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researcher

Zihan Wang

4 papers here

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

author position
  • first author1
  • middle author2
  • last author1

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

fields
  • cs.LG3
  • cs.CL1
ORCID 0000-0003-1056-6326
same name
  • Zihan Wang — 23 papers, h 12
  • Zihan Wang — 20 papers, h 10
  • Zihan Wang — 16 papers, h 11
  • Zihan Wang — 12 papers, h 8
  • Zihan Wang — 11 papers, h 5
  • Zihan Wang — 9 papers, 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

activity
20212023
most citedM^4I: Multi-modal Models Membership Inference

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

collaborators

4 papers

cs.LG2023★ 1 cited

Implicit bias of SGD in L2​-regularized linear DNNs: One-way jumps from high to low rank

Zihan Wang, Arthur Jacot

The L2​-regularized loss of Deep Linear Networks (DLNs) with more than one hidden layers has multiple local minima, corresponding to matrices with different ranks. In tasks suc…

cs.LG2022★ 3 cited

M^4I: Multi-modal Models Membership Inference

Pingyi Hu, Zihan Wang, Ruoxi Sun +2

With the development of machine learning techniques, the attention of research has been moved from single-modal learning to multi-modal learning, as real-world data exist in the fo…

cs.LG2022

Rethinking the Setting of Semi-supervised Learning on Graphs

Ziang Li, Ming Ding, Weikai Li +4

We argue that the present setting of semisupervised learning on graphs may result in unfair comparisons, due to its potential risk of over-tuning hyper-parameters for models. In th…

cs.CL2021

Dual Slot Selector via Local Reliability Verification for Dialogue State Tracking

Jinyu Guo, Kai Shuang, Jijie Li +1

The goal of dialogue state tracking (DST) is to predict the current dialogue state given all previous dialogue contexts. Existing approaches generally predict the dialogue state at…

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