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researcher

Xudong Zhu

Ohio State University

4 papers hereh-index 321 citations4 works total

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

author position
  • first author4

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

fields
  • cs.LG3
  • cs.CL1
affiliations
  • Ohio State University
HomepageORCID 0009-0000-3068-0754
same name
  • Xudong Zhu — 6 papers, h 11
  • Xudong Zhu — 6 papers, h 3
  • Xudong Zhu — 3 papers, h 7
  • Xudong Zhu — 1 paper, h 2
  • Xudong Zhu — 1 paper, h 2
  • Xudong Zhu — 1 paper, h 0

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
20242026
most citedFCDS: Fusing Constituency and Dependency Syntax into Document-Level Relation Extraction

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

collaborators

4 papers

cs.LG2026

One Token Can Be Enough: Bridging Prompting and Activation Steering with Prefix Steering

Xudong Zhu, Zhihui Zhu

Prompting guides language model behavior through the initial context, whereas activation steering often intervenes throughout generation. A natural question is whether steering can…

cs.LG2025

AbsTopK: Rethinking Sparse Autoencoders For Bidirectional Features

Xudong Zhu, Mohammad Mahdi Khalili, Zhihui Zhu

Sparse autoencoders (SAEs) have emerged as powerful techniques for interpretability of large language models (LLMs), aiming to decompose hidden states into meaningful semantic feat…

cs.LG2025★ 1 cited

From Emergence to Control: Probing and Modulating Self-Reflection in Language Models

Xudong Zhu, Jiachen Jiang, Mohammad Mahdi Khalili +1

Self-reflection -- the ability of a large language model (LLM) to revisit, evaluate, and revise its own reasoning -- has recently emerged as a powerful behavior enabled by reinforc…

cs.CL2024★ 1 cited

FCDS: Fusing Constituency and Dependency Syntax into Document-Level Relation Extraction

Xudong Zhu, Zhao Kang, Bei Hui

Document-level Relation Extraction (DocRE) aims to identify relation labels between entities within a single document. It requires handling several sentences and reasoning over the…

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