2 citations · 2 across the 4 of their papers we have counts for
4 papers · 1 filter
Learning Style, Forgetting Semantics: A Case Study of SFT and RFT on Classification Tasks
Haodong Liang, Yanhao Jin, Krishnakumar Balasubramanian +1
Why does supervised fine-tuning (SFT) lead to more forgetting than reinforcement fine-tuning (RFT), even when all teacher demonstrations are semantically correct? We study this que…
Transformers Provably Implement In-Context Reinforcement Learning with Policy Improvement
Haodong Liang, Lifeng Lai
We investigate the ability of transformers to perform in-context reinforcement learning (ICRL), where a model must infer and execute learning algorithms from trajectory data withou…
Differentially Private Two-Stage Gradient Descent for Instrumental Variable Regression
Haodong Liang, Yanhao Jin, Krishnakumar Balasubramanian +1
We study instrumental variable regression (IVaR) under differential privacy constraints. Classical IVaR methods (like two-stage least squares regression) rely on solving moment equ…
Transformers Handle Endogeneity in In-Context Linear Regression
Haodong Liang, Krishnakumar Balasubramanian, Lifeng Lai
We explore the capability of transformers to address endogeneity in in-context linear regression. Our main finding is that transformers inherently possess a mechanism to handle end…