Papers with memorisation-generalisation map

1 papers
Memorisation Cartography: Mapping out the Memorisation-Generalisation Continuum in Neural Machine Translation (2023.emnlp-main)

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Challenge: Using the counterfactual memorisation metric, we find that when training neural networks, models will memorise some inputs but not others.
Approach: They use the counterfactual memorisation metric to build a resource that places 5M NMT datapoints on a memorisations-generalisation map and describe how the datapoint’s surface-level characteristics and a models’ per-datum training signals are predictive of memorising in NMT.
Outcome: The proposed model places 5M NMT datapoints on a memorisation-generalisation map and shows how their surface-level characteristics and models’ per-datum training signals are predictive of memorising in NMT.

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