1 citations · 2 across the 5 of their papers we have counts for
9 papers
MMViR: A Multi-Modal and Multi-Granularity Representation for Long-range Video Understanding
Zizhong Li, Haopeng Zhang, Jiawei Zhang
Long videos, ranging from minutes to hours, present significant challenges for current Multi-modal Large Language Models (MLLMs) due to their complex events, diverse scenes, and lo…
Token-Level Precise Attack on RAG: Searching for the Best Alternatives to Mislead Generation
Zizhong Li, Haopeng Zhang, Jiawei Zhang
While large language models (LLMs) have achieved remarkable success in providing trustworthy responses for knowledge-intensive tasks, they still face critical limitations such as h…
AIGVE-Tool: AI-Generated Video Evaluation Toolkit with Multifaceted Benchmark
Xinhao Xiang, Xiao Liu, Zizhong Li +2
The rapid advancement in AI-generated video synthesis has led to a growth demand for standardized and effective evaluation metrics. Existing metrics lack a unified framework for sy…
A Survey of AI-Generated Video Evaluation
Xiao Liu, Xinhao Xiang, Zizhong Li +6
The growing capabilities of AI in generating video content have brought forward significant challenges in effectively evaluating these videos. Unlike static images or text, video c…
Intermediate Distillation: Data-Efficient Distillation from Black-Box LLMs for Information Retrieval
Zizhong Li, Haopeng Zhang, Jiawei Zhang
Recent research has explored distilling knowledge from large language models (LLMs) to optimize retriever models, especially within the retrieval-augmented generation (RAG) framewo…
Unveiling the Magic: Investigating Attention Distillation in Retrieval-augmented Generation
Zizhong Li, Haopeng Zhang, Jiawei Zhang
Retrieval-augmented generation framework can address the limitations of large language models by enabling real-time knowledge updates for more accurate answers. An efficient way in…