Image de couverture de livre

GIRL: Generative Imagination Reinforcement Learning via Information-Theoretic Hallucination Control

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	Hiremath, Prakul Sunil
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning Artificial Intelligence I.2.6; I.2.8
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Regret-Aware Policy Optimization: Environment-Level Memory for Replay Suppression under Delayed Harm
par: Hiremath, Prakul Sunil
Publié: (2026)

Safe Reinforcement Learning with Preference-based Constraint Inference
par: Li, Chenglin, et autres
Publié: (2026)

CORE: Towards Scalable and Efficient Causal Discovery with Reinforcement Learning
par: Sauter, Andreas W. M., et autres
Publié: (2024)

Umbrella Reinforcement Learning -- computationally efficient tool for hard non-linear problems
par: Nuzhin, Egor E., et autres
Publié: (2024)

AI and Machine Learning Approaches for Predicting Nanoparticles Toxicity The Critical Role of Physiochemical Properties
par: Yousaf, Iqra
Publié: (2024)

SMOSE: Sparse Mixture of Shallow Experts for Interpretable Reinforcement Learning in Continuous Control Tasks
par: Vincze, Mátyás, et autres
Publié: (2024)

Incentives for Responsiveness, Instrumental Control and Impact
par: Carey, Ryan, et autres
Publié: (2020)

Sketch Decompositions for Classical Planning via Deep Reinforcement Learning
par: Aichmüller, Michael, et autres
Publié: (2024)

What Do World Models Learn in RL? Probing Latent Representations in Learned Environment Simulators
par: Zhang, Xinyu
Publié: (2026)

Hybrid-AIRL: Enhancing Inverse Reinforcement Learning with Supervised Expert Guidance
par: Silue, Bram, et autres
Publié: (2025)

Working Paper: Active Causal Structure Learning with Latent Variables: Towards Learning to Detour in Autonomous Robots
par: Riscos, Pablo de los, et autres
Publié: (2024)

On the Generalization Gap in LLM Planning: Tests and Verifier-Reward RL
par: Belcamino, Valerio, et autres
Publié: (2026)

Embedded Safety-Aligned Intelligence via Differentiable Internal Alignment Embeddings
par: Rathva, Harsh, et autres
Publié: (2025)

Adaptable Hindsight Experience Replay for Search-Based Learning
par: Vazaios, Alexandros, et autres
Publié: (2025)

Differentiable Symbolic Planning: A Neural Architecture for Constraint Reasoning with Learned Feasibility
par: Oruganti, Venkatakrishna Reddy
Publié: (2026)

From Cumulative Constraints to Adaptive Runtime Safety Control for Nonstationary Reinforcement Learning
par: Tomashevskiy, Timofey
Publié: (2026)

A Parallel Hybrid Action Space Reinforcement Learning Model for Real-world Adaptive Traffic Signal Control
par: Wang, Yuxuan, et autres
Publié: (2025)

Zero-Shot Context Generalization in Reinforcement Learning from Few Training Contexts
par: Chapman, James, et autres
Publié: (2025)

Social Interpretable Reinforcement Learning
par: Custode, Leonardo Lucio, et autres
Publié: (2024)

Not All Transitions Matter: Evidence from PPO
par: Basnet, Ajhesh
Publié: (2026)

AGWM: Affordance-Grounded World Models for Environments with Compositional Prerequisites
par: Zhang, Qinshi, et autres
Publié: (2026)

Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search
par: Zawalski, Michał, et autres
Publié: (2022)

Score-informed Neural Operator for Enhancing Ordering-based Causal Discovery
par: Kang, Jiyeon, et autres
Publié: (2025)

Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning
par: Wang, Zizhao, et autres
Publié: (2024)

Fractional Policy Gradients: Reinforcement Learning with Long-Term Memory
par: Pawar, Urvi, et autres
Publié: (2025)

Constrained Auto-Bidding via Generative Response Modeling
par: Yang, Eunseok, et autres
Publié: (2026)

SafeRL-Lite: A Lightweight, Explainable, and Constrained Reinforcement Learning Library
par: Mishra, Satyam, et autres
Publié: (2025)

Learning Nonlinear Regime Transitions via Semi-Parametric State-Space Models
par: Hiremath, Prakul Sunil
Publié: (2026)

On the Limits of Learned Importance Scoring for KV Cache Compression
par: Steele, Brady
Publié: (2026)

FlowRL: Flow-Augmented Few-Shot Reinforcement Learning for Semi-Structured Sensor Data
par: Pivezhandi, Mohammad, et autres
Publié: (2024)

NeSIG: A Neuro-Symbolic Method for Learning to Generate Planning Problems
par: Núñez-Molina, Carlos, et autres
Publié: (2023)

Dynamic Policy Induction for Adaptive Prompt Optimization: Bridging the Efficiency-Accuracy Gap via Lightweight Reinforcement Learning
par: Xu, Jiexi
Publié: (2025)

Combining Trained Models in Reinforcement Learning
par: Patil, Ujjwal, et autres
Publié: (2026)

Learning to Select Goals in Automated Planning with Deep-Q Learning
par: Núñez-Molina, Carlos, et autres
Publié: (2024)

Resolving Action Bottleneck: Agentic Reinforcement Learning Informed by Token-Level Energy
par: He, Langzhou, et autres
Publié: (2026)

The State of Robot Motion Generation
par: Bekris, Kostas E., et autres
Publié: (2024)

Centrally Coordinated Multi-Agent Reinforcement Learning for Power Grid Topology Control
par: de Mol, Barbera, et autres
Publié: (2025)

SCULPT: Constraint-Guided Pruned MCTS that Carves Efficient Paths for Mathematical Reasoning
par: Fang, Qitong, et autres
Publié: (2026)

Scaling Trends for Multi-Hop Contextual Reasoning in Mid-Scale Language Models
par: Steele, Brady, et autres
Publié: (2026)

The ARC of Progress towards AGI: A Living Survey of Abstraction and Reasoning
par: Vahdati, Sahar, et autres
Publié: (2026)