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1
FastIF: Scalable Influence Functions for Efficient Model Interpretation and Debugging ...
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2
ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning ...
Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.609/ Abstract: Recent commonsense-reasoning tasks are typically discriminative in nature, where a model answers a multiple-choice question for a certain context. Discriminative tasks are limiting because they fail to adequately evaluate the model's ability to reason and explain predictions with underlying commonsense knowledge. They also allow such models to use reasoning shortcuts and not be "right for the right reasons". In this work, we present ExplaGraphs, a new generative and structured commonsense-reasoning task (and an associated dataset) of explanation graph generation for stance prediction. Specifically, given a belief and an argument, a model has to predict if the argument supports or counters the belief and also generate a commonsense-augmented graph that serves as non-trivial, complete, and unambiguous explanation for the predicted stance. We collect explanation graphs through a novel Create-Verify-And-Refine graph collection ...
Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing
URL: https://dx.doi.org/10.48448/xpfc-9497
https://underline.io/lecture/37914-explagraphs-an-explanation-graph-generation-task-for-structured-commonsense-reasoning
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3
EmailSum: Abstractive Email Thread Summarization ...
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4
Inducing Transformer’s Compositional Generalization Ability via Auxiliary Sequence Prediction Tasks ...
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5
I like fish, especially dolphins: Addressing Contradictions in Dialogue Modeling ...
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6
InfoSurgeon: Cross-Media Fine-grained Information Consistency Checking for Fake News Detection ...
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7
Continuous Language Generative Flow ...
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8
ChrEnTranslate: Cherokee-English Machine Translation Demo with Quality Estimation and Corrective Feedback ...
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9
Integrating Visuospatial, Linguistic, and Commonsense Structure into Story Visualization ...
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10
Summary-Source Proposition-level Alignment: Task, Datasets and Supervised Baseline ...
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11
Continual Few-Shot Learning for Text Classification ...
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12
Finding a Balanced Degree of Automation for Summary Evaluation ...
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13
Analysis of Tree-Structured Architectures for Code Generation ...
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14
Simple, accurate parsing with an all-fragments grammar
In: Association for Computational Linguistics. Proceedings of the conference. - Stroudsburg, Penn. : ACL 48 (2010) 2, 1098-1107
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