Explores reference document choices for applying DeepSHAP to neural retrieval models and reports that its explanations differ substantially from those of LIME.
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3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.IR 3years
2019 3verdicts
UNVERDICTED 3representative citing papers
A neural semantic matcher for product search uses a custom loss on behavior data, n-gram pooling, and hashing to beat prior methods by 4.7% Recall@100 and 14.5% MAP.
Position paper proposing to extend the OSIRRC replicability infrastructure with two performance benchmark scenarios, backed by a case study on neural re-ranking model runtimes.
citing papers explorer
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A study on the Interpretability of Neural Retrieval Models using DeepSHAP
Explores reference document choices for applying DeepSHAP to neural retrieval models and reports that its explanations differ substantially from those of LIME.
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Semantic Product Search
A neural semantic matcher for product search uses a custom loss on behavior data, n-gram pooling, and hashing to beat prior methods by 4.7% Recall@100 and 14.5% MAP.
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Let's measure run time! Extending the IR replicability infrastructure to include performance aspects
Position paper proposing to extend the OSIRRC replicability infrastructure with two performance benchmark scenarios, backed by a case study on neural re-ranking model runtimes.