Liqun Chen

Affiliations:
  • Duke University, Durham, NC, USA (PhD 2021)


According to our database1, Liqun Chen authored at least 36 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Text Feature Adversarial Learning for Text Generation With Knowledge Transfer From GPT2.
IEEE Trans. Neural Networks Learn. Syst., May, 2024

2023
Understanding and Constructing Latent Modality Structures in Multi-Modal Representation Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Why do We Need Large Batchsizes in Contrastive Learning? A Gradient-Bias Perspective.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Vision-Language Pre-Training with Triple Contrastive Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Multi-modal Alignment using Representation Codebook.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Learning deep models via optimal transport distance.
PhD thesis, 2021

Simpler, Faster, Stronger: Breaking The log-K Curse On Contrastive Learners With FlatNCE.
CoRR, 2021

SpanPredict: Extraction of Predictive Document Spans with Neural Attention.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Contextualized Perturbation for Textual Adversarial Attack.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Wasserstein Contrastive Representation Distillation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
Weakly supervised cross-domain alignment with optimal transport.
CoRR, 2020

Graph Optimal Transport for Cross-Domain Alignment.
Proceedings of the 37th International Conference on Machine Learning, 2020

Improving Text Generation with Student-Forcing Optimal Transport.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Advancing weakly supervised cross-domain alignment with optimal transport.
Proceedings of the 31st British Machine Vision Conference 2020, 2020

Graph-Driven Generative Models for Heterogeneous Multi-Task Learning.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Dynamic Embedding on Textual Networks via a Gaussian Process.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Sequence Generation with Optimal-Transport-Enhanced Reinforcement Learning.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
LMVP: Video Predictor with Leaked Motion Information.
CoRR, 2019

Improving Textual Network Learning with Variational Homophilic Embeddings.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

On Fenchel Mini-Max Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Variational Annealing of GANs: A Langevin Perspective.
Proceedings of the 36th International Conference on Machine Learning, 2019

Improving Sequence-to-Sequence Learning via Optimal Transport.
Proceedings of the 7th International Conference on Learning Representations, 2019

Towards Generating Long and Coherent Text with Multi-Level Latent Variable Models.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Improving Textual Network Embedding with Global Attention via Optimal Transport.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018
Sequence Generation with Guider Network.
CoRR, 2018

Adversarial Text Generation via Feature-Mover's Distance.
CoRR, 2018

A Unified Particle-Optimization Framework for Scalable Bayesian Sampling.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Adversarial Text Generation via Feature-Mover's Distance.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Chi-square Generative Adversarial Network.
Proceedings of the 35th International Conference on Machine Learning, 2018

Variational Inference and Model Selection with Generalized Evidence Bounds.
Proceedings of the 35th International Conference on Machine Learning, 2018

Symmetric Variational Autoencoder and Connections to Adversarial Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Symmetric Variational Autoencoder and Connections to Adversarial Learning.
CoRR, 2017

Towards Understanding Adversarial Learning for Joint Distribution Matching.
CoRR, 2017

Adversarial Symmetric Variational Autoencoder.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Triangle Generative Adversarial Networks.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017


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