Scholar

Yu Zhang

Google Scholar ID: y3JK-1oAAAAJ

Soochow University

Sequence ModelingNatural Language Processing

Citations & Impact

All-time

Citations

670

H-index

i10-index

Publications

Co-authors

list available

Contact

Publications

13 items

Browse publications on Google Scholar (top-right) ↗

Resume (English only)

Academic Achievements

Publications:
- Kimi Linear: An Expressive, Efficient Attention Architecture (Preprint)
- Gated Slot Attention for Efficient Linear-Time Sequence Modeling (NeurIPS 2024)
- Parallelizing Linear Transformers with the Delta Rule over Sequence Length (NeurIPS 2024)
- Scalable MatMul-free Language Modeling (Preprint)
- Non-autoregressive Text Editing with Copy-aware Latent Alignments (EMNLP 2023)
- Semantic Role Labeling as Dependency Parsing: Exploring Latent Tree Structures Inside Arguments (COLING 2022)
- Fast and Accurate End-to-End Span-based Semantic Role Labeling as Word-based Graph Parsing (COLING 2022, Best Paper Award)
- Fast and Accurate Neural CRF Constituency Parsing (IJCAI 2020)
- Efficient Second-Order TreeCRF for Neural Dependency Parsing (ACL 2020)
- Is POS Tagging Necessary or Even Helpful for Neural Dependency Parsing? (NLPCC 2020, Best Paper Award)
- HLT@SUDA at SemEval-2019 Task 1: UCCA Graph Parsing as Constituent Tree Parsing (SemEval 2019)

Research Experience

Education

Background

Currently a third-year PhD student at Soochow University, focusing on developing efficient text generation models and hardware-efficient linear-time sequence modeling methods. Early research focused on structured prediction tasks, specifically dependency parsing and constituency parsing.

Miscellany

Projects:
- FLA: A Triton-Based Library for Hardware-Efficient Implementations of Linear Attention Mechanism
- SuPar: State-of-the-art syntactic/semantic parsers

Co-authors

1 total