1 citations · 2 across the 9 of their papers we have counts for
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MedFeat: Model-Aware and Explainability-Driven Feature Engineering with LLMs for Clinical Tabular Prediction
Zizheng Zhang, Yiming Li, Justin Xu +6
In clinical tabular prediction, classical machine learning models with feature engineering often outperform neural methods. LLMs are increasingly used to automate this process, act…
In-Context Compositional Q-Learning for Offline Reinforcement Learning
Qiushui Xu, Yuhao Huang, Yushu Jiang +4
Accurate estimation of the Q-function is a central challenge in offline reinforcement learning. However, existing approaches often rely on a shared global Q-function, which is inad…
Sample-efficient LLM Optimization with Reset Replay
Zichuan Liu, Jinyu Wang, Lei Song +1
Recent advancements in LLM post-training, particularly through reinforcement learning and preference optimization, are key to boosting their reasoning capabilities. However, these…
Unveiling Markov Heads in Pretrained Language Models for Offline Reinforcement Learning
Wenhao Zhao, Qiushui Xu, Linjie Xu +4
Recently, incorporating knowledge from pretrained language models (PLMs) into decision transformers (DTs) has generated significant attention in offline reinforcement learning (RL)…