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Xiaosen Wang

School of Computer Science and Technology, Huazhong University of Science and Technology, China

15 papers hereh-index 111.6k citations22 works total

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

author position
  • first author7
  • middle author4
  • last author4

Across the 15 of 15 papers where every author was matched, so the position is known.

fields
  • cs.CV6
  • cs.LG4
  • cs.AI2
  • cs.CL2
  • cs.IR1
affiliations
  • School of Computer Science and Technology, Huazhong University of Science and Technology, China
Homepage
same name
  • Xiaosen Wang — 18 papers, h 12
  • Xiaosen Wang — 6 papers, h 4

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
20192026
most citedNatural Language Adversarial Defense through Synonym Encoding

33 citations · 101 across the 15 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2026

TMPO: Trajectory Matching Policy Optimization for Diverse and Efficient Diffusion Alignment

Jiaming Li, Chenyu Zhu, Nanxi Yi +9

Reinforcement learning (RL) has shown extraordinary potential in aligning diffusion models to downstream tasks, yet most of them still suffer from significant reward hacking, which…

cs.LG2025

Refining Adaptive Zeroth-Order Optimization at Ease

Yao Shu, Qixin Zhang, Kun He +1

Recently, zeroth-order (ZO) optimization plays an essential role in scenarios where gradient information is inaccessible or unaffordable, such as black-box systems and resource-con…

cs.LG2023★ 3 cited

Improving Adversarial Transferability with Scheduled Step Size and Dual Example

Zeliang Zhang, Peihan Liu, Xiaosen Wang +1

Deep neural networks are widely known to be vulnerable to adversarial examples, especially showing significantly poor performance on adversarial examples generated under the white-…

cs.LG2021★ 2 cited

Multi-stage Optimization based Adversarial Training

Xiaosen Wang, Chuanbiao Song, Liwei Wang +1

In the field of adversarial robustness, there is a common practice that adopts the single-step adversarial training for quickly developing adversarially robust models. However, the…

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