A Deterministic Algorithm for Bridging Anaphora Resolution (D18-1)

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Challenge: Existing methods for bridging anaphora resolution only consider NPs’ head nouns and thus do not capture the semantics of NP.
Approach: They propose a deterministic approach to bridging anaphora resolution which represents the semantics of an NP based on its head noun and modifications.
Outcome: The proposed approach achieves competitive results compared to the best system in Hou et al. (2013) which explores Markov Logic Networks to model the problem.

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Enhanced Word Representations for Bridging Anaphora Resolution (N18-2)

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Challenge: Existing word representations do not capture semantic similarity for bridging anaphora resolution.
Approach: They propose to use word embeddings to capture semantic similarity by exploring syntactic structure of noun phrases.
Outcome: The proposed model achieves 30% of accuracy for bridging anaphora resolution on ISNotes corpus.
Bridging resolution: Task definition, corpus resources and rule-based experiments (C18-1)

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Challenge: Recent work on bridging resolution has been based on the corpus ISNotes, as this was the only corpus available with unrestricted bridling annotations.
Approach: They propose a rule-based system to resolve bridging annotations in ISNotes corpus and apply it to new corpora.
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Bridging Resolution: A Survey of the State of the Art (2020.coling-main)

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Challenge: bridging resolution is an anaphora resolution task that is less studied than entity coreference resolution.
Approach: This paper presents a survey of the current state of research on bridging resolution . it identifies and resolves bridling/associative anaphors, which are anamorphic references to non-identical associated antecedents.
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How to represent a word and predict it, too: Improving tied architectures for language modelling (D18-1)

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Challenge: Recent state-of-the-art models use word embeddings as input and output mappings instead of tied models.
Approach: They propose to decouple hidden state from word embedding prediction . they extend their proposed modification to word2vec models .
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Bridging Anaphora Resolution as Question Answering (2020.acl-main)

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Challenge: Existing studies on bridging anaphora resolution focus on question answering based on context . briding anaphorisms and their antecedents are linked via various lexico-semantic, frame or encyclopedic relations.
Approach: They propose a question answering framework for bridging anaphora resolution . they propose briding anaphorisms and their antecedents are linked via various lexico-semantic, frame or encyclopedic relations.
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Attention Focusing for Neural Machine Translation by Bridging Source and Target Embeddings (P18-1)

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Challenge: Neural machine translation uses source and target word embeddings to improve translation quality . source and targeted word embeds are at the two ends of a long information processing procedure .
Approach: They propose a method to shorten the distance between source and target words in neural machine translation by bridging source and targeting word embeddings.
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Bridging Resolution: Making Sense of the State of the Art (2021.naacl-main)

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Challenge: bridging resolution is a task that involves identifying and resolving bridling/associative anaphors, which are anamorphic references to non-identical associated antecedents.
Approach: They propose a hybrid rule-based and MTL approach that would enable a better understanding of their comparative strengths and weaknesses.
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PairSpanBERT: An Enhanced Language Model for Bridging Resolution (2023.acl-long)

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Challenge: bridging resolution is crucial for machine comprehension of discourse entities for various downstream applications.
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Enhancing Word Embeddings with Knowledge Extracted from Lexical Resources (2020.acl-srw)

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Challenge: In this paper, we present an effective method for semantic specialization of word vector representations.
Approach: They propose a method for semantic specialization of word vector representations using BabelNet.
Outcome: The proposed method improves on word similarity and dialog state tracking tasks.
ChEMU-Ref: A Corpus for Modeling Anaphora Resolution in the Chemical Domain (2021.eacl-main)

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Challenge: Using a novel annotation scheme, we identify anaphoric references in chemical patents and determine the chemical relation between linked entities.
Approach: They propose a neural approach to anaphora resolution based on coreference and bridging links in chemical patents.
Outcome: The proposed framework can be used to identify anaphoric references in chemical patents and determine the chemical relation between linked entities.

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