Is In-Context Learning in Large Language Models Bayesian? A Martingale
Perspective

Is In-Context Learning in Large Language Models Bayesian? A Martingale Perspective

2 June 2024

Chris Holmes

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Papers citing "Is In-Context Learning in Large Language Models Bayesian? A Martingale Perspective"

8 / 8 papers shown

Title
Counterfactual reasoning: an analysis of in-context emergence Moritz Miller Bernhard Schölkopf Siyuan Guo ReLM LRM 177 0 0 05 Jun 2025
Position: The Future of Bayesian Prediction Is Prior-Fitted Samuel G. Müller Arik Reuter Noah Hollmann David Rügamer Frank Hutter 39 0 0 29 May 2025
Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Jiayi Geng Howard Chen Dilip Arumugam Thomas L. Griffiths 109 0 0 23 May 2025
Plan and Budget: Effective and Efficient Test-Time Scaling on Large Language Model Reasoning Junhong Lin Xinyue Zeng Jie Zhu Song Wang Julian Shun Jun Wu Dawei Zhou LRM 165 1 0 22 May 2025
Uncertainty Quantification for Prior-Data Fitted Networks using Martingale Posteriors Thomas Nagler David Rügamer UQCV 103 0 0 16 May 2025
Enough Coin Flips Can Make LLMs Act Bayesian Ritwik Gupta Rodolfo Corona Jiaxin Ge Eric Wang Dan Klein Trevor Darrell David M. Chan BDL LRM 108 3 0 06 Mar 2025
In-Context Parametric Inference: Point or Distribution Estimators? Sarthak Mittal Yoshua Bengio Nikolay Malkin Guillaume Lajoie 136 0 0 17 Feb 2025
Transformers Handle Endogeneity in In-Context Linear Regression Haodong Liang Krishnakumar Balasubramanian Lifeng Lai 147 2 0 02 Oct 2024