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researcher

Xinze Li

19 papers hereh-index 8190 citations26 works total

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

author position
  • first author4
  • middle author14

Across the 18 of 19 papers where every author was matched, so the position is known.

fields
  • cs.CL14
  • cs.IR2
  • cs.CE1
  • cs.CV1
  • cs.SE1
same name
  • Xinze Li — 10 papers, h 20
  • Xinze Li — 9 papers, h 6
  • Xinze Li — 4 papers, h 5
  • Xinze Li — 3 papers, h 6
  • Xinze Li — 3 papers, h 3
  • Xinze Li — 3 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
20232026
most citedConstructing Mechanical Design Agent Based on Large Language Models

2 citations · 5 across the 16 of their papers we have counts for

collaborators
Showing 2026 · cs.CLShow all

4 papers · 2 filters

cs.CL2026

MetaMem: Evolving Meta-Memory for Knowledge Utilization through Self-Reflective Symbolic Optimization

Haidong Xin, Xinze Li, Zhenghao Liu +6

Existing memory systems enable Large Language Models (LLMs) to support long-horizon human-LLM interactions by persisting historical interactions beyond limited context windows. How…

cs.CL2026

Long-Chain Reasoning Distillation via Adaptive Prefix Alignment

Zhenghao Liu, Zhuoyang Wu, Xinze Li +6

Large Language Models (LLMs) have demonstrated remarkable reasoning capabilities, particularly in solving complex mathematical problems. Recent studies show that distilling long re…

cs.CL2026

Finding What Matters: Anchoring Context Knowledge with Evolving Indices for Iterative Retrieval

Mingyan Wu, Zhenghao Liu, Xinze Li +7

Retrieval-Augmented Generation (RAG) has become a dominant paradigm for mitigating hallucinations in Large Language Models (LLMs) by incorporating external knowledge. However, exis…

cs.CL2026

SEEK: Steering LLM Reasoning for RAG via Internal Reasoning Sketches

Xinze Li, Yuqing Lan, Zhenghao Liu +7

Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by incorporating external knowledge into the generation process. Benefiting from the reasoning capabiliti…

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