SOTAVerified

Decision Making

Papers

Showing 701725 of 12311 papers

TitleStatusHype
CAMANet: Class Activation Map Guided Attention Network for Radiology Report GenerationCode1
HOP: History-and-Order Aware Pre-training for Vision-and-Language NavigationCode1
Can GPT-4V(ision) Serve Medical Applications? Case Studies on GPT-4V for Multimodal Medical DiagnosisCode1
Can Learned Optimization Make Reinforcement Learning Less Difficult?Code1
Do Embodied Agents Dream of Pixelated Sheep: Embodied Decision Making using Language Guided World ModellingCode1
Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?Code1
Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMsCode1
Human-Centric Multimodal Machine Learning: Recent Advances and Testbed on AI-based RecruitmentCode1
Hybrid and Automated Machine Learning Approaches for Oil Fields Development: the Case Study of Volve Field, North SeaCode1
Hybrid Multi-agent Deep Reinforcement Learning for Autonomous Mobility on Demand SystemsCode1
Causal-aware Large Language Models: Enhancing Decision-Making Through Learning, Adapting and ActingCode1
Rejecting Hallucinated State Targets during PlanningCode1
CARL-GT: Evaluating Causal Reasoning Capabilities of Large Language ModelsCode1
ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical ImagesCode1
Diverse and Admissible Trajectory Forecasting through Multimodal Context UnderstandingCode1
Improving Recommendation Fairness via Data AugmentationCode1
Goal-directed graph construction using reinforcement learningCode1
In-Context Decision Transformer: Reinforcement Learning via Hierarchical Chain-of-ThoughtCode1
Achieving Robustness to Aleatoric Uncertainty with Heteroscedastic Bayesian OptimisationCode1
Real-Time Machine-Learning-Based Optimization Using Input Convex Long Short-Term Memory NetworkCode1
Integrating Clinical Knowledge into Concept Bottleneck ModelsCode1
Causal Discovery with Language Models as Imperfect ExpertsCode1
Interpretable by Design: Learning Predictors by Composing Interpretable QueriesCode1
A Justice-Based Framework for the Analysis of Algorithmic Fairness-Utility Trade-OffsCode1
Distributive Justice as the Foundational Premise of Fair ML: Unification, Extension, and Interpretation of Group Fairness MetricsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SRLAAverage Remaining Cycles6.4Unverified