1 citations · 2 across the 9 of their papers we have counts for
9 papers
Improving Chain-of-Thought for Logical Reasoning via Attention-Aware Intervention
Nguyen Minh Phuong, Dang Huu Tien, Naoya Inoue
Modern logical reasoning with LLMs primarily relies on employing complex interactive frameworks that decompose the reasoning process into subtasks solved through carefully designed…
Beyond Forgetting: Representation Misdirection 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 latent representations of forget-s…
Detecting and Rectifying Noisy Labels: A Similarity-based Approach
Dang Huu-Tien, Minh-Phuong Nguyen, Naoya Inoue
Label noise in datasets could significantly damage the performance and robustness of deep neural networks (DNNs) trained on these datasets. As the size of modern DNNs grows, there…
Non-Interactive Symbolic-Aided Chain-of-Thought for Logical Reasoning
Phuong Minh Nguyen, Tien Huu Dang, Naoya Inoue
This work introduces Symbolic-Aided Chain-of-Thought (CoT), an improved approach to standard CoT, for logical reasoning in large language models (LLMs). The key idea is to integrat…
RegMean++: Enhancing Effectiveness and Generalization of Regression Mean for Model Merging
The-Hai Nguyen, Dang Huu-Tien, Takeshi Suzuki +1
Regression Mean (RegMean), an approach that formulates model merging as a linear regression problem, aims to find the optimal weights for each linear layer in the merged model by m…
Improving LLM Unlearning Robustness via Random Perturbations
Dang Huu-Tien, Hoang Thanh-Tung, Anh Bui +3
Here, we show that current LLM unlearning methods inherently reduce models' robustness, causing them to misbehave even when a single non-adversarial forget-token is present in the…
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…
Class based Influence Functions for Error Detection
Thang Nguyen-Duc, Hoang Thanh-Tung, Quan Hung Tran +4
Influence functions (IFs) are a powerful tool for detecting anomalous examples in large scale datasets. However, they are unstable when applied to deep networks. In this paper, we…
Non-Standard Vietnamese Word Detection and Normalization for Text-to-Speech
Huu-Tien Dang, Thi-Hai-Yen Vuong, Xuan-Hieu Phan
Converting written texts into their spoken forms is an essential problem in any text-to-speech (TTS) systems. However, building an effective text normalization solution for a real-…