Papers with Evidence Truncation
Diversify, Rationalize, and Combine: Ensembling Multiple QA Strategies for Zero-shot Knowledge-based VQA (2024.findings-emnlp)
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| Challenge: | Knowledge-based Visual Qustion-answering (K-VQA) often requires background knowledge beyond the image content. |
| Approach: | They propose a method that uses a bundle of complementary question-answering tactics to aggregate their answers using textual rationales. |
| Outcome: | Experiments show that DietCoke outperforms state-of-the-art LLM-based baselines by 2.8% and 4.7% on K-VQA. |