Volatility promotes exploration and stochasticity suppresses it in Gaussian state-space bandits, shown by extending Gittins indices and deriving the CAUSE exploration bonus via control-as-inference.
Finite-time analysis of the multiarmed bandit problem.Machine learning, 47(2):235–256
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Framing LLM agent loops as a Context Gathering Decision Process POMDP yields a predicate-based belief state that boosts multi-hop reasoning up to 11.4% and an exhaustion gate that cuts token use up to 39% with no performance loss.
DAPRO adaptively spends a fixed interaction budget across multi-turn LLM conversations and builds valid lower bounds on time-to-jailbreak, with coverage error scaling as the square root of the mean censoring weight.
COMPASS-Hedge is claimed to be the first parameter-free full-information anytime algorithm with simultaneous minimax adversarial, gap-dependent stochastic, and near-constant baseline-relative regret.
Develops COF algorithm for MAB-CS that intelligently checks cheap arm feasibility by pooling samples, with generalized instance-dependent lower bounds and matching upper bounds on cumulative cost and quality regret.
BlossomPsy combines multi-turn LLM dialogue, photo-based items, a multi-head classifier, modified UCB, and PID-tuned confidence scaling for adaptive MBTI assessment with preliminary human and LLM evaluation.
citing papers explorer
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Not all uncertainty is alike: volatility, stochasticity, and exploration
Volatility promotes exploration and stochasticity suppresses it in Gaussian state-space bandits, shown by extending Gittins indices and deriving the CAUSE exploration bonus via control-as-inference.
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The Context Gathering Decision Process: A POMDP Framework for Agentic Search
Framing LLM agent loops as a Context Gathering Decision Process POMDP yields a predicate-based belief state that boosts multi-hop reasoning up to 11.4% and an exhaustion gate that cuts token use up to 39% with no performance loss.
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How Many Iterations to Jailbreak? Dynamic Budget Allocation for Multi-Turn LLM Evaluation
DAPRO adaptively spends a fixed interaction budget across multi-turn LLM conversations and builds valid lower bounds on time-to-jailbreak, with coverage error scaling as the square root of the mean censoring weight.
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Learning Safely Without Knowing the World:COMPASS-Hedge
COMPASS-Hedge is claimed to be the first parameter-free full-information anytime algorithm with simultaneous minimax adversarial, gap-dependent stochastic, and near-constant baseline-relative regret.
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Cost-Ordered Feasibility for Multi-Armed Bandits with Cost Subsidy
Develops COF algorithm for MAB-CS that intelligently checks cheap arm feasibility by pooling samples, with generalized instance-dependent lower bounds and matching upper bounds on cumulative cost and quality regret.
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BlossomPsy: A User-Centric AI System for Adaptive and Engaging MBTI Personality Assessments
BlossomPsy combines multi-turn LLM dialogue, photo-based items, a multi-head classifier, modified UCB, and PID-tuned confidence scaling for adaptive MBTI assessment with preliminary human and LLM evaluation.