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Zhengyan Zhang

4 papers hereh-index 4496 citations10 works total

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

author position
  • middle author2

Across the 2 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL4
same name
  • Zhengyan Zhang — 24 papers, h 21
  • Zhengyan Zhang — 4 papers, h 9
  • Zhengyan Zhang — 2 papers
  • Zhengyan Zhang — 2 papers, h 0
  • Zhengyan 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

most citedNative Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention

4 citations · 4 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CL2026

Gender Bias in MT for a Genderless Language: New Benchmarks for Basque

Amaia Murillo, Olatz-Perez-de-Viñaspre, Naiara Perez

Large language models (LLMs) and machine translation (MT) systems are increasingly used in our daily lives, but their outputs can reproduce gender bias present in the training data…

cs.CL2026

mHC: Manifold-Constrained Hyper-Connections

Zhenda Xie, Yixuan Wei, Huanqi Cao +17

Recently, studies exemplified by Hyper-Connections (HC) have extended the ubiquitous residual connection paradigm established over the past decade by expanding the residual stream…

cs.CL2025

Jailbreak Distillation: Renewable Safety Benchmarking

Jingyu Zhang, Ahmed Elgohary, Xiawei Wang +5

Large language models (LLMs) are rapidly deployed in critical applications, raising urgent needs for robust safety benchmarking. We propose Jailbreak Distillation (JBDistill), a no…

cs.CL2025★ 4 cited

Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention

Jingyang Yuan, Huazuo Gao, Damai Dai +12

Long-context modeling is crucial for next-generation language models, yet the high computational cost of standard attention mechanisms poses significant computational challenges. S…

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