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Decision Making

Papers

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Showing 1701–1725 of 12311 papers

TitleStatusHype
Wasserstein Distributionally Robust Bayesian Optimization with Continuous ContextCode0
LLM-based Agent Simulation for Maternal Health Interventions: Uncertainty Estimation and Decision-focused EvaluationCode0
Quantifying Symptom Causality in Clinical Decision Making: An Exploration Using CausaLM—0
CubeRobot: Grounding Language in Rubik's Cube Manipulation via Vision-Language Model—0
High-Quality Spatial Reconstruction and Orthoimage Generation Using Efficient 2D Gaussian Splatting—0
A theory of anticipated surprise for understanding risky intertemporal choices—0
Multi-agent Application System in Office Collaboration Scenarios—0
MARS: Memory-Enhanced Agents with Reflective Self-improvement—0
Observation Adaptation via Annealed Importance Resampling for Partially Observable Markov Decision Processes—0
Latent Embedding Adaptation for Human Preference Alignment in Diffusion Planners—0
Option Discovery Using LLM-guided Semantic Hierarchical Reinforcement Learning—0
Enhancing Multi-Label Emotion Analysis and Corresponding Intensities for Ethiopian Languages—0
Statistical Proof of Execution (SPEX)—0
Reinforcement Learning in Switching Non-Stationary Markov Decision Processes: Algorithms and Convergence Analysis—0
EconEvals: Benchmarks and Litmus Tests for LLM Agents in Unknown Environments—0
Generative AI in Knowledge Work: Design Implications for Data Navigation and Decision-Making—0
Surgical Action Planning with Large Language Models—0
Strategic Prompt Pricing for AIGC Services: A User-Centric Approach—0
Optimizing Navigation And Chemical Application in Precision Agriculture With Deep Reinforcement Learning And Conditional Action Tree—0
Active Inference for Energy Control and Planning in Smart Buildings and Communities—0
A Qualitative Study of User Perception of M365 AI Copilot—0
A-IDE : Agent-Integrated Denoising Experts—0
When Debate Fails: Bias Reinforcement in Large Language Models—0
Dancing with Critiques: Enhancing LLM Reasoning with Stepwise Natural Language Self-CritiqueCode0
When Words Outperform Vision: VLMs Can Self-Improve Via Text-Only Training For Human-Centered Decision Making—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SRLAAverage Remaining Cycles6.4—Unverified