Research map / Vision-language and multimodal / Visual question answering
Attentive Interactive Neural Networks for Answer Selection in Community Question Answering
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| AI-CNN vs best baseline Kelp | answer selection · SemEval-2016 Task 3 CQA | MAP: 79.19 -> 80.14 | Helped |
| add attention using all information (ablation) | AI-CNN w/o features · SemEval-2016 Task 3 CQA | MAP: 78.05 -> 79.17 | Helped |
| attention from segment representation only (ablation) | AI-CNN · SemEval-2016 Task 3 CQA | MAP: 78.05 -> 78.83 | Helped |
| attention from question topic only (ablation) | AI-CNN · SemEval-2016 Task 3 CQA | MAP: 78.05 -> 77.91 | Hurt |
| attention from question type only (ablation) | AI-CNN · SemEval-2016 Task 3 CQA | MAP: 78.05 -> 78.22 | No clear effect |
| add four handcrafted features (ablation) | AI-CNN · SemEval-2016 Task 3 CQA | MAP: 79.17 -> 80.14 | Helped |
| add anonymous-user feature alone (ablation) | AI-CNN · SemEval-2016 Task 3 CQA | MAP: 79.17 -> 78.87 | Hurt |
| add same-user feature alone (ablation) | AI-CNN · SemEval-2016 Task 3 CQA | MAP: 79.17 -> 79.62 | Helped |
Closest papers by meaning
- Hybrid Attentive Answer Selection in CQA With Deep Users Modelling (AAAI 2018 · similarity 0.92)
- COALA: A Neural Coverage-Based Approach for Long Answer Selection with Small Data (AAAI 2019 · similarity 0.90)
- Attentive User-Engaged Adversarial Neural Network for Community Question Answering (AAAI 2020 · similarity 0.88)
- Joint Learning of Answer Selection and Answer Summary Generation in Community Question Answering (AAAI 2020 · similarity 0.88)
- Community-Based Question Answering via Asymmetric Multi-Faceted Ranking Network Learning (AAAI 2017 · similarity 0.88)
- Answer, Assemble, Ace: Understanding How LMs Answer Multiple Choice Questions (ICLR 2025 · similarity 0.84)
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