arXiv AI
CapGeo-Bench: Decoupling Visual Perception from Reasoning and Evaluating Geometric Understanding
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arXiv Computer Vision
Aug 31
CompareBench: A Benchmark for Visual Comparison Reasoning in Vision-Language Models
The paper introduces CompareBench, a new benchmark suite for evaluating visual comparison reasoning in vision‑language models. It includes TallyBench for object counting, OmniCaps for captioning and tagging, and a 1,200‑question CompareBench that tests quantity, geometric, spatial, and temporal comparisons. Experiments on nine closed‑source models show strong overall performance but persistent weaknesses in counting, spatial reasoning, geometric comparison, and temporal ordering, highlighting visual comparison as a systematic challenge for current VLMs.
arXiv Computer Vision
Sep 14
ChitraMiti: Benchmarking Visual Grounding and Modality Reliance in Bengali Geometric Reasoning
ChitraMiti introduces a synthetic benchmark of 12,874 Bengali planar geometry problems with structured 15‑attribute descriptions, alongside a complementary set of 500 textbook diagrams. Using a three‑phase protocol that tests diagram‑only, diagram‑plus‑description, and description‑only inputs, the study finds that description‑only performance matches diagram‑plus‑description performance across several VLMs, yet models still struggle with cross‑modal verification. Fine‑tuning on ChitraMiti improves results on both datasets, though a gap remains compared to the best zero‑shot model.
arXiv Computation and Language
Sep 10
From Symbolic Perception to Logical Deduction: A Framework for Guiding Language Models in Geometric Reasoning
The paper introduces a framework that combines a Geometric Vision Parser and a Symbolic Solver to enable a Large Language Model to solve complex plane geometry problems. By translating diagrams into symbolic representations and performing formal deductions, the approach reduces hallucinations and produces interpretable, human-like solutions. Experiments on a new benchmark from 2025 Chinese Zhongkao exams show performance comparable to Gemini 2.5 Pro.
arXiv AI
Aug 18
MetaReason: Precise Interleaved Multimodal Reasoning via Editing Meta Information for Solving Geometry Problems
arXiv:2608. 15006v1 Announce Type: cross Abstract: Although visual reasoning is crucial for solving complex geometry tasks, existing vision-language models rely heavily on text-only reasoning.
arXiv AI
Aug 5
JigShape: Evaluating Visual-Geometric Reasoning in VLMs through Jigsaw Puzzles
arXiv:2607. 27670v2 Announce Type: replace-cross Abstract: Jigsaw puzzle solving requires jointly reasoning about visual content and geometric constraints, yet existing benchmarks use rectangular cuts that create ambiguous ground truth in texture-repeated regions.
arXiv Computation and Language
3d ago
Imagine3D-LLM: Teaching MLLMs to Imagine 3D Scenes Before Answering
arXiv:2609.38177v1 Announce Type: cross Abstract: Reasoning about the 3D world from multi-view images remains a fundamental challenge for Multimodal Large Language Models (MLLMs). While modern MLLMs...