2 citations · 2 across the 9 of their papers we have counts for
3 papers · 1 filter
Training with (Swap) Regret Loss in a Single-Layer Self-Attention Model: A Case Study on the Probability Simplex
Chanwoo Park, Asuman Ozdaglar
We revisit the regret loss framework introduced in Park et al. (2025), which uses decision-theoretic regret as a direct loss function for training models to make better decisions,…
Collaborative and Efficient Fine-tuning: Leveraging Task Similarity
Gagik Magakyan, Amirhossein Reisizadeh, Chanwoo Park +2
Adaptability has been regarded as a central feature in the foundation models, enabling them to effectively acclimate to unseen downstream tasks. Parameter-efficient fine-tuning met…
Do LLM Agents Have Regret? A Case Study in Online Learning and Games
Chanwoo Park, Xiangyu Liu, Asuman Ozdaglar +1
Large language models (LLMs) have been increasingly employed for (interactive) decision-making, via the development of LLM-based autonomous agents. Despite their emerging successes…