2 papers
cs.CL2026
Multilingual Refusal Alignment for Safer Large Language Models
Aleksandra KrasnodÄbska, Wojciech Kusa, Aldo Lipani
As Large Language Models (LLMs) are deployed globally, ensuring their safety and alignment across multiple languages becomes paramount. However, safety behaviors often vary unpredi…
cs.LG2025
Encode, Think, Decode: Scaling test-time reasoning with recursive latent thoughts
Yeskendir Koishekenov, Aldo Lipani, Nicola Cancedda
Most efforts to improve the reasoning capabilities of large language models (LLMs) involve either scaling the number of parameters and the size of training data, or scaling inferen…