Multi Armed Bandit - Edgentiq

Balancing Performance and Safety: A New Approach to Offline Safe Reinforcement Learning

Optimizing Information Retrieval for AI: A Bandit Approach to Complex Queries

Beyond Regret: How Frequency Analysis Illuminates the Multi-Armed Bandit Problem

A New Era for Multi-Armed Bandits: Stable Thompson Sampling with Stochastic Approximation

The Double-Edged Sword: How LLM Training Boosts Performance But Fosters Greed in Decision-Making

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Recently Added

A Strategic Approach to Uncovering Tough Translation Topics

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Accelerating Best-Arm Identification in Graph Bandits with Quantum Walks

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HAEPO: Enhancing Reinforcement Learning with Trajectory-Level Exploration

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Unlocking Math Question Difficulty: A New AI Approach Beyond Language Analysis

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Optimizing Large Language Models for Long Contexts with Adaptive Chunk Sampling

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Optimizing LLM Instruction Tuning with Dynamic Dataset Mixtures

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A New Framework for User-Centric Selection with Proactive Information Acquisition

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Gen AI News and Updates

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Balancing Performance and Safety: A New Approach to Offline Safe Reinforcement Learning

October 28, 2025

Optimizing Information Retrieval for AI: A Bandit Approach to Complex Queries

October 22, 2025

Beyond Regret: How Frequency Analysis Illuminates the Multi-Armed Bandit Problem

October 13, 2025