◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Richard Yuanzhe Pang

New York University

27 papers hereh-index 205.3k citations31 works total

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

author position
  • sole author1
  • first author8
  • middle author17

Across the 26 of 27 papers where every author was matched, so the position is known.

fields
  • cs.CL23
  • cs.LG3
  • cs.AI1
affiliations
  • New York University
Homepage

identity via Semantic Scholar / OpenAlex

activity
20182026
most citedIntermediate-Task Transfer Learning with Pretrained Models for Natural Language Understanding: When and Why Does It Work?

53 citations · 208 across the 25 of their papers we have counts for

collaborators
Showing 2020 · cs.CLShow all

3 papers · 2 filters

cs.CL2020★ 5 cited

Text Generation by Learning from Demonstrations

Richard Yuanzhe Pang, He He

Current approaches to text generation largely rely on autoregressive models and maximum likelihood estimation. This paradigm leads to (i) diverse but low-quality samples due to mis…

cs.CL2020★ 8 cited

ENGINE: Energy-Based Inference Networks for Non-Autoregressive Machine Translation

Lifu Tu, Richard Yuanzhe Pang, Sam Wiseman +1

We propose to train a non-autoregressive machine translation model to minimize the energy defined by a pretrained autoregressive model. In particular, we view our non-autoregressiv…

cs.CL2020★ 53 cited

Intermediate-Task Transfer Learning with Pretrained Models for Natural Language Understanding: When and Why Does It Work?

Yada Pruksachatkun, Jason Phang, Haokun Liu +6

While pretrained models such as BERT have shown large gains across natural language understanding tasks, their performance can be improved by further training the model on a data-r…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.