Hugging Face Trending Papers
Efficient Cost-Aware LLM Evaluation via Bayesian Bandit Gittins Indices
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arXiv Machine Learning
Sep 23
Efficient Cost-Aware LLM Evaluation via Bayesian Bandit Gittins Indices
arXiv:2609.25645v1 Announce Type: new Abstract: Exhaustively evaluating every candidate LLM configuration on every benchmark item to identify a high-performing one is costly. We formulate configurati...
arXiv AI
Sep 2
Bandits in Prod: Hyperparameter Optimization at Inference Time
The paper introduces Online Hyperparameter Optimization (OHPO), framing it as an infinitely many‑armed bandit problem over mixed and conditional search spaces. It proposes the IMABO framework, which couples any bandit policy with any oracle for proposing new configurations, and presents IMOSS—a restart‑free anytime policy with provable regret bounds. Experiments show that IMABO, combined with practical oracles such as TPE, an incumbent‑mutation oracle, and a pretrained tabular foundation model, outperforms random search across a range of settings from classical ML models to LLM‑based agents.
arXiv Machine Learning
Jul 8
No-Regret Gaussian Process Optimization of Time-Varying Functions
arXiv:2512. 00517v3 Announce Type: replace-cross Abstract: Sequential optimization of black-box functions from noisy evaluations has been widely studied, with Gaussian Process bandit algorithms such as GP-UCB guaranteeing no-regret in stationary settings.
arXiv AI
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RecHarness: A Bandit-Routed Agentic Harness for Self-Evolving Recommender Systems
arXiv:2607. 29241v1 Announce Type: cross Abstract: Optimizing modern recommender models still depends heavily on engineers manually iterating over architectural, objective, and training-strategy changes.
arXiv AI
Jul 13
Correlation-Aware Contextual Bandits with Surrogate Rewards for LLM Routing
arXiv:2607. 09015v1 Announce Type: cross Abstract: We study contextual bandit problems with correlated arms and access to surrogate reward signals produced by a machine learning model, motivated by applications such as large language model (LLM) routing.
arXiv Machine Learning
Aug 18
Improved Regret Analysis for Parallel Gaussian Process Bandit Optimization
arXiv:2608. 16492v1 Announce Type: cross Abstract: This paper studies the regret analysis for parallel Gaussian process (GP) bandit optimization.