoning. A critical limitation is identified in many document understanding benchmarks:…
Investigating Redundancy in Multimodal Large Language Models with Multiple Vision Encoders
Yizhou Wang, Song Mao, Yang Chen +8
Recent multimodal large language models (MLLMs) increasingly integrate multiple vision encoders to improve performance on various benchmarks, assuming that diverse pretraining obje…
R-AVST: Empowering Video-LLMs with Fine-Grained Spatio-Temporal Reasoning in Complex Audio-Visual Scenarios
Lu Zhu, Tiantian Geng, Yangye Chen +3
Recently, rapid advancements have been made in multimodal large language models (MLLMs), especially in video understanding tasks. However, current research focuses on simple video…
IWR-Bench: Can LVLMs reconstruct interactive webpage from a user interaction video?
Yang Chen, Minghao Liu, Yufan Shen +18
The webpage-to-code task requires models to understand visual representations of webpages and generate corresponding code. However, existing benchmarks primarily focus on static sc…
Learning Only with Images: Visual Reinforcement Learning with Reasoning, Rendering, and Visual Feedback
Yang Chen, Yufan Shen, Wenxuan Huang +7
Multimodal Large Language Models (MLLMs) exhibit impressive performance across various visual tasks. Subsequent investigations into enhancing their visual reasoning abilities have…
ProcTag: Process Tagging for Assessing the Efficacy of Document Instruction Data
Yufan Shen, Chuwei Luo, Zhaoqing Zhu +5
Recently, large language models (LLMs) and multimodal large language models (MLLMs) have demonstrated promising results on document visual question answering (VQA) task, particular…