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Zhiwei Liu

41 papers hereh-index 171.2k citations52 works total

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

author position
  • first author4
  • middle author36

Across the 40 of 41 papers where every author was matched, so the position is known.

fields
  • cs.CL13
  • cs.AI12
  • cs.SE5
  • cs.LG4
  • cs.SD3
  • cs.IR2
same name
  • Zhiwei Liu — 30 papers, h 22
  • Zhiwei Liu — 25 papers, h 9
  • Zhiwei Liu — 24 papers, h 15
  • Zhiwei Liu — 8 papers, h 5
  • Zhiwei Liu — 6 papers, h 8
  • Zhiwei Liu — 2 papers, h 2

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 citedCodeFuse-13B: A Pretrained Multi-lingual Code Large Language Model

18 citations · 75 across the 40 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2026

Critical-State RL: Diagnosing Trainable States for Multi-Turn Tool Use

Zixiang Chen, Wenting Zhao, Zhepeng Cen +9

Multi-turn tool-use failures can hinge on a single model call, yet reward variation alone does not reveal which call would benefit from training. When rewards depend on later inter…

cs.LG2025

GeoGNN: Quantifying and Mitigating Semantic Drift in Text-Attributed Graphs

Liangwei Yang, Jing Ma, Jianguo Zhang +11

Graph neural networks (GNNs) on text--attributed graphs (TAGs) typically encode node texts using pretrained language models (PLMs) and propagate these embeddings through linear nei…

cs.LG2025

Test-Time Adaptation for LLM Agents via Environment Interaction

Arthur Chen, Zuxin Liu, Jianguo Zhang +6

Large language model (LLM)-based agents struggle to generalize to novel and complex environments, such as unseen websites or new sets of functions, due to a fundamental mismatch be…

cs.LG2025

xRouter: Training Cost-Aware LLMs Orchestration System via Reinforcement Learning

Cheng Qian, Zuxin Liu, Shirley Kokane +10

Modern LLM deployments confront a widening cost-performance spectrum: premium models deliver strong reasoning but are expensive, while lightweight models are economical yet brittle…

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