Pengyu Cheng | DeepAI

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239 publications
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Ricardo Henao
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Ruiyi Zhang
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∙ 09/06/2023

Everyone Deserves A Reward: Learning Customized Human Preferences

Reward models (RMs) are crucial in aligning large language models (LLMs)...

1 Pengyu Cheng, et al. ∙

∙ 08/25/2023

Chunk, Align, Select: A Simple Long-sequence Processing Method for Transformers

Although dominant in natural language processing, transformer-based mode...

0 Jiawen Xie, et al. ∙

∙ 11/14/2022

Replacing Language Model for Style Transfer

We introduce replacing language model (RLM), a sequence-to-sequence lang...

1 Pengyu Cheng, et al. ∙

∙ 03/11/2022

Semi-constraint Optimal Transport for Entity Alignment with Dangling Cases

Entity alignment (EA) merges knowledge graphs (KGs) by identifying the e...

6 Shengxuan Luo, et al. ∙

∙ 03/02/2022

Speaker Adaption with Intuitive Prosodic Features for Statistical Parametric Speech Synthesis

In this paper, we propose a method of speaker adaption with intuitive pr...

0 Pengyu Cheng, et al. ∙

∙ 03/17/2021

Improving Zero-shot Voice Style Transfer via Disentangled Representation Learning

Voice style transfer, also called voice conversion, seeks to modify one ...

0 Siyang Yuan, et al. ∙

∙ 03/11/2021

FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders

Pretrained text encoders, such as BERT, have been applied increasingly i...

17 Pengyu Cheng, et al. ∙

∙ 11/09/2020

Estimating Total Correlation with Mutual Information Bounds

Total correlation (TC) is a fundamental concept in information theory to...

0 Pengyu Cheng, et al. ∙

∙ 08/13/2020

WAFFLe: Weight Anonymized Factorization for Federated Learning

In domains where data are sensitive or private, there is great value in ...

16 Weituo Hao, et al. ∙

∙ 06/22/2020

CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information

Mutual information (MI) minimization has gained considerable interests i...

38 Pengyu Cheng, et al. ∙

∙ 06/01/2020

Improving Disentangled Text Representation Learning with Information-Theoretic Guidance

Learning disentangled representations of natural language is essential f...

5 Pengyu Cheng, et al. ∙

∙ 10/05/2019

Gaussian-Process-Based Dynamic Embedding for Textual Networks

Textual network embedding aims to learn low-dimensional representations ...

0 Pengyu Cheng, et al. ∙

∙ 10/05/2019

Straight-Through Estimator as Projected Wasserstein Gradient Flow

The Straight-Through (ST) estimator is a widely used technique for back-...

5 Pengyu Cheng, et al. ∙

∙ 06/19/2019

Learning Compressed Sentence Representations for On-Device Text Processing

Vector representations of sentences, trained on massive text corpora, ar...

0 Dinghan Shen, et al. ∙

∙ 06/05/2019

Improving Textual Network Embedding with Global Attention via Optimal Transport

Constituting highly informative network embeddings is an important tool ...

0 Liqun Chen, et al. ∙

∙ 07/04/2018

Accelerated First-order Methods on the Wasserstein Space for Bayesian Inference

We consider doing Bayesian inference by minimizing the KL divergence on ...

0 Chang Liu, et al. ∙

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