9 citations · 16 across the 12 of their papers we have counts for
13 papers
Beyond Polarization: The Generative Constraint of Chain-of-Thought in Pointwise Reranking
Xiaoyang Chen, Jie Liu, Haijin Liang +5
In pointwise document reranking, Chain-of-Thought models typically underperform direct scoring models. While existing diagnostics attribute this to inferior classification, score p…
Rank4Gen: RAG-Preference-Aligned Document Set Selection and Ranking
Yongqi Fan, Yuxiang Chu, Zhentao Xia +9
In the RAG paradigm, document ranking determines the evidence available to downstream generators. Through controlled analysis, we identify two phenomena underexplored by existing r…
Accelerating Multi-modal LLM Gaming Performance via Input Prediction and Mishit Correction
Ziyang Lin, Zixuan Sun, Sanhorn Chen +2
Real-time sequential control agents are often bottlenecked by inference latency. Even modest per-step planning delays can destabilize control and degrade overall performance. We pr…
TFRank: Think-Free Reasoning Enables Practical Pointwise LLM Ranking
Yongqi Fan, Xiaoyang Chen, Dezhi Ye +6
Reasoning-intensive ranking models built on Large Language Models (LLMs) have made notable progress. However, existing approaches often rely on large-scale LLMs and explicit Chain-…
DeepMath-Creative: A Benchmark for Evaluating Mathematical Creativity of Large Language Models
Xiaoyang Chen, Xinan Dai, Yu Du +28
To advance the mathematical proficiency of large language models (LLMs), the DeepMath team has launched an open-source initiative aimed at developing an open mathematical LLM and s…
3D-AffordanceLLM: Harnessing Large Language Models for Open-Vocabulary Affordance Detection in 3D Worlds
Hengshuo Chu, Xiang Deng, Qi Lv +4
3D Affordance detection is a challenging problem with broad applications on various robotic tasks. Existing methods typically formulate the detection paradigm as a label-based sema…
Match, Compare, or Select? An Investigation of Large Language Models for Entity Matching
Tianshu Wang, Xiaoyang Chen, Hongyu Lin +5
Entity matching (EM) is a critical step in entity resolution (ER). Recently, entity matching based on large language models (LLMs) has shown great promise. However, current LLM-bas…
Towards Universal Dense Blocking for Entity Resolution
Tianshu Wang, Hongyu Lin, Xianpei Han +3
Blocking is a critical step in entity resolution, and the emergence of neural network-based representation models has led to the development of dense blocking as a promising approa…
Spiral of Silence: How is Large Language Model Killing Information Retrieval? -- A Case Study on Open Domain Question Answering
Xiaoyang Chen, Ben He, Hongyu Lin +5
The practice of Retrieval-Augmented Generation (RAG), which integrates Large Language Models (LLMs) with retrieval systems, has become increasingly prevalent. However, the repercus…
Offline Pseudo Relevance Feedback for Efficient and Effective Single-pass Dense Retrieval
Xueru Wen, Xiaoyang Chen, Xuanang Chen +2
Dense retrieval has made significant advancements in information retrieval (IR) by achieving high levels of effectiveness while maintaining online efficiency during a single-pass r…
Understanding Differential Search Index for Text Retrieval
Xiaoyang Chen, Yanjiang Liu, Ben He +2
The Differentiable Search Index (DSI) is a novel information retrieval (IR) framework that utilizes a differentiable function to generate a sorted list of document identifiers in r…
Groupwise Query Performance Prediction with BERT
Xiaoyang Chen, Ben He, Le Sun
While large-scale pre-trained language models like BERT have advanced the state-of-the-art in IR, its application in query performance prediction (QPP) is so far based on pointwise…
Co-BERT: A Context-Aware BERT Retrieval Model Incorporating Local and Query-specific Context
Xiaoyang Chen, Kai Hui, Ben He +3
BERT-based text ranking models have dramatically advanced the state-of-the-art in ad-hoc retrieval, wherein most models tend to consider individual query-document pairs independent…