arXiv (All)
open access
GSM8K-V: Can Vision Language Models Solve Grade School Math Word Problems in Visual Contexts
Mathematical reasoning is a key capability for vision-language models (VLMs), yet current benchmarks mainly evaluate text-based or explicitly symbolic visual inputs. It remains unclear whether VLMs can reason mathematically when information must be perceived and inferred from images rather than read
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Reading Right, Answering Wrong: How Visual Configuration Changes Affect Evidence Use in VLMs#1061402
- SinkPruner: Sink-Free Visual Token Pruning for Multimodal Large Language Models#820996
- The Linear Representation Hypothesis for Vision-Language-Action Models#1105555
- Kernel-Based Steering of CLIP with Vision-Language Model Preferences#1116534
- A Survey on Efficient Vision-Language-Action Models#1129131
Record · ID 927168
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive