Coreference Resolution
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Benchmarks
Winograd Schema Challenge
OntoNotes
CoNLL 2012
GAP
DWIE
WikiCoref
CoNLL12
LitBank
OntoGUM
PreCo
STM-coref
XWinograd EN
XWinograd FR
DocRED-IE
Quizbowl
The ARRAU Corpus
Most implemented
Attention Is All You Need
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Language Models are Few-Shot Learners
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Deep contextualized word representations
Language Models are Unsupervised Multitask Learners
Papers
Activation-Guided Neuron Intervention to Induce Alzheimer's-Related Computational Language Phenotypes in a Large Language Model
Changes in spontaneous speech provide an early signal of cognitive dysfunction in Alzheimer's disease (AD) that large language models (LLMs) can detect. However, detection alone cannot establish whether the underlying mo…
Coreference ResolutionImproving Ad-hoc Search Effectiveness for Conversational Information Retrieval via Model Merging
Conversational information retrieval is challenging since it requires the consideration of the conversation history which potentially gives rise to topic shifts and coreference resolution across previous turns. To addres…
Coreference ResolutionInformation RetrievalFrom Gentlemen to Frontiermen: Masculine Formations in English-Language Fiction (1771--1930)
Masculinity in nineteenth-century fiction is not a single ideal but a field of competing scripts. Drawing on 150 British and American canonical novels from the txtLAB Novel450 corpus, published between 1771 and 1930, thi…
Coreference ResolutionIntroducing corpora Hlava Cor and Hlava AD: Human Label Variation in Coreference and Discourse Relations
As previous research on annotator disagreement in discourse phenomena has shown, understanding text coherence varies considerably from one individual to another. To explore this phenomenon, we created two corpora with mu…
Coreference ResolutionRandomized YaRN Improves Length Generalization for Long-Context Reasoning
Large language models (LLMs) are typically pretrained on short sequences and then extended to work on longer sequences with additional training. However, such LLMs still struggle to further generalize to very long sequen…
Coreference ResolutionPlug-and-Adapt: Multimodal Coreference Resolution at First Sight with a Pretrained Alignment Model
Visual information helps resolve ambiguity in coreference resolution, leading to notable performance gains. However, existing Multi-modal Coreference Resolution (MCR) methods require training with (partially) annotated d…
Coreference Resolution