2 papers
cs.CL2026
Translate-R1: Cost-Aware Translation Tool Use via Reinforcement Learning
Pratik Jayarao, Chaitanya Dwivedi, Himanshu Gupta +5
The performance gap across languages in LLMs is well documented, and closing it natively requires pretraining or fine-tuning on corpora that, for most languages, are quite limited.…
cs.LG2025
AutoMixAlign: Adaptive Data Mixing for Multi-Task Preference Optimization in LLMs
Nicholas E. Corrado, Julian Katz-Samuels, Adithya Devraj +6
When aligning large language models (LLMs), their performance on various tasks (such as being helpful, harmless, and honest) depends heavily on the composition of their training da…