Learning to Pose Problems: Reasoning-Driven and Solver-Adaptive Data Synthesis

arXiv:2511.09907 · cs.AI, cs.CV · Submitted 2025-11-13 · Read on arXiv

cs.AI, cs.CV

Submitted: 2025-11-13

Updated: 2026-10-15

Terminology

• Generator — 3× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Vision-language models — 1× in this paper · explained in 2 episodes

Related papers

• MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
• Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
• Agents' Last Exam
• The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
• MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
• Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems