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Jiayu Liu

8 papers hereh-index 439 citations11 works total

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

author position
  • first author2
  • middle author6

Across the 8 of 8 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.AI2
  • cs.CV1
  • cs.LG1
same name
  • Jiayu Liu — 16 papers, h 3
  • Jiayu Liu — 10 papers, h 6
  • Jiayu Liu — 6 papers, h 3
  • Jiayu Liu — 5 papers, h 3
  • Jiayu Liu — 4 papers, h 2
  • Jiayu Liu — 3 papers, h 3

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

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2026

Co-Evolution in Agentic Systems: Toward Self-Directed Evolution Beyond Human Design

Qing Zong, Jiayu Liu, Junhao Shen +9

Agentic systems are increasingly expected to improve after deployment, yet single-entity self-evolution is often bounded by a static learning context, such as fixed tasks and feedb…

cs.CL2026

NOVA: NOise-aware Verbal Confidence CAlibration for Robust Large Language Models in RAG Systems

Jiayu Liu, Rui Wang, Qing Zong +9

Accurately assessing model confidence is essential for deploying large language models (LLMs) in mission-critical factual domains. While retrieval-augmented generation (RAG) is wid…

cs.CL2025

CritiCal: Can Critique Help LLM Uncertainty or Confidence Calibration?

Qing Zong, Jiayu Liu, Tianshi Zheng +7

Accurate confidence calibration in Large Language Models (LLMs) is critical for safe use in high-stakes domains, where clear verbalized confidence enhances user trust. Traditional…

cs.CL2025

Revisiting Epistemic Markers in Confidence Estimation: Can Markers Accurately Reflect Large Language Models' Uncertainty?

Jiayu Liu, Qing Zong, Weiqi Wang +1

As large language models (LLMs) are increasingly used in high-stakes domains, accurately assessing their confidence is crucial. Humans typically express confidence through epistemi…

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