Learning to Ignore: Long Document Coreference with Bounded Memory Neural Networks

Long document coreference resolution remains a challenging task due to the large memory and runtime requirements of current models. Recent work doing incremental coreference resolution using just the global representation of entities shows practical benefits but requires keeping all entities in memory, which can be impractical for long documents... (read more)

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Datasets


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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Coreference Resolution CoNLL 2012 U-MEM* + SpanBERT-large Avg F1 79.6 # 4
Coreference Resolution OntoNotes U-MEM* + SpanBERT F1 79.6 # 1

Methods used in the Paper


METHOD TYPE
Memory Network
Working Memory Models