5 papers
Beyond Forgetting: Machine Unlearning Elicits Controllable Side Behaviors and Capabilities
Tien Dang, The-Hai Nguyen, Dinh Mai Phuong +5
We consider Representation Misdirection (RM), a class of large language model (LLM) unlearning methods that achieve forgetting by redirecting the forget-representations, that is, l…
FastDiSS: Few-step Match Many-step Diffusion Language Model on Sequence-to-Sequence Generation--Full Version
Dat Nguyen-Cong, Tung Kieu, Hoang Thanh-Tung
Self-conditioning has been central to the success of continuous diffusion language models, as it allows models to correct previous errors. Yet its ability degrades precisely in the…
Guiding Noisy Label Conditional Diffusion Models with Score-based Discriminator Correction
Dat Nguyen Cong, Hieu Tran Bao, Hoang Thanh-Tung
Diffusion models have gained prominence as state-of-the-art techniques for synthesizing images and videos, particularly due to their ability to scale effectively with large dataset…
Learning to Stop Overthinking at Test Time
Hieu Tran Bao, Nguyen Cong Dat, Nguyen Duc Anh +1
Test time scaling is currently one of the most active research areas that shows promise after training time scaling has reached its limits. Deep-thinking (DT) models are a class of…
On Effects of Steering Latent Representation for Large Language Model Unlearning
Dang Huu-Tien, Trung-Tin Pham, Hoang Thanh-Tung +1
Representation Misdirection for Unlearning (RMU), which steers model representation in the intermediate layer to a target random representation, is an effective method for large la…