2 citations · 2 across the 4 of their papers we have counts for
4 papers
Quantifying Aleatoric Uncertainty of In-Context Learning for Robust Measure of LLM Prediction Confidence
Jinseok Chung, Minkyoung Song, Hyunji Jung +1
In-Context Learning (ICL) allows LLMs to adapt to new tasks from a few demonstrations, but its reliability remains a concern: predictions are highly sensitive to both prompt design…
SAFE: Finding Sparse and Flat Minima to Improve Pruning
Dongyeop Lee, Kwanhee Lee, Jinseok Chung +1
Sparsifying neural networks often suffers from seemingly inevitable performance degradation, and it remains challenging to restore the original performance despite much recent prog…
SASSHA: Sharpness-aware Adaptive Second-order Optimization with Stable Hessian Approximation
Dahun Shin, Dongyeop Lee, Jinseok Chung +1
Approximate second-order optimization methods often exhibit poorer generalization compared to first-order approaches. In this work, we look into this issue through the lens of the…
FedFwd: Federated Learning without Backpropagation
Seonghwan Park, Dahun Shin, Jinseok Chung +1
In federated learning (FL), clients with limited resources can disrupt the training efficiency. A potential solution to this problem is to leverage a new learning procedure that do…