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Zixuan Li

30 papers hereh-index 151.3k citations48 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author6
  • middle author23

Across the 29 of 30 papers where every author was matched, so the position is known.

fields
  • cs.CL14
  • cs.AI11
  • cs.LG4
  • cs.RO1
same name
  • Zixuan Li — 9 papers, h 4
  • Zixuan Li — 8 papers, h 3
  • Zixuan Li — 6 papers, h 3
  • Zixuan Li — 6 papers, h 3
  • Zixuan Li — 4 papers, h 5
  • Zixuan Li — 4 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20212026
most citedTemporal Knowledge Graph Reasoning Based on Evolutional Representation Learning

14 citations · 46 across the 27 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.AI2026

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…

cs.CL2026

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…

cs.AI2026

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Knowledge Graphs (KGs) are widely used to mitigate the limitations of Large Language Models (LLMs), such as outdated knowledge and hallucinations.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…

cs.AI2026

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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.