From the 1 of 8 linked papers with an AI index.
8 papers
Latent Fact-Checking: Detecting Misinformation through Activation Engineering
Pedro T. Barcelos, Pedro Barcelos, Otávio Parraga +4
The proliferation of misinformation online has driven demand for scalable detection systems. While most existing approaches rely on surface-level linguistic features or external kn…
Inference-Time Machine Unlearning via Gated Activation Redirection
VinÃcius Conte Turani, Otávio Parraga, João Vitor Boer Abitante +7
The paper proposes GUARD-IT, a gradient‑free method that modifies activations at inference time with input‑dependent rotations to erase specific data from large language models whi…
Continual Learning for Sequential Personalization of Small Language Models: A Stability Monitoring Analysis
Thomas S. Paula, Lucas S. Kupssinskü, Rodrigo C. Barros
Small Language Models (SLMs) are increasingly being considered for deployment on edge devices such as laptops, enabling private, low-latency, and locally personalized applications.…
Low-Rank Adapters Initialization via Gradient Surgery for Continual Learning
Joana Pasquali, Ramiro N. Barros, Arthur S. Bianchessi +7
LoRA is widely adopted for continual fine-tuning of Large Language Models due to its parameter efficiency, modularity across tasks, and compatibility with replay strategies. Howeve…
Bayesian Attention Mechanism: A Probabilistic Framework for Positional Encoding and Context Length Extrapolation
Arthur S. Bianchessi, Yasmin C. Aguirre, Rodrigo C. Barros +1
Transformer-based language models rely on positional encoding (PE) to handle token order and support context length extrapolation. However, existing PE methods lack theoretical cla…
Quantization-Robust LLM Unlearning via Low-Rank Adaptation
João Vitor Boer Abitante, Joana Meneguzzo Pasquali, Luan Fonseca Garcia +4
Large Language Model (LLM) unlearning aims to remove targeted knowledge from a trained model, but practical deployments often require post-training quantization (PTQ) for efficient…