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20242026
most citedCombining LLM decision and RL action selection to improve RL policy for adaptive interventions

3 citations · 3 across the 8 of their papers we have counts for

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7 papers · 1 filter

cs.LG2026

Inducing Emergent Misalignment from Reward Hacks with Iterative DPO

Oliver Daniels, Perusha Moodley, Benjamin M. Marlin +1

Reward hacking during reinforcement learning from verifiable rewards (RLVR) can induce reward seeking and broad misalignment in language models. Studying this misgeneralization is…

cs.LG2026

Stress-Testing Alignment Audits With Prompt-Level Strategic Deception

Oliver Daniels, Perusha Moodley, Benjamin M. Marlin +1

Alignment audits aim to robustly identify hidden goals from strategic, situationally aware misaligned models. Despite this threat model, existing auditing methods have not been sys…

cs.LG2025

ACE and Diverse Generalization via Selective Disagreement

Oliver Daniels, Stuart Armstrong, Alexandre Maranhão +3

Deep neural networks are notoriously sensitive to spurious correlations - where a model learns a shortcut that fails out-of-distribution. Existing work on spurious correlations has…

cs.LG2025

Enhancing Adaptive Behavioral Interventions with LLM Inference from Participant-Described States

Karine Karine, Benjamin M. Marlin

The use of reinforcement learning (RL) methods to support health behavior change via personalized and just-in-time adaptive interventions is of significant interest to health and b…

cs.LG20253 cited

Combining LLM decision and RL action selection to improve RL policy for adaptive interventions

Karine Karine, Benjamin M. Marlin

Reinforcement learning (RL) is increasingly being used in the healthcare domain, particularly for the development of personalized health adaptive interventions. Inspired by the suc…

cs.LG2024

BOTS: Batch Bayesian Optimization of Extended Thompson Sampling for Severely Episode-Limited RL Settings

Karine Karine, Susan A. Murphy, Benjamin M. Marlin

In settings where the application of reinforcement learning (RL) requires running real-world trials, including the optimization of adaptive health interventions, the number of epis…