3 citations · 4 across the 9 of their papers we have counts for
9 papers
EM^2Mem: Event-Centric Multimodal Memory for Large Language Models
Yijun Chen, Yaqi Zheng, Yanya Li +11
Multimodal memory offers a scalable interface for long-video question answering, but existing methods often retrieve captions, frames, transcripts, summaries, or graph facts as iso…
Rethinking Message Passing as Retrieval for Text-Attributed Graph Learning
Jintang Li, Yuhong Chen, Ruofan Wu +4
Graph neural networks (GNNs) are typically conceptualized as message-passing neural networks, yet it remains unclear why neighborhood aggregation reliably outperforms node-wise mul…
LightMem-Ego: Your AI Memory for Everyday Life
Yijun Chen, Boyi Xiao, Yixian Zhao +10
Personal AI assistants on mobile and wearable devices continuously perceive users' daily lives through visual and audio streams. However, answering queries about past experiences r…
QCA: Query- and Content-Aware Keyframe Selection for Long Video Understanding
Jun Peng, Baiyang Song, Jie Li +4
Video understanding is often plagued by severe temporal redundancy, where processing dense frame sequences is both semantically inefficient and computationally expensive. This chal…
Semantic and Visual Evidence for Efficient Long-Video Reasoning: A Solution for the HD-EPIC VQA Challenge
Yinsong Xu, Wei Jing, Liuxin Zhang +2
Understanding long-form egocentric videos remains challenging for multimodal large language models (MLLMs) due to limited context length and insufficient grounding of fine-grained…
Towards Effective Long Video Understanding of Multimodal Large Language Models via One-shot Clip Retrieval
Tao Chen, Shaobo Ju, Qiong Wu +6
Due to excessive memory overhead, most Multimodal Large Language Models (MLLMs) can only process videos of limited frames. In this paper, we propose an effective and efficient para…
MMICT: Boosting Multi-Modal Fine-Tuning with In-Context Examples
Tao Chen, Enwei Zhang, Yuting Gao +5
Although In-Context Learning (ICL) brings remarkable performance gains to Large Language Models (LLMs), the improvements remain lower than fine-tuning on downstream tasks. This pap…
PDF: Point Diffusion Implicit Function for Large-scale Scene Neural Representation
Yuhan Ding, Fukun Yin, Jiayuan Fan +6
Recent advances in implicit neural representations have achieved impressive results by sampling and fusing individual points along sampling rays in the sampling space. However, due…
MMAPS: End-to-End Multi-Grained Multi-Modal Attribute-Aware Product Summarization
Tao Chen, Ze Lin, Hui Li +4
Given the long textual product information and the product image, Multi-modal Product Summarization (MPS) aims to increase customers' desire to purchase by highlighting product cha…