14 citations · 16 across the 6 of their papers we have counts for
7 papers
TimelineAgent: An LLM-based Framework for Query-Centric Event Timeline Extraction Across Multiple Documents
Qingkai Min, Yunxin Bao, Yifeng Lu +4
Query-centric cross-document event timeline extraction aims to construct event timelines from multiple documents under diverse query focuses. The task is very challenging due to th…
AI Historian: Helping historians organize and verify person-centred temporal clues from dispersed historical narratives
Yifeng Lu, Zijie Yang, Jie Li +2
History is not preserved in complete, continuous form. Accounts of a person's activities, relationships and historical contexts are scattered across texts, chapters and narrative p…
OpenResearcher: Unleashing AI for Accelerated Scientific Research
Yuxiang Zheng, Shichao Sun, Lin Qiu +13
The rapid growth of scientific literature imposes significant challenges for researchers endeavoring to stay updated with the latest advancements in their fields and delve into new…
Synergetic Event Understanding: A Collaborative Approach to Cross-Document Event Coreference Resolution with Large Language Models
Qingkai Min, Qipeng Guo, Xiangkun Hu +3
Cross-document event coreference resolution (CDECR) involves clustering event mentions across multiple documents that refer to the same real-world events. Existing approaches utili…
A Rationale-centric Counterfactual Data Augmentation Method for Cross-Document Event Coreference Resolution
Bowen Ding, Qingkai Min, Shengkun Ma +3
Based on Pre-trained Language Models (PLMs), event coreference resolution (ECR) systems have demonstrated outstanding performance in clustering coreferential events across document…
Dialogue State Induction Using Neural Latent Variable Models
Qingkai Min, Libo Qin, Zhiyang Teng +2
Dialogue state modules are a useful component in a task-oriented dialogue system. Traditional methods find dialogue states by manually labeling training corpora, upon which neural…
A Pilot Study for Chinese SQL Semantic Parsing
Qingkai Min, Yuefeng Shi, Yue Zhang
The task of semantic parsing is highly useful for dialogue and question answering systems. Many datasets have been proposed to map natural language text into SQL, among which the r…