activity
20232026
most citedFusion-in-T5: Unifying Document Ranking Signals for Improved Information Retrieval

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.IR2026

MoDora: Tree-Based Semi-Structured Document Analysis System

Bangrui Xu, Qihang Yao, Zirui Tang +8

Semi-structured documents integrate diverse interleaved data elements (e.g., tables, charts, hierarchical paragraphs) arranged in various and often irregular layouts. These documen…

cs.IR2025

LISRec: Modeling User Preferences with Learned Item Shortcuts for Sequential Recommendation

Haidong Xin, Zhenghao Liu, Sen Mei +7

User-item interaction histories are pivotal for sequential recommendation systems but often include noise, such as unintended clicks or actions that fail to reflect genuine user pr…

cs.CL2025

Craw4LLM: Efficient Web Crawling for LLM Pretraining

Shi Yu, Zhiyuan Liu, Chenyan Xiong

Web crawl is a main source of large language models' (LLMs) pretraining data, but the majority of crawled web pages are discarded in pretraining due to low data quality. This paper…

cs.CL2024★ 1 cited

Say More with Less: Understanding Prompt Learning Behaviors through Gist Compression

Xinze Li, Zhenghao Liu, Chenyan Xiong +4

Large language models (LLMs) require lengthy prompts as the input context to produce output aligned with user intentions, a process that incurs extra costs during inference. In thi…

cs.IR2023★ 2 cited

Fusion-in-T5: Unifying Document Ranking Signals for Improved Information Retrieval

Shi Yu, Chenghao Fan, Chenyan Xiong +3

Common document ranking pipelines in search systems are cascade systems that involve multiple ranking layers to integrate different information step-by-step. In this paper, we prop…