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A Simple Contrastive Learning Objective for Alleviating Neural Text
  Degeneration

A Simple Contrastive Learning Objective for Alleviating Neural Text Degeneration

5 May 2022
Shaojie Jiang
Ruqing Zhang
Svitlana Vakulenko
Maarten de Rijke
ArXivPDFHTML

Papers citing "A Simple Contrastive Learning Objective for Alleviating Neural Text Degeneration"

12 / 12 papers shown
Title
Teaching Models to Understand (but not Generate) High-risk Data
Teaching Models to Understand (but not Generate) High-risk Data
Ryan Yixiang Wang
Matthew Finlayson
Luca Soldaini
Swabha Swayamdipta
Robin Jia
139
0
0
05 May 2025
Some things are more CRINGE than others: Iterative Preference
  Optimization with the Pairwise Cringe Loss
Some things are more CRINGE than others: Iterative Preference Optimization with the Pairwise Cringe Loss
Jing Xu
Andrew Lee
Sainbayar Sukhbaatar
Jason Weston
20
86
0
27 Dec 2023
Improving Summarization with Human Edits
Improving Summarization with Human Edits
Zonghai Yao
Benjamin J Schloss
Sai P. Selvaraj
29
3
0
09 Oct 2023
SequenceMatch: Imitation Learning for Autoregressive Sequence Modelling
  with Backtracking
SequenceMatch: Imitation Learning for Autoregressive Sequence Modelling with Backtracking
Chris Cundy
Stefano Ermon
16
10
0
08 Jun 2023
Look-back Decoding for Open-Ended Text Generation
Look-back Decoding for Open-Ended Text Generation
Nan Xu
Chunting Zhou
Asli Celikyilmaz
Xuezhe Ma
31
9
0
22 May 2023
Revisiting the Architectures like Pointer Networks to Efficiently
  Improve the Next Word Distribution, Summarization Factuality, and Beyond
Revisiting the Architectures like Pointer Networks to Efficiently Improve the Next Word Distribution, Summarization Factuality, and Beyond
Haw-Shiuan Chang
Zonghai Yao
Alolika Gon
Hong-ye Yu
Andrew McCallum
43
10
0
20 May 2023
Contrastive Learning Reduces Hallucination in Conversations
Contrastive Learning Reduces Hallucination in Conversations
Weiwei Sun
Zhengliang Shi
Shen Gao
Pengjie Ren
Maarten de Rijke
Z. Ren
42
62
0
20 Dec 2022
The CRINGE Loss: Learning what language not to model
The CRINGE Loss: Learning what language not to model
Leonard Adolphs
Tianyu Gao
Jing Xu
Kurt Shuster
Sainbayar Sukhbaatar
Jason Weston
MU
23
35
0
10 Nov 2022
DIRECTOR: Generator-Classifiers For Supervised Language Modeling
DIRECTOR: Generator-Classifiers For Supervised Language Modeling
Kushal Arora
Kurt Shuster
Sainbayar Sukhbaatar
Jason Weston
VLM
30
40
0
15 Jun 2022
Training language models to follow instructions with human feedback
Training language models to follow instructions with human feedback
Long Ouyang
Jeff Wu
Xu Jiang
Diogo Almeida
Carroll L. Wainwright
...
Amanda Askell
Peter Welinder
Paul Christiano
Jan Leike
Ryan J. Lowe
OSLM
ALM
339
12,003
0
04 Mar 2022
COCO-LM: Correcting and Contrasting Text Sequences for Language Model
  Pretraining
COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining
Yu Meng
Chenyan Xiong
Payal Bajaj
Saurabh Tiwary
Paul N. Bennett
Jiawei Han
Xia Song
125
203
0
16 Feb 2021
Efficient Estimation of Word Representations in Vector Space
Efficient Estimation of Word Representations in Vector Space
Tomáš Mikolov
Kai Chen
G. Corrado
J. Dean
3DV
281
31,267
0
16 Jan 2013
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