#problem-generation News & Analysis

3 articles tagged with #problem-generation. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

3 articles

AINeutralarXiv – CS AI · May 296/10

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A Matter of Interest: Understanding Interestingness of Math Problems in Humans and Language Models

Researchers compared how large language models rate the interestingness of math problems against human judgments from college students and International Math Olympiad competitors. While LLMs show broad agreement with humans, they fail to match the distribution of human preferences and poorly explain why problems are interesting, though they can generate novel engaging problems after validity filtering.

AIBullisharXiv – CS AI · May 116/10

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

Researchers developed a novel framework for synthesizing training data that enables reasoning models to generate high-quality mathematical and reasoning problems by explicitly planning problem directions and adapting difficulty to solver capabilities. The approach achieved a 3.4% cumulative improvement across 10 benchmarks, demonstrating scalable alternatives to manual dataset curation.

AIBullisharXiv – CS AI · May 96/10

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Verifier-Backed Hard Problem Generation for Mathematical Reasoning

Researchers introduce VHG, a verifier-enhanced framework that improves how large language models generate valid and challenging mathematical problems through three-party self-play involving a setter, solver, and independent verifier. The approach addresses critical limitations in existing problem generation methods by constraining reward signals to ensure both problem validity and difficulty, demonstrating substantial improvements over baseline approaches.