Product
Help
Pricing
About
Jobs
Log in
Get started
Author
Add to collection
Zewen Liu
Observed name:
Liu, Zewen
Institutions:
Emory University,
Qilu Institute of Technology
Observed institutions:
Emory University,
Qilu Institute of Technology
OpenAlex ID:
A5137559621
Harness Updating Is Not Harness Benefit: Disentangling Evolution Capabilities in Self-Evolving LLM Agents
2026
·
Minhua Lin
, Juncheng Wu
, et al.
·
Conference on Empirical Methods in Natural Language Processing (EMNLP)
·
49
PDF
Adaptive Auto-Harness: Sustained Self-Improvement for Agentic System Deployment on Open-Ended Task Streams
2026
·
Liu, Zewen
, Shi, Zhan
, et al.
·
arXiv (Cornell University)
·
34
PDF
Evo-Harness: Context-to-Harness Skill Compilation for Self-Evolving Agents
2026
·
Tianxin Wei
, Zhan Shi
, et al.
·
Conference on Empirical Methods in Natural Language Processing (EMNLP)
·
26
PDF
Contagion Networks: Evaluator Preference Propagation in Multi-Agent LLM Systems
2026
·
Liu, Zewen
·
arXiv (Cornell University)
·
5
PDF
Memory Contagion: Cross-Temporal Propagation of Evaluator Bias via Agent Memory
2026
·
Liu, Zewen
·
arXiv (Cornell University)
·
2
PDF
BOUNDARY_SYNC: Measuring Communication-Induced Representational Coupling in Multi-Agent LLM Systems
2026
·
Liu, Zewen
·
arXiv (Cornell University)
·
1
PDF
Calibrating the Evaluator: Does Probability Calibration Mitigate Preference Coupling in LLM Agent Feedback Loops?
2026
·
Liu, Zewen
·
arXiv (Cornell University)
·
1
PDF
The Hidden Cost of Resampling: How Imbalance Correction Degrades Probability Calibration in Tree Ensembles
2026
·
Liu, Zewen
·
arXiv (Cornell University)
·
1
PDF
EPC: A Standardized Protocol for Measuring Evaluator Preference Dynamics in LLM Agent Systems
2026
·
Liu, Zewen
·
arXiv (Cornell University)
PDF
The Contagion Tensor: A Framework for Measuring Output-Distribution Coupling in Multi-Agent LLM Systems -- and Auditing the Claims It Enables
2026
·
Liu, Zewen
·
arXiv (Cornell University)
PDF
Show more works
View as search
Works count:
10
Citation count:
119
H-index:
4
I10-index:
3
Year
Topic
Type