activity
20242026
collaborators

5 papers

cs.CV2026

FoveaTree: Information-Density Trees for Query-Guided Visual Token Pruning in Video Large Language Models

Zihan Meng, Weidong Chen, Dexiang Hong +2

Video large language models (Video LLMs) encode each frame into hundreds of visual tokens, making video inference expensive. Existing methods reduce this cost through similarity-ba…

cs.CV2026

Audio-Visual Exchange-Aware Token Pruning for Efficient Audio-Visual Captioning

Zihan Meng, Dexiang Hong, Weidong Chen +3

Audio-visual captioning generates natural language descriptions from video and audio content. Multimodal LLMs have advanced this task, but both modalities contribute many tokens to…

cs.AI2025

Agent Learning via Early Experience

Kai Zhang, Xiangchao Chen, Bo Liu +27

A long-term goal of language agents is to learn and improve through their own experience, ultimately outperforming humans in complex, real-world tasks. However, training agents fro…

cs.CV2025

Bidirectional Likelihood Estimation with Multi-Modal Large Language Models for Text-Video Retrieval

Dohwan Ko, Ji Soo Lee, Minhyuk Choi +2

Text-Video Retrieval aims to find the most relevant text (or video) candidate given a video (or text) query from large-scale online databases. Recent work leverages multi-modal lar…

cs.CV2024

Visual Delta Generator with Large Multi-modal Models for Semi-supervised Composed Image Retrieval

Young Kyun Jang, Donghyun Kim, Zihang Meng +2

Composed Image Retrieval (CIR) is a task that retrieves images similar to a query, based on a provided textual modification. Current techniques rely on supervised learning for CIR…