From the 1 of 10 linked papers with an AI index.
3 papers · 1 filter
Distilling the Essence: Efficient Reasoning Distillation via Sequence Truncation
Wei-Rui Chen, Vignesh Kothapalli, Ata Fatahibaarzi +5
Distilling the capabilities from a large reasoning model (LRM) to a smaller student model often involves training on substantial amounts of reasoning data. However, knowledge disti…
To Think or Not to Think: The Hidden Cost of Meta-Training with Excessive CoT Examples
Vignesh Kothapalli, Ata Fatahibaarzi, Hamed Firooz +1
Chain-of-thought (CoT) prompting combined with few-shot in-context learning (ICL) has unlocked significant reasoning capabilities in large language models (LLMs). However, ICL with…
CoT-ICL Lab: A Synthetic Framework for Studying Chain-of-Thought Learning from In-Context Demonstrations
Vignesh Kothapalli, Hamed Firooz, Maziar Sanjabi
We introduce CoT-ICL Lab, a framework and methodology to generate synthetic tokenized datasets and systematically study chain-of-thought (CoT) in-context learning (ICL) in language…