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cs.AI2026
Understanding and Mitigating Premature Confidence for Better LLM Reasoning
Jingchu Gai, Guanning Zeng, Christina Baek +4
Long chains of thought (CoT) from current language models frequently contain logical gaps and unjustified leaps, limiting the gains from additional test-time compute. Improving rea…
cs.LG2026
The Finetuner's Fallacy: When to Pretrain with Your Finetuning Data
Christina Baek, Ricardo Pio Monti, David Schwab +31
Real-world model deployments demand strong performance on narrow domains where data is often scarce. Typically, practitioners finetune models to specialize them, but this risks ove…