Research map / Vision-language and multimodal / Visual question answering
A simple neural network module for relational reasoning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add a Relation Network to the CNN+LSTM visual QA architecture | CNN+LSTM · CLEVR pixel test | overall accuracy: 68.5 to 95.5 | Helped |
| Use a Relation Network instead of an MLP reasoning module | CNN-based Sort-of-CLEVR model · Sort-of-CLEVR relational questions | accuracy: 63% to above 94% | Helped |
| Use a Relation Network instead of an MLP reasoning module | CNN-based Sort-of-CLEVR model · Sort-of-CLEVR non-relational questions | accuracy | No clear effect |
| Use a Relation Network for dynamic ball connection inference | Dynamic physical systems model · Connection inference | correctly classified test scenes | Helped |
| Use a Relation Network for counting connected systems | Dynamic physical systems model · Counting | scenes with correct count | Helped |
| Use an RN architecture for basic induction | bAbI · Basic induction task | total error: 2.1% total error; Sparse DNC 54%; DNC 55.1%; EntNet 52.1% | Helped |
Closest papers by meaning
- Recurrent Relational Networks (NeurIPS 2018 · similarity 0.91)
- When No Paths Lead to Rome: Benchmarking Systematic Neural Relational Reasoning (NeurIPS 2025 · similarity 0.88)
- Systematic Relational Reasoning With Epistemic Graph Neural Networks (ICLR 2025 · similarity 0.87)
- When can transformers reason with abstract symbols? (ICLR 2024 · similarity 0.86)
- ChainMPQ: Interleaved Text-Image Reasoning Chains for Mitigating Relation Hallucinations (ICLR 2026 · similarity 0.85)
- Reasoning of Large Language Models over Knowledge Graphs with Super-Relations (ICLR 2025 · similarity 0.85)
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