arXiv AI June 15, 2026 By Xiaoxian Duan, Zequn Liu, Yingce Xia

VeriGeo: Controllable Geometry Question Generation with Numerical and Analytical Verification

arXiv:2606. 14176v1 Announce Type: new Abstract: Geometry problem generation is useful for AI-assisted education and multimodal mathematical reasoning, but reliable synthesis remains difficult because the problem statement, diagram, constraints, and solution should be mutually consistent.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv AI

Jun 29

Verifiable Geometry Problem Solving: Solver-Driven Autoformalization and Theorem Proposing

arXiv:2606. 27926v1 Announce Type: new Abstract: Geometry Problem Solving have increasingly adopt the neuro-symbolic paradigm, combining neural intuition with symbolic rigor.

By Can Li, Ting Zhang, Junbo Zhao, Hua Huang

agents reinforcement-learning multimodal

arXiv Computation and Language

Sep 1

Reactivating Test-Time Scaling for Plane Geometry Problem Solving

arXiv:2608.30156v1 Announce Type: new Abstract: Plane geometry problem (PGP) solving has become a critical benchmark for multimodal reasoning because it requires accurate visual perception and precis...

By Xiaoqiang Kang, Shengen Wu, Maizhen Ning, Xiaobo Jin, Kaizhu Huang, Yutao Yue, Xiaowei Huang, Qiufeng Wang

multimodal benchmarks

arXiv AI

Jul 15

FormalAnalyticGeo: A Neural-Symbolic Based Framework for Multimodal Analytic Geometry Problem Generation

arXiv:2607. 12982v1 Announce Type: new Abstract: Math reasoning has achieved significant progress with the rapid advancement of Multimodal Large Language Models (MLLMs), however analytic geometry remains largely underexplored, primarily due to the scarcity of annotated samples.

By Ruoran Xu, Wending Gao, Qiufeng Wang

llms multimodal

arXiv AI

Jul 21

Constraint-Anchored Reasoning Traces

arXiv:2607. 16727v1 Announce Type: new Abstract: Autoregressive multimodal large language models (MLLMs) suffer from error snowballing: a single incorrect inference early in a chainof-thought (CoT) trace corrupts all downstream reasoning.

By Zehua Cheng, Wei Dai, Jiahao Sun

llms fine-tuning multimodal benchmarks

arXiv AI

Aug 3

AMTFV: Agentic Mathematical Tool-Flow Verification for LLM Self-Correction

arXiv:2607. 29549v1 Announce Type: new Abstract: Large language models have demonstrated strong mathematical problem-solving capabilities, yet reliably verifying their candidate answers remains challenging.

By Rui Zou, Yutao Zhu, Mengqi Wei, Ji-Rong Wen

llms agents

arXiv Machine Learning

Aug 11

Math-Vision Diagrams: A Comprehensive Benchmark for Evaluating LLM Mathematical Diagram Generation Capabilities

arXiv:2608. 08964v1 Announce Type: new Abstract: The generation of mathematically precise diagrams from tex- tual prompts has emerged as a critical yet underexplored capability of Large Language Models (LLMs).

By Harish Kashyap, Kiran Byadarhaly, Sriram Chakaravarthy, Sanyukta Tuti, Aryan Mistry

llms diffusion benchmarks

One email a morning, machine-written

Related stories

Verifiable Geometry Problem Solving: Solver-Driven Autoformalization and Theorem Proposing

Reactivating Test-Time Scaling for Plane Geometry Problem Solving

FormalAnalyticGeo: A Neural-Symbolic Based Framework for Multimodal Analytic Geometry Problem Generation

Constraint-Anchored Reasoning Traces

AMTFV: Agentic Mathematical Tool-Flow Verification for LLM Self-Correction

Math-Vision Diagrams: A Comprehensive Benchmark for Evaluating LLM Mathematical Diagram Generation Capabilities