Research map / Vision-language and multimodal / Visual question answering
From Recognition to Cognition: Visual Commonsense Reasoning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use R2C instead of BERT | VCR · VCR test Q→AR | accuracy: 35.0 -> 44.0 | Helped |
| Add query representation and query-response contextualization (ablation) | R2C · VCR validation Q→AR | accuracy: 21.5 -> 43.1 | Helped |
| Add the reasoning LSTM (ablation) | R2C · VCR validation Q→AR | accuracy: 42.2 -> 43.1 | Helped |
| Include visual features during grounding (ablation) | R2C · VCR validation Q→AR | accuracy: 33.8 -> 43.1 | Helped |
| Use BERT rather than GloVe representations (ablation) | R2C · VCR validation Q→AR | accuracy: 18.3 -> 43.1 | Helped |
Closest papers by meaning
- Visual Graph Arena: Evaluating Visual Conceptualization of Vision and Multimodal Large Language Models (ICML 2025 · similarity 0.89)
- VisRes Bench: On Evaluating the Visual Reasoning Capabilities of VLMs (CVPR 2026 · similarity 0.89)
- VGR: Visual Grounded Reasoning (ICLR 2026 · similarity 0.89)
- Benchmarking Multimodal Mathematical Reasoning with Explicit Visual Dependency (NeurIPS 2026 · similarity 0.89)
- Long Grounded Thoughts: Synthesizing Visual Problems and Reasoning Chains at Scale (ICML 2026 · similarity 0.88)
- HumanPCR: Probing MLLM Capabilities in Diverse Human-Centric Scenes (ICLR 2026 · similarity 0.88)
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