2026
How Does Alignment Enhance LLMs’ Multilingual Capabilities? A Language Neurons Perspective
AAAI 2026technical
Multilingual Alignment is an effective and representative paradigm to enhance LLMs
4 accepted papers
Multilingual Alignment is an effective and representative paradigm to enhance LLMs
Large Language Models have demonstrated outstanding performance across various downstream tasks and have been widely applied in multiple scenarios. Human-annotated preference data is used for training to further improve LLMs’ performance, which is constrained by the upper limit of human performance.…
Recently, Large Language Models (LLMs) have shown impressive language capabilities, while most of them have very unbalanced performance across different languages. Multilingual alignment based on the translation parallel data is an effective method to enhance LLMs’ multilingual capabilities. In this…
We investigate the problem of distributed online convex optimization with complicated constraints, in which the projection operation could be the computational bottleneck. To avoid projections, distributed online projection-free methods have been proposed and attain an O(T^{3/4}) regret bound for ge…