2 citations · 2 across the 9 of their papers we have counts for
9 papers
On Minimax Optimality and Uniqueness of Fixed-Step First-Order Methods for Smooth Convex Optimization
Benjamin Grimmer, Sunghyeon Jo, Chanwoo Park
This paper considers the design of optimal fixed-step first-order methods for high-dimensional minimization of -smooth convex functions. For optimizing worst-case performance me…
HyperStyler: Low-resource Authorship Style Transfer via Context-aware Style Navigation and Hypernetworks
Jongkyung Shin, Minguk Jeon, Chanwoo Park +1
Low-resource authorship style transfer (LAST) aims to rewrite text into the style of an arbitrary target author using only a few reference examples while preserving the original me…
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…
Post-Training LLMs as Better Decision-Making Agents: A Regret-Minimization Approach
Chanwoo Park, Ziyang Chen, Asuman Ozdaglar +1
Large language models (LLMs) are increasingly deployed as "agents" for decision-making (DM) in interactive and dynamic environments. Yet, since they were not originally designed fo…
MAPoRL: Multi-Agent Post-Co-Training for Collaborative Large Language Models with Reinforcement Learning
Chanwoo Park, Seungju Han, Xingzhi Guo +3
Leveraging multiple large language models (LLMs) to build collaborative multi-agentic workflows has demonstrated significant potential. However, most previous studies focus on prom…
RLHF from Heterogeneous Feedback via Personalization and Preference Aggregation
Chanwoo Park, Mingyang Liu, Dingwen Kong +2
Reinforcement learning from human feedback (RLHF) has been an effective technique for aligning AI systems with human values, with remarkable successes in fine-tuning large-language…
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…
Mirror Duality in Convex Optimization
Jaeyeon Kim, Chanwoo Park, Asuman Ozdaglar +2
While first-order optimization methods are usually designed to efficiently reduce the function value , there has been recent interest in methods efficiently reducing the magn…