sample efficiency

ACE: Adapting sampling for Counterfactual Explanations L4DC 2026 AutoJudger: An Agent-Driven Framework for Efficient Benchmarking of MLLMs ACL 2026 Boosting Vision-Language-Action Finetuning with Feasible Action Neighborhood Prior CVPR 2026 Causality-Aware Efficient Exploration for Cooperative Multi-Agent Reinforcement Learning AAAI 2026 Context-Sensitive Abstractions for Reinforcement Learning with Parameterized Actions AAAI 2026 CRISP: Curriculum-Inducing Primitive Informed Subgoal Prediction for Boosting Hierarchical Reinforcement Learning AAAI 2026 Efficient Solution and Learning of Robust Factored MDPs AAAI 2026 Latent State-Predictive Exploration for Deep Reinforcement Learning AAAI 2026 Learning from Cognition: Enhancing RL Efficiency for LLM Reasoning via Hierarchical Metacognitive Decomposition and Refinement ACL 2026 MARPO: A Reflective Policy Optimization for Multi-Agent Reinforcement Learning AAAI 2026 Memory Based Advantage Shaping for LLM-Guided Reinforcement Learning (Student Abstract) AAAI 2026 MolMem: Memory-Augmented Agentic Reinforcement Learning for Sample-Efficient Molecular Optimization ACL 2026 Online Difficulty Filtering for Reasoning Oriented Reinforcement Learning EACL 2026 On Transportability for Structural Causal Bandits UAI 2026 PSPO: Prompt-Level Prioritization and Experience-Weighted Smoothing for Efficient Policy Optimization AAAI 2026 Stable and Efficient Single-Rollout RL for Multimodal Reasoning CVPR 2026 State Proficiency-Based Adaptive Fine-Tuning for Offline-to-Online Reinforcement Learning AAAI 2026 TIGER-MARL: Enhancing Multi-Agent Reinforcement Learning with Temporal Information through Graph-based Embeddings and Representations L4DC 2026 When transformers learn “impossible” languages, what do they learn? CoNLL 2026 WOMBET: World Model-based Experience Transfer for Robust and Sample-efficient Reinforcement Learning L4DC 2026 A Case for Validation Buffer in Pessimistic Actor-Critic IJCAI 2025 Action abstractions for amortized sampling ICLR 2025 Action-Conditioned Hamiltonian Generative Networks (AC-HGN) for Supervised and Reinforcement Learning L4DC 2025 Adaptive Q-Network: On-the-fly Target Selection for Deep Reinforcement Learning ICLR 2025 Adaptive Experimental Design to Accelerate Scientific Discovery and Engineering Design AAAI 2025