8 citations · 20 across the 24 of their papers we have counts for
27 papers
MemScope: Evolving Agent Memory Architectures through Localized Code Repair
Miao Su, Yucan Guo, Zixuan Li +4
Agent memory architectures define how LLM agents store and reuse experience across tasks, but they are typically fixed after deployment, limiting their adaptability across task typ…
RAdapter: A Routing and Rewriting Adapter for Efficient Hybrid RAG
Yucan Guo, Miao Su, Saiping Guan +6
Retrieval-Augmented Generation (RAG) has become a prevailing paradigm for enhancing Large Language Models (LLMs) with non-parametric knowledge. Vanilla RAG efficiently handles simp…
FinDeepIndicator: Benchmarking Deep Research Agents in End-to-End Financial Indicator Construction
Chaoqun Yang, Fengbin Zhu, Xinyu Lin +5
Financial indicators are essential tools for transforming raw financial data into interpretable measures for various downstream tasks, such as valuation, risk assessment, and econo…
Event Ontology Expansion via LLM-Based Conceptualization
Weicheng Ren, Zixuan Li, Long Bai +3
Event ontology expansion aims to discover emerging event types from data and extend them to appropriate positions in the existing event ontology.. Existing methods typically cluste…
Beyond Dialogue Time: Temporal Semantic Memory for Personalized LLM Agents
Miao Su, Yucan Guo, Zhongni Hou +8
Memory enables Large Language Model (LLM) agents to perceive, store, and use information from past dialogues, which is essential for personalization. However, existing methods fail…
Maximizing Local Entropy Where It Matters: Prefix-Aware Localized LLM Unlearning
Naixin Zhai, Pengyang Shao, Binbin Zheng +4
Machine unlearning aims to forget sensitive knowledge from Large Language Models (LLMs) while maintaining general utility. However, existing approaches typically treat all tokens i…
KnowCoder-V2: Deep Knowledge Analysis
Zixuan Li, Wenxuan Liu, Long Bai +13
Deep knowledge analysis tasks always involve the systematic extraction and association of knowledge from large volumes of data, followed by logical reasoning to discover insights.…
G2S: A General-to-Specific Learning Framework for Temporal Knowledge Graph Forecasting with Large Language Models
Long Bai, Zixuan Li, Xiaolong Jin +3
Forecasting over Temporal Knowledge Graphs (TKGs) which predicts future facts based on historical ones has received much attention. Recent studies have introduced Large Language Mo…
Mixture Policy based Multi-Hop Reasoning over N-tuple Temporal Knowledge Graphs
Zhongni Hou, Miao Su, Xiaolong Jin +4
Temporal Knowledge Graphs (TKGs), which utilize quadruples in the form of (subject, predicate, object, timestamp) to describe temporal facts, have attracted extensive attention. N-…
Towards Robust Universal Information Extraction: Benchmark, Evaluation, and Solution
Jizhao Zhu, Akang Shi, Zixuan Li +4
In this paper, we aim to enhance the robustness of Universal Information Extraction (UIE) by introducing a new benchmark dataset, a comprehensive evaluation, and a feasible solutio…
Towards Event Extraction with Massive Types: LLM-based Collaborative Annotation and Partitioning Extraction
Wenxuan Liu, Zixuan Li, Long Bai +5
Developing a general-purpose extraction system that can extract events with massive types is a long-standing target in Event Extraction (EE). In doing so, the challenge comes from…
KnowCoder-X: Boosting Multilingual Information Extraction via Code
Yuxin Zuo, Wenxuan Jiang, Wenxuan Liu +7
Empirical evidence indicates that LLMs exhibit spontaneous cross-lingual alignment. However, although LLMs show promising cross-lingual alignment in Information Extraction (IE), a…
Temporal Knowledge Graph Question Answering: A Survey
Miao Su, Zixuan Li, Zhuo Chen +3
Knowledge Base Question Answering (KBQA) has been a long-standing field to answer questions based on knowledge bases. Recently, the evolving dynamics of knowledge have attracted a…
Graphical Reasoning: LLM-based Semi-Open Relation Extraction
Yicheng Tao, Yiqun Wang, Longju Bai
This paper presents a comprehensive exploration of relation extraction utilizing advanced language models, specifically Chain of Thought (CoT) and Graphical Reasoning (GRE) techniq…
Class-Incremental Few-Shot Event Detection
Kailin Zhao, Xiaolong Jin, Long Bai +2
Event detection is one of the fundamental tasks in information extraction and knowledge graph. However, a realistic event detection system often needs to deal with new event classe…
Selective Temporal Knowledge Graph Reasoning
Zhongni Hou, Xiaolong Jin, Zixuan Li +3
Temporal Knowledge Graph (TKG), which characterizes temporally evolving facts in the form of (subject, relation, object, timestamp), has attracted much attention recently. TKG reas…
KnowCoder: Coding Structured Knowledge into LLMs for Universal Information Extraction
Zixuan Li, Yutao Zeng, Yuxin Zuo +14
In this paper, we propose KnowCoder, a Large Language Model (LLM) to conduct Universal Information Extraction (UIE) via code generation. KnowCoder aims to develop a kind of unified…
Retrieval-Augmented Code Generation for Universal Information Extraction
Yucan Guo, Zixuan Li, Xiaolong Jin +8
Information Extraction (IE) aims to extract structural knowledge (e.g., entities, relations, events) from natural language texts, which brings challenges to existing methods due to…
An In-Context Schema Understanding Method for Knowledge Base Question Answering
Yantao Liu, Zixuan Li, Xiaolong Jin +5
The Knowledge Base Question Answering (KBQA) task aims to answer natural language questions based on a given knowledge base. Recently, Large Language Models (LLMs) have shown stron…
ProtoEM: A Prototype-Enhanced Matching Framework for Event Relation Extraction
Zhilei Hu, Zixuan Li, Daozhu Xu +5
Event Relation Extraction (ERE) aims to extract multiple kinds of relations among events in texts. However, existing methods singly categorize event relations as different classes,…
Nested Event Extraction upon Pivot Element Recogniton
Weicheng Ren, Zixuan Li, Xiaolong Jin +6
Nested Event Extraction (NEE) aims to extract complex event structures where an event contains other events as its arguments recursively. Nested events involve a kind of Pivot Elem…
Semantic Structure Enhanced Event Causality Identification
Zhilei Hu, Zixuan Li, Xiaolong Jin +4
Event Causality Identification (ECI) aims to identify causal relations between events in unstructured texts. This is a very challenging task, because causal relations are usually e…
Rich Event Modeling for Script Event Prediction
Long Bai, Saiping Guan, Zixuan Li +3
Script is a kind of structured knowledge extracted from texts, which contains a sequence of events. Based on such knowledge, script event prediction aims to predict the subsequent…
HiSMatch: Historical Structure Matching based Temporal Knowledge Graph Reasoning
Zixuan Li, Zhongni Hou, Saiping Guan +7
A Temporal Knowledge Graph (TKG) is a sequence of KGs with respective timestamps, which adopts quadruples in the form of (\emph{subject}, \emph{relation}, \emph{object}, \emph{time…