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Divergence Frontiers for Generative Models: Sample Complexity,
  Quantization Effects, and Frontier Integrals

Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals

15 June 2021
Lang Liu
Krishna Pillutla
Sean Welleck
Sewoong Oh
Yejin Choi
Zaïd Harchaoui
    MQ
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Papers citing "Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals"

14 / 14 papers shown
Title
Remasking Discrete Diffusion Models with Inference-Time Scaling
Guanghan Wang
Yair Schiff
S. Sahoo
Volodymyr Kuleshov
DiffM
43
2
0
01 Mar 2025
CorrSynth -- A Correlated Sampling Method for Diverse Dataset Generation from LLMs
CorrSynth -- A Correlated Sampling Method for Diverse Dataset Generation from LLMs
Suhas S Kowshik
Abhishek Divekar
Vijit Malik
SyDa
37
0
0
13 Nov 2024
KnowledgeSG: Privacy-Preserving Synthetic Text Generation with Knowledge
  Distillation from Server
KnowledgeSG: Privacy-Preserving Synthetic Text Generation with Knowledge Distillation from Server
Wenhao Wang
Xiaoyu Liang
Rui Ye
Jingyi Chai
Siheng Chen
Yanfeng Wang
SyDa
21
3
0
08 Oct 2024
SynthesizRR: Generating Diverse Datasets with Retrieval Augmentation
SynthesizRR: Generating Diverse Datasets with Retrieval Augmentation
Abhishek Divekar
Greg Durrett
26
5
0
16 May 2024
DistiLLM: Towards Streamlined Distillation for Large Language Models
DistiLLM: Towards Streamlined Distillation for Large Language Models
Jongwoo Ko
Sungnyun Kim
Tianyi Chen
SeYoung Yun
61
25
0
06 Feb 2024
Style-News: Incorporating Stylized News Generation and Adversarial
  Verification for Neural Fake News Detection
Style-News: Incorporating Stylized News Generation and Adversarial Verification for Neural Fake News Detection
Wei-Yao Wang
Yu-Chieh Chang
Wenjie Peng
10
0
0
27 Jan 2024
Does Writing with Language Models Reduce Content Diversity?
Does Writing with Language Models Reduce Content Diversity?
Vishakh Padmakumar
He He
20
79
0
11 Sep 2023
MAUVE Scores for Generative Models: Theory and Practice
MAUVE Scores for Generative Models: Theory and Practice
Krishna Pillutla
Lang Liu
John Thickstun
Sean Welleck
Swabha Swayamdipta
Rowan Zellers
Sewoong Oh
Yejin Choi
Zaïd Harchaoui
EGVM
23
21
0
30 Dec 2022
RenyiCL: Contrastive Representation Learning with Skew Renyi Divergence
RenyiCL: Contrastive Representation Learning with Skew Renyi Divergence
Kyungmin Lee
Jinwoo Shin
SSL
DRL
22
10
0
12 Aug 2022
On the Usefulness of Embeddings, Clusters and Strings for Text Generator
  Evaluation
On the Usefulness of Embeddings, Clusters and Strings for Text Generator Evaluation
Tiago Pimentel
Clara Meister
Ryan Cotterell
35
7
0
31 May 2022
MAUVE: Measuring the Gap Between Neural Text and Human Text using
  Divergence Frontiers
MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers
Krishna Pillutla
Swabha Swayamdipta
Rowan Zellers
John Thickstun
Sean Welleck
Yejin Choi
Zaïd Harchaoui
26
340
0
02 Feb 2021
On the Theoretical Equivalence of Several Trade-Off Curves Assessing
  Statistical Proximity
On the Theoretical Equivalence of Several Trade-Off Curves Assessing Statistical Proximity
Rodrigue Siry
Ryan Webster
Loïc Simon
Julien Rabin
8
4
0
21 Jun 2020
A Style-Based Generator Architecture for Generative Adversarial Networks
A Style-Based Generator Architecture for Generative Adversarial Networks
Tero Karras
S. Laine
Timo Aila
262
10,320
0
12 Dec 2018
Revisiting Classifier Two-Sample Tests
Revisiting Classifier Two-Sample Tests
David Lopez-Paz
Maxime Oquab
65
389
0
20 Oct 2016
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