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Yicheng Wang

6 papers hereh-index 365.2k citations202 works total

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

author position
  • first author1
  • middle author5

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.CL3
  • cond-mat.supr-con1
  • cs.CV1
  • physics.ins-det1
same name
  • Yicheng Wang — 11 papers, h 4
  • Yicheng Wang — 6 papers, h 3
  • Yicheng Wang — 5 papers, h 9
  • Yicheng Wang — 5 papers, h 23
  • Yicheng Wang — 4 papers, h 2
  • Yicheng Wang — 4 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
20162019
most citedTuning phase transitions of FeSe thin flakes by field effect transistor with solid ion conductor as gate dielectric

101 citations · 147 across the 6 of their papers we have counts for

collaborators
Showing 2018Show all

4 papers · 1 filter

cs.CL2018★ 8 cited

Analyzing Compositionality-Sensitivity of NLI Models

Yixin Nie, Yicheng Wang, Mohit Bansal

Success in natural language inference (NLI) should require a model to understand both lexical and compositional semantics. However, through adversarial evaluation, we find that sev…

cs.CL2018★ 14 cited

Commonsense for Generative Multi-Hop Question Answering Tasks

Lisa Bauer, Yicheng Wang, Mohit Bansal

Reading comprehension QA tasks have seen a recent surge in popularity, yet most works have focused on fact-finding extractive QA. We instead focus on a more challenging multi-hop g…

cs.CV2018★ 2 cited

Qiniu Submission to ActivityNet Challenge 2018

Xiaoteng Zhang, Yixin Bao, Feiyun Zhang +7

In this paper, we introduce our submissions for the tasks of trimmed activity recognition (Kinetics) and trimmed event recognition (Moments in Time) for Activitynet Challenge 2018.…

cs.CL2018★ 20 cited

Robust Machine Comprehension Models via Adversarial Training

Yicheng Wang, Mohit Bansal

It is shown that many published models for the Stanford Question Answering Dataset (Rajpurkar et al., 2016) lack robustness, suffering an over 50% decrease in F1 score during adver…

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