Maximum Likelihood Estimation is All You Need for Well-Specified Covariate Shift
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Position: Scaling Simulation is Neither Necessary Nor Sufficient for In-the-Wild Robot Manipulation
MMA: Multi-Modal Adapter for Vision-Language Models
RAG-SR: Retrieval-Augmented Generation for Neural Symbolic Regression
SaCo Loss: Sample-Wise Affinity Consistency for Vision-Language Pre-Training
HyPoGen: Optimization-Biased Hypernetworks for Generalizable Policy Generation
Cocktail: Mixing Multi-Modality Control for Text-Conditional Image Generation
@article{ge2026maximum,
title = {Maximum Likelihood Estimation is All You Need for Well-Specified Covariate Shift},
author = {Jiawei Ge and Shange Tang and Jianqing Fan and Cong Ma and Chi Jin},
year = {2026},
url = {https://api.semanticscholar.org/CorpusID:08309e107788089b95f368a9716f2b98ccf6219d},
journal = {ICLR 2024 2024}
}Shows whether official code is linked for this paper.
[](https://codeofpaper.com/paper/08309e107788089b95f368a9716f2b98ccf6219d)