Knowledge Dependency Estimation for Reliable Question Answering
Researchers have developed a new method called Knot to estimate the knowledge dependencies of question-answering models. This technique aims to identify which pieces of information a model relies on to generate an answer, addressing the challenge of noisy and redundant knowledge sources in large language model-based QA systems. Knot uses subset-level counterfactual supervision and models subset sensitivity to provide fine-grained dependency scores, outperforming existing baselines in predicting subset sensitivity and identifying influential knowledge candidates. AI