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Yuyu Zhang

11 papers hereh-index 4106 citations13 works total

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

author position
  • middle author10

Across the 10 of 11 papers where every author was matched, so the position is known.

fields
  • cs.AI4
  • cs.CL4
  • cs.IR2
  • cs.SE1
same name
  • Yuyu Zhang — 14 papers, h 18
  • Yuyu Zhang — 1 paper, h 2
  • Yuyu Zhang — 1 paper, h 2
  • Yuyu Zhang — 1 paper, h 2
  • Yuyu Zhang — 1 paper, 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
20232026
most citedGPT-Fathom: Benchmarking Large Language Models to Decipher the Evolutionary Path towards GPT-4 and Beyond

2 citations · 3 across the 11 of their papers we have counts for

collaborators
Showing cs.AIShow all

4 papers · 1 filter

cs.AI2026

Function-Aware Fill-in-the-Middle as Mid-Training for Coding Agent Foundation Models

Yubo Wang, Jiarong Liang, Yuxuan Zhang +5

Coding agents must integrate external tool returns into ongoing reasoning - a capability that standard left-to-right pretraining on code exposes only in its forward direction. We o…

cs.AI2026

Dr-DCI: Scaling Direct Corpus Interaction via Dynamic Workspace Expansion

Yi Lu, Zhuofeng Li, Ping Nie +7

Agentic search over large corpora relies on retriever-mediated interfaces (e.g., BM25 or ColBERT) for scalable candidate discovery. While effective at ranking relevant documents, t…

cs.AI2026

Reasoning for Mobile User Experience with Multimodal LLMs: Task, Benchmark, and Approach

Ruichao Mao, Zhou Fang, Teng Guo +9

User experience (UX) centered on usability, perceived consistency, and functional clarity is fundamental to real-world user interfaces (UI). The application of multimodal large lan…

cs.AI2026

RewardHarness: Self-Evolving Agentic Post-Training

Yuxuan Zhang, Penghui Du, Bo Li +11

Aligning generative models with human preferences remains a central challenge. While RLHF is widely adopted, it relies on large-scale preference data. This limitation is particular…

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