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Raphael Tang

Microsoft

19 papers hereh-index 203k citations46 works total

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

author position
  • first author11
  • middle author7

Across the 18 of 19 papers where every author was matched, so the position is known.

fields
  • cs.CL14
  • cs.CV2
  • cs.CY1
  • cs.IR1
  • cs.LG1
affiliations
  • Microsoft
  • University College London
  • University of Waterloo
  • Comcast
Homepage
same name
  • Raphael Tang — 5 papers, h 4
  • Raphael Tang — 2 papers
  • Raphael Tang — 1 paper

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
20172025
most citedDistilling Task-Specific Knowledge from BERT into Simple Neural Networks

335 citations · 506 across the 13 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CL2019★ 34 cited

What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning

Jaejun Lee, Raphael Tang, Jimmy Lin

Pretrained transformer-based language models have achieved state of the art across countless tasks in natural language processing. These models are highly expressive, comprising at…

cs.CL2019★ 4 cited

Explicit Pairwise Word Interaction Modeling Improves Pretrained Transformers for English Semantic Similarity Tasks

Yinan Zhang, Raphael Tang, Jimmy Lin

In English semantic similarity tasks, classic word embedding-based approaches explicitly model pairwise "interactions" between the word representations of a sentence pair. Transfor…

cs.CL2019

DocBERT: BERT for Document Classification

Ashutosh Adhikari, Achyudh Ram, Raphael Tang +1

We present, to our knowledge, the first application of BERT to document classification. A few characteristics of the task might lead one to think that BERT is not the most appropri…

cs.CL2019★ 335 cited

Distilling Task-Specific Knowledge from BERT into Simple Neural Networks

Raphael Tang, Yao Lu, Linqing Liu +3

In the natural language processing literature, neural networks are becoming increasingly deeper and complex. The recent poster child of this trend is the deep language representati…

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