14 citations · 46 across the 27 of their papers we have counts for
30 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…
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…
Code-on-Graph: Iterative Programmatic Reasoning via Large Language Models on Knowledge Graphs
Weiwei Ding, Zixuan Li, Long Bai +7
Knowledge Graphs (KGs) are widely used to mitigate the limitations of Large Language Models (LLMs), such as outdated knowledge and hallucinations. Existing LLM-KG integration frame…
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…
KnowCoder-A1: Incentivizing Agentic Reasoning Capability with Outcome Supervision for KBQA
Zhuo Chen, Fei Wang, Zixuan Li +6
Knowledge Base Question Answering (KBQA) aims to answer natural-language questions over a structured Knowledge Base (KB). Recent work improves KBQA by adopting an agentic reasoning…
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…
Self-Improvement Programming for Temporal Knowledge Graph Question Answering
Zhuo Chen, Zhao Zhang, Zixuan Li +4
Temporal Knowledge Graph Question Answering (TKGQA) aims to answer questions with temporal intent over Temporal Knowledge Graphs (TKGs). The core challenge of this task lies in und…
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…
Unlocking the Power of Large Language Models for Entity Alignment
Xuhui Jiang, Yinghan Shen, Zhichao Shi +6
Entity Alignment (EA) is vital for integrating diverse knowledge graph (KG) data, playing a crucial role in data-driven AI applications. Traditional EA methods primarily rely on co…
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…
Surfer: Progressive Reasoning with World Models for Robotic Manipulation
Pengzhen Ren, Kaidong Zhang, Hetao Zheng +5
Considering how to make the model accurately understand and follow natural language instructions and perform actions consistent with world knowledge is a key challenge in robot man…
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…
Toward Practical Entity Alignment Method Design: Insights from New Highly Heterogeneous Knowledge Graph Datasets
Xuhui Jiang, Chengjin Xu, Yinghan Shen +7
The flourishing of knowledge graph applications has driven the need for entity alignment (EA) across KGs. However, the heterogeneity of practical KGs, characterized by differing sc…
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…