16 citations · 44 across the 35 of their papers we have counts for
7 papers · 2 filters
Task Preference Optimization: Improving Multimodal Large Language Models with Vision Task Alignment
Ziang Yan, Zhilin Li, Yinan He +9
Current multimodal large language models (MLLMs) struggle with fine-grained or precise understanding of visuals although they give comprehensive perception and reasoning in a spect…
Bootstrapping Language-Guided Navigation Learning with Self-Refining Data Flywheel
Zun Wang, Jialu Li, Yicong Hong +8
Creating high-quality data for training robust language-instructed agents is a long-lasting challenge in embodied AI. In this paper, we introduce a Self-Refining Data Flywheel (SRD…
Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling
Zhe Chen, Weiyun Wang, Yue Cao +39
We introduce InternVL 2.5, an advanced multimodal large language model (MLLM) series that builds upon InternVL 2.0, maintaining its core model architecture while introducing signif…
SyncVIS: Synchronized Video Instance Segmentation
Rongkun Zheng, Lu Qi, Xi Chen +4
Recent DETR-based methods have advanced the development of Video Instance Segmentation (VIS) through transformers' efficiency and capability in modeling spatial and temporal inform…
ViLLa: Video Reasoning Segmentation with Large Language Model
Rongkun Zheng, Lu Qi, Xi Chen +4
Recent efforts in video reasoning segmentation (VRS) integrate large language models (LLMs) with perception models to localize and track objects via textual instructions, achieving…
InternVideo2: Scaling Foundation Models for Multimodal Video Understanding
Yi Wang, Kunchang Li, Xinhao Li +17
We introduce InternVideo2, a new family of video foundation models (ViFM) that achieve the state-of-the-art results in video recognition, video-text tasks, and video-centric dialog…