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cs.LG2026
TANDEM: Bi-Level Data Mixture Optimization with Twin Networks
Jiaxing Wang, Deping Xiang, Jin Xu +9
The capabilities of large language models (LLMs) significantly depend on training data drawn from various domains. Optimizing domain-specific mixture ratios can be modeled as a bi-…
cs.LG2026
Maximizing Mutual Information Between Prompt and Response Improves LLM Performance With No Additional Data
Hyunji Nam, Haoran Li, Natasha Jaques
While post-training has successfully improved large language models (LLMs) across a variety of domains, these gains heavily rely on human-labeled data or external verifiers. Existi…