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researcher

Yefeng Zheng

38 papers hereh-index 221.9k citations77 works total

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

author position
  • middle author24
  • last author11

Across the 35 of 38 papers where every author was matched, so the position is known.

fields
  • cs.CL20
  • cs.CV6
  • cs.AI4
  • cs.IR3
  • cs.LG2
  • q-bio.QM2
same name
  • Yefeng Zheng — 33 papers, h 28
  • Yefeng Zheng — 28 papers, h 19
  • Yefeng Zheng — 23 papers, h 15
  • Yefeng Zheng — 23 papers, h 23
  • Yefeng Zheng — 12 papers, h 7
  • Yefeng Zheng — 11 papers, h 17

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
20222026
most citedMulti-modal Contrastive Representation Learning for Entity Alignment

26 citations · 132 across the 36 of their papers we have counts for

collaborators
Showing cs.AIShow all

4 papers · 1 filter

cs.AI2026

Bridging Auxiliary Constraints to Resolve Instruction Following in Large Reasoning Models

Zhengyi Zhao, Shubo Zhang, Huimin Wang +7

Large Reasoning Models (LRMs) have demonstrated impressive capabilities in many tasks, yet they struggle with reliably following multiple instructions, either by failing to satisfy…

cs.AI2026

Tandem: Riding Together with Large and Small Language Models for Efficient Reasoning

Zichuan Fu, Xian Wu, Guojing Li +7

Recent advancements in large language models (LLMs) have catalyzed the rise of reasoning-intensive inference paradigms, where models perform explicit step-by-step reasoning before…

cs.AI2025

Model Merging for Knowledge Editing

Zichuan Fu, Xian Wu, Guojing Li +6

Large Language Models (LLMs) require continuous updates to maintain accurate and current knowledge as the world evolves. While existing knowledge editing approaches offer various s…

cs.AI2025

MemeReaCon: Probing Contextual Meme Understanding in Large Vision-Language Models

Zhengyi Zhao, Shubo Zhang, Yuxi Zhang +10

Memes have emerged as a popular form of multimodal online communication, where their interpretation heavily depends on the specific context in which they appear. Current approaches…

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