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researcher

Minji Tang

2 papers hereh-index 329 citations4 works total

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

author position
  • middle author1

Across the 1 of 2 papers where every author was matched, so the position is known.

fields
  • cs.CL1
  • cs.LG1

identity via Semantic Scholar / OpenAlex

most citedNoisywikiHow: A Benchmark for Learning with Real-world Noisy Labels in Natural Language Processing

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

collaborators

2 papers

cs.CL2023★ 1 cited

NoisywikiHow: A Benchmark for Learning with Real-world Noisy Labels in Natural Language Processing

Tingting Wu, Xiao Ding, Minji Tang +3

Large-scale datasets in the real world inevitably involve label noise. Deep models can gradually overfit noisy labels and thus degrade model generalization. To mitigate the effects…

cs.LG2022

DiscrimLoss: A Universal Loss for Hard Samples and Incorrect Samples Discrimination

Tingting Wu, Xiao Ding, Hao Zhang +4

Given data with label noise (i.e., incorrect data), deep neural networks would gradually memorize the label noise and impair model performance. To relieve this issue, curriculum le…

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