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researcher

Chenyu Wang

32 papers hereh-index 10749 citations36 works total

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

author position
  • first author11
  • middle author19
  • last author1

Across the 31 of 32 papers where every author was matched, so the position is known.

fields
  • cs.LG12
  • cs.CL7
  • cs.AI6
  • cs.AR3
  • cs.CV1
  • cs.RO1
same name
  • Chenyu Wang — 13 papers, h 21
  • Chenyu Wang — 7 papers, h 6
  • Chenyu Wang — 7 papers, h 3
  • Chenyu Wang — 5 papers, h 4
  • Chenyu Wang — 3 papers, h 3
  • Chenyu Wang — 3 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 citedDirichlet Flow Matching with Applications to DNA Sequence Design

10 citations · 28 across the 30 of their papers we have counts for

collaborators
Showing 2026 · cs.CLShow all

4 papers · 2 filters

cs.CL2026

Guideline-as-Oracle: Zero-Annotation Training of an Ophthalmic Telephone Triage Agent

Chenyu Wang, Yi Liu, Baoqing Li +2

Scaling supervision for multi-turn medical agents is difficult because expert dialogue annotation is costly and clinical conversations are privacy-restricted. We introduce Guidelin…

cs.CL2026

ConflictRAG: Detecting and Resolving Knowledge Conflicts in Retrieval Augmented Generation

Chenyu Wang, Yueyuan Li, Yingmin Liu +1

Retrieval-Augmented Generation (RAG) systems implicitly assume mutual consistency among retrieved documents -- an assumption that frequently fails in practice. We present ConflictR…

cs.CL2026

Economy of Minds: Emerging Multi-Agent Intelligence with Economic Interactions

Zhenting Qi, Huangyuan Su, Ao Qu +13

How can a population of agents self-orchestrate and self-adapt into stronger collective intelligence without centralized control? Inspired by Friedrich Hayek's economic theory of d…

cs.CL2026

HRM-Text: Efficient Pretraining Beyond Scaling

Guan Wang, Changling Liu, Chenyu Wang +6

The current pretraining paradigm for large language models relies on massive compute and internet-scale raw text, creating a significant barrier to foundational research. In contra…

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