Hoang Thanh-Tung

Orcid: 0000-0001-8537-9192

According to our database1, Hoang Thanh-Tung authored at least 20 papers between 2018 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
FastDiSS: Few-step Match Many-step Diffusion Language Model on Sequence-to-Sequence Generation-Full Version.
CoRR, April, 2026

Beyond Forgetting: Machine Unlearning Elicits Controllable Side Behaviors and Capabilities.
CoRR, January, 2026

Improving LLM Unlearning Robustness via Random Perturbations.
Trans. Mach. Learn. Res., 2026

2025
Guiding Noisy Label Conditional Diffusion Models with Score-based Discriminator Correction.
CoRR, August, 2025

Learning to Stop Overthinking at Test Time.
CoRR, February, 2025

Improving the Robustness of Representation Misdirection for Large Language Model Unlearning.
CoRR, January, 2025

Wicked Oddities: Selectively Poisoning for Effective Clean-Label Backdoor Attacks.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Diffusion Directed Acyclic Transformer for Non-Autoregressive Machine Translation.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2025

On Effects of Steering Latent Representation for Large Language Model Unlearning.
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024
On Effects of Steering Latent Representation for Large Language Model Unlearning.
CoRR, 2024

Wicked Oddities: Selectively Poisoning for Effective Clean-Label Backdoor Attacks.
CoRR, 2024

2023
A Cosine Similarity-based Method for Out-of-Distribution Detection.
CoRR, 2023

Class based Influence Functions for Error Detection.
CoRR, 2023

Class based Influence Functions for Error Detection.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

2022
Towards Using Data-Centric Approach for Better Code Representation Learning.
CoRR, 2022

Towards Using Data-Influence Methods to Detect Noisy Samples in Source Code Corpora.
Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering, 2022

2020
Toward a Generalization Metric for Deep Generative Models.
CoRR, 2020

Catastrophic forgetting and mode collapse in GANs.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019
Improving Generalization and Stability of Generative Adversarial Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
On catastrophic forgetting and mode collapse in Generative Adversarial Networks.
CoRR, 2018


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