6 citations · 8 across the 8 of their papers we have counts for
8 papers
DiffuRank: Effective Document Reranking with Diffusion Language Models
Qi Liu, Kun Ai, Jiaxin Mao +6
Recent advances in large language models (LLMs) have inspired new paradigms for document reranking. While this paradigm better exploits the reasoning and contextual understanding c…
E2Rank: Unifying Text Embedding and Listwise Reranking for Effective and Efficient Search
Qi Liu, Yanzhao Zhang, Mingxin Li +3
Text embedding models deliver competitive retrieval performance with high efficiency, but their ranking fidelity remains limited compared to LLM-based listwise rerankers, which cap…
How do Large Language Models Understand Relevance? A Mechanistic Interpretability Perspective
Qi Liu, Jiaxin Mao, Ji-Rong Wen
Recent studies have shown that large language models (LLMs) can assess relevance and support information retrieval (IR) tasks such as document ranking and relevance judgment genera…
LLM4Ranking: An Easy-to-use Framework of Utilizing Large Language Models for Document Reranking
Qi Liu, Haozhe Duan, Yiqun Chen +3
Utilizing large language models (LLMs) for document reranking has been a popular and promising research direction in recent years, many studies are dedicated to improving the perfo…
PanguIR Technical Report for NTCIR-18 AEOLLM Task
Lang Mei, Chong Chen, Jiaxin Mao
As large language models (LLMs) gain widespread attention in both academia and industry, it becomes increasingly critical and challenging to effectively evaluate their capabilities…
Mamba Retriever: Utilizing Mamba for Effective and Efficient Dense Retrieval
Hanqi Zhang, Chong Chen, Lang Mei +2
In the information retrieval (IR) area, dense retrieval (DR) models use deep learning techniques to encode queries and passages into embedding space to compute their semantic relat…
Leveraging Passage Embeddings for Efficient Listwise Reranking with Large Language Models
Qi Liu, Bo Wang, Nan Wang +1
Recent studies have demonstrated the effectiveness of using large language language models (LLMs) in passage ranking. The listwise approaches, such as RankGPT, have become new stat…
An Analysis on Matching Mechanisms and Token Pruning for Late-interaction Models
Qi Liu, Gang Guo, Jiaxin Mao +5
With the development of pre-trained language models, the dense retrieval models have become promising alternatives to the traditional retrieval models that rely on exact match and…