2 papers
cs.CL2025
Exploring Explanations Improves the Robustness of In-Context Learning
Ukyo Honda, Tatsushi Oka
In-context learning (ICL) has emerged as a successful paradigm for leveraging large language models (LLMs). However, it often struggles to generalize beyond the distribution of the…
cs.CL2024
Not Eliminate but Aggregate: Post-Hoc Control over Mixture-of-Experts to Address Shortcut Shifts in Natural Language Understanding
Ukyo Honda, Tatsushi Oka, Peinan Zhang +1
Recent models for natural language understanding are inclined to exploit simple patterns in datasets, commonly known as shortcuts. These shortcuts hinge on spurious correlations be…