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WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation ...
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Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detection ...
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Specializing Multilingual Language Models: An Empirical Study ...
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Provable Limitations of Acquiring Meaning from Ungrounded Form: What will Future Language Models Understand? ...
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Measuring Association Between Labels and Free-Text Rationales ...
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Promoting Graph Awareness in Linearized Graph-to-Text Generation ...
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Challenges in Automated Debiasing for Toxic Language Detection ...
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NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristics ...
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Effects of Parameter Norm Growth During Transformer Training: Inductive Bias from Gradient Descent ...
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Competency Problems: On Finding and Removing Artifacts in Language Data ...
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Extracting and Inferring Personal Attributes from Dialogue
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Abstract:
Thesis (Master's)--University of Washington, 2021 ; Personal attributes represent structured information about a person, such as their hobbies, pets, family, likes and dislikes. In this work, we introduce the tasks of extracting and inferring personal attributes from human-human dialogue. We first demonstrate the benefit of incorporating personal attributes in a social chit-chat dialogue model and task-oriented dialogue setting. Thus motivated, we propose the tasks of personal attribute extraction and inference, and then analyze the linguistic demands of these tasks. To meet these challenges, we introduce a simple and extensible model that combines an autoregressive language model utilizing constrained attribute generation with a discriminative reranker. Our model outperforms strong baselines on extracting personal attributes as well as inferring personal attributes that are not contained verbatim in utterances and instead requires commonsense reasoning and lexical inferences, which occur frequently in everyday conversation.
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Keyword:
Artificial intelligence; Linguistics
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URL: http://hdl.handle.net/1773/48052
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Semantic Comparisons for Natural Language Processing Applications
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Challenges in Automated Debiasing for Toxic Language Detection
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Parsing with Multilingual BERT, a Small Corpus, and a Small Treebank ...
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Unsupervised Bitext Mining and Translation via Self-trained Contextual Embeddings ...
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Evaluating Models' Local Decision Boundaries via Contrast Sets ...
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Grounded Compositional Outputs for Adaptive Language Modeling ...
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