5 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.LG2024★ 1 cited
Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL
Yunseon Choi, Sangmin Bae, Seonghyun Ban +6
With the advent of foundation models, prompt tuning has positioned itself as an important technique for directing model behaviors and eliciting desired responses. Prompt tuning reg…
cs.CL2024★ 5 cited
Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning
Haeju Lee, Minchan Jeong, Se-Young Yun +1
Prompt tuning, in which prompts are optimized to adapt large-scale pre-trained language models to downstream tasks instead of fine-tuning the full model parameters, has been shown…
cs.AI2024
Stitching Sub-Trajectories with Conditional Diffusion Model for Goal-Conditioned Offline RL
Sungyoon Kim, Yunseon Choi, Daiki E. Matsunaga +1
Offline Goal-Conditioned Reinforcement Learning (Offline GCRL) is an important problem in RL that focuses on acquiring diverse goal-oriented skills solely from pre-collected behavi…