·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Welcome NVIDIA Cosmos 3: The First Open Omni-model for Physical AI Reasoning and Action8h◆Physically Viable World Models: A Case for Query-Conditioned Embodied AI9h◆Discovering a Zeta Map Algorithm on Dyck Paths via Mechanistic Interpretability9h◆Diagnosing Failure Modes of Shared-State Collaboration in Resource-Constrained Visual Agents9h◆Answer-Set-Programming-based Abstractions for Reinforcement Learning9h◆TRINE: A Token-Aware, Runtime-Adaptive FPGA Inference Engine for Multimodal AI9h◆Prior Availability in Industrial Visual Sim-to-Real: A Review of CAD-Guided and CAD-Unavailable Regimes9h◆BOKBO (Best of K Bad Options): Calibrated Abstention for VLA Policies9h◆Universal Decision Learners9h◆Algorithmic Recourse of In-Context Learning for Tabular Data9h◆Graph Machine Learning in the Era of Large Language Models (LLMs)9h◆NGDBench: Towards Neural Graph Data Management9h◆End-to-End Compression for Tabular Foundation Models9h◆SLAT: Segment-Level Adaptive Trimming for Efficient CoT Reasoning9h◆A Pilot Study on Curator-Guided Multilingual Art Description for Blind and Low-Vision Audiences with Small Vision-Language Models9h◆Counterfactual Trace Auditing of LLM Agent Skills9h◆GETA: Generalized Encrypted Traffic Analysis9h◆LongDS-Bench: On the Failure of Long-Horizon Agentic Data Analysis9h◆Value Functions as Supermartingale Certificates9h◆PithTrain: A Compact and Agent-Native MoE Training System9h◆Welcome NVIDIA Cosmos 3: The First Open Omni-model for Physical AI Reasoning and Action8h◆Physically Viable World Models: A Case for Query-Conditioned Embodied AI9h◆Discovering a Zeta Map Algorithm on Dyck Paths via Mechanistic Interpretability9h◆Diagnosing Failure Modes of Shared-State Collaboration in Resource-Constrained Visual Agents9h◆Answer-Set-Programming-based Abstractions for Reinforcement Learning9h◆TRINE: A Token-Aware, Runtime-Adaptive FPGA Inference Engine for Multimodal AI9h◆Prior Availability in Industrial Visual Sim-to-Real: A Review of CAD-Guided and CAD-Unavailable Regimes9h◆BOKBO (Best of K Bad Options): Calibrated Abstention for VLA Policies9h◆Universal Decision Learners9h◆Algorithmic Recourse of In-Context Learning for Tabular Data9h◆Graph Machine Learning in the Era of Large Language Models (LLMs)9h◆NGDBench: Towards Neural Graph Data Management9h◆End-to-End Compression for Tabular Foundation Models9h◆SLAT: Segment-Level Adaptive Trimming for Efficient CoT Reasoning9h◆A Pilot Study on Curator-Guided Multilingual Art Description for Blind and Low-Vision Audiences with Small Vision-Language Models9h◆Counterfactual Trace Auditing of LLM Agent Skills9h◆GETA: Generalized Encrypted Traffic Analysis9h◆LongDS-Bench: On the Failure of Long-Horizon Agentic Data Analysis9h◆Value Functions as Supermartingale Certificates9h◆PithTrain: A Compact and Agent-Native MoE Training System9h◆
News/InterChart: Benchmarking Visual Reasoning Across Decomposed and Distributed Chart Information
arxiv
PublishedMay 5, 2026 at 4:00 AM
—neutral

InterChart: Benchmarking Visual Reasoning Across Decomposed and Distributed Chart Information

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2508.07630v2 Announce Type: replace-cross Abstract: We introduce InterChart, a diagnostic benchmark that evaluates how well vision-language models (VLMs) reason across multiple related charts, a task central to real-world applications such as scientific reporting, financial analysis, and publi

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

// no spam · unsubscribe one-click · free forever

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#benchmark#vision-language#multimodal-reasoning#evaluation

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#benchmark#vision-language#multimodal-reasoning#evaluation

Related coverage

More from ARXIV
arxivPhysically Viable World Models: A Case for Query-Conditioned Embodied AI9harxivDiscovering a Zeta Map Algorithm on Dyck Paths via Mechanistic Interpretability9harxivDiagnosing Failure Modes of Shared-State Collaboration in Resource-Constrained Visual Agents9harxivAnswer-Set-Programming-based Abstractions for Reinforcement Learning9h
The Bubble Brief
WEEKLY

Read benchmark insights every Tuesday — top movers, new releases, story of the week.

// no spam · unsubscribe one-click · free forever

Originally published on arxiv ↗
HomeModelsNews