2 papers
cs.LG2026
In-Context Semi-Supervised Learning
Jiashuo Fan, Paul Rosu, Aaron T. Wang +3
There has been significant recent interest in understanding the capacity of Transformers for in-context learning (ICL), yet most theory focuses on supervised settings with explicit…
stat.ML2025
On Understanding Attention-Based In-Context Learning for Categorical Data
Aaron T. Wang, William Convertino, Xiang Cheng +2
In-context learning based on attention models is examined for data with categorical outcomes, with inference in such models viewed from the perspective of functional gradient desce…