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Y. Lan

5 papers hereh-index 8198 citations17 works total

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

author position
  • middle author5

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.LG1
same name
  • Y. Lan — 24 papers, h 18
  • Y. Lan — 15 papers, h 22
  • Y. Lan — 8 papers, h 7
  • Y. Lan — 4 papers
  • Y. Lan — 4 papers, h 3
  • Y. Lan — 2 papers, h 19

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
20242026
collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2025

DEER: Disentangled Mixture of Experts with Instance-Adaptive Routing for Generalizable Machine-Generated Text Detection

Guoxin Ma, Xiaoming Liu, Hongyang Chen +6

Detecting machine-generated text has become a critical challenge amid the rapid advancement of LLMs, yet existing detectors degrade severely under domain shift. Through systematic…

cs.CL2025

Can Reasoning Path still be Effective as Input? Bridging Post-Reasoning to Chain-of-Thought Compression

Chengzhengxu Li, Xiaoming Liu, Zhaohan Zhang +5

Recent developments have enabled advanced reasoning in Large Language Models (LLMs) via long Chain-of-Thought (CoT), trading efficiency during inference for performance. Existing w…

cs.CL2025

MGT-Prism: Enhancing Domain Generalization for Machine-Generated Text Detection via Spectral Alignment

Shengchao Liu, Xiaoming Liu, Chengzhengxu Li +4

Large Language Models have shown growing ability to generate fluent and coherent texts that are highly similar to the writing style of humans. Current detectors for Machine-Generat…

cs.CL2024

Concentrate Attention: Towards Domain-Generalizable Prompt Optimization for Language Models

Chengzhengxu Li, Xiaoming Liu, Zhaohan Zhang +4

Recent advances in prompt optimization have notably enhanced the performance of pre-trained language models (PLMs) on downstream tasks. However, the potential of optimized prompts…

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