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researcher

Wei Cheng

39 papers hereh-index 13601 citations51 works total

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

author position
  • middle author34
  • last author4

Across the 38 of 39 papers where every author was matched, so the position is known.

fields
  • cs.CL15
  • cs.LG15
  • cs.AI6
  • cs.CV2
  • cs.DC1
same name
  • Wei Cheng — 51 papers, h 80
  • Wei Cheng — 26 papers, h 10
  • Wei Cheng — 22 papers, h 4
  • Wei Cheng — 11 papers, h 4
  • Wei Cheng — 9 papers, h 27
  • Wei Cheng — 9 papers, h 4

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 citedA Survey on Detection of LLMs-Generated Content

7 citations · 39 across the 33 of their papers we have counts for

collaborators
Showing 2025 · cs.CLShow all

4 papers · 2 filters

cs.CL2025

Human Texts Are Outliers: Detecting LLM-generated Texts via Out-of-distribution Detection

Cong Zeng, Shengkun Tang, Yuanzhou Chen +6

The rapid advancement of large language models (LLMs) such as ChatGPT, DeepSeek, and Claude has significantly increased the presence of AI-generated text in digital communication.…

cs.CL2025★ 1 cited

Learning to Route: A Rule-Driven Agent Framework for Hybrid-Source Retrieval-Augmented Generation

Haoyue Bai, Haoyu Wang, Shengyu Chen +5

Large Language Models (LLMs) have shown remarkable performance on general Question Answering (QA), yet they often struggle in domain-specific scenarios where accurate and up-to-dat…

cs.CL2025

DeepSieve: Information Sieving via LLM-as-a-Knowledge-Router

Minghao Guo, Qingcheng Zeng, Xujiang Zhao +5

Large Language Models (LLMs) excel at many reasoning tasks but struggle with knowledge-intensive queries due to their inability to dynamically access up-to-date or domain-specific…

cs.CL2025

MixLLM: Dynamic Routing in Mixed Large Language Models

Xinyuan Wang, Yanchi Liu, Wei Cheng +5

Large Language Models (LLMs) exhibit potential artificial generic intelligence recently, however, their usage is costly with high response latency. Given mixed LLMs with their own…

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