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20172026
most citedApplied Causal Inference Powered by ML and AI

37 citations · 117 across the 38 of their papers we have counts for

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cs.LG2026

A positive resolution of the gap-entropy conjecture

P. M. Aronow, Nathan Kallus, Patrick Lopatto

We prove the gap-entropy conjecture for fixed-confidence best-arm identification with independent unit-variance Gaussian arms, means in , and a unique optimal arm. For each…

cs.LG2026

Causal Inference on Networks under Misspecified Exposure Mappings: A Partial Identification Framework

Maresa Schröder, Miruna Oprescu, Stefan Feuerriegel +1

Estimating treatment effects in networks is challenging, as each potential outcome depends on the treatments of all other nodes in the network. To overcome this difficulty, existin…

cs.LG2025

Exploration in the Limit

Brian M. Cho, Nathan Kallus

In fixed-confidence best arm identification (BAI), the objective is to quickly identify the optimal option while controlling the probability of error below a desired threshold. Des…

cs.LG2025

Entropy After </Think> for reasoning model early exiting

Xi Wang, James McInerney, Lequn Wang +1

Reasoning LLMs show improved performance with longer chains of thought. However, recent work has highlighted their tendency to overthink, continuing to revise answers even after re…

cs.LG2025

Optimization of Epsilon-Greedy Exploration

Ethan Che, Hakan Ceylan, James McInerney +1

Modern recommendation systems rely on exploration to learn user preferences for new items, typically implementing uniform exploration policies (e.g., epsilon-greedy) due to their s…

cs.LG2025

Value-Guided Search for Efficient Chain-of-Thought Reasoning

Kaiwen Wang, Jin Peng Zhou, Jonathan Chang +4

In this paper, we propose a simple and efficient method for value model training on long-context reasoning traces. Compared to existing process reward models (PRMs), our method doe…