66 citations · 122 across the 30 of their papers we have counts for
8 papers · 1 filter
VisDocAgentBench: Benchmarking Agents for Visually Rich Document Retrieval
Lexiang Hu, Yanzhao Zhang, Mingxin Li +5
Visually rich documents encode relevance through language, layout, structured visual elements, and corpus context, yet retrieval is typically evaluated by one-shot query--page matc…
DEPT: Document Embedding Preservation Tuning for Unified Query Expansion and Retrieval
Jingyuan Wang, Richong Zhang, Zhijie Nie +2
Large language models (LLMs) can both expand underspecified queries and encode text as dense representations, suggesting a unified model for query expansion and retrieval. Existing…
CORE-Bench: A Comprehensive Benchmark for Code Retrieval in the Era of Agentic Coding
Fuwei Zhang, Yanzhao Zhang, Mingxin Li +5
Code retrieval is becoming central to coding agents, but agentic coding requires more than matching a natural-language query to an isolated snippet. Given a user request, a coding…
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…
ERank: Fusing Supervised Fine-Tuning and Reinforcement Learning for Effective and Efficient Text Reranking
Yuzheng Cai, Yanzhao Zhang, Dingkun Long +3
Text reranking models are a crucial component in modern systems like Retrieval-Augmented Generation, tasked with selecting the most relevant documents prior to generation. However,…
A Two-Stage Adaptation of Large Language Models for Text Ranking
Longhui Zhang, Yanzhao Zhang, Dingkun Long +3
Text ranking is a critical task in information retrieval. Recent advances in pre-trained language models (PLMs), especially large language models (LLMs), present new opportunities…
Challenging Decoder helps in Masked Auto-Encoder Pre-training for Dense Passage Retrieval
Zehan Li, Yanzhao Zhang, Dingkun Long +1
Recently, various studies have been directed towards exploring dense passage retrieval techniques employing pre-trained language models, among which the masked auto-encoder (MAE) p…
HLATR: Enhance Multi-stage Text Retrieval with Hybrid List Aware Transformer Reranking
Yanzhao Zhang, Dingkun Long, Guangwei Xu +1
Deep pre-trained language models (e,g. BERT) are effective at large-scale text retrieval task. Existing text retrieval systems with state-of-the-art performance usually adopt a ret…