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Looking for Confirmations: An Effective and Human-Like Visual Dialogue Strategy ...
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CrossVQA: Scalably Generating Benchmarks for Systematically Testing VQA Generalization ...
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Latent Hatred: A Benchmark for Understanding Implicit Hate Speech ...
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STaCK: Sentence Ordering with Temporal Commonsense Knowledge ...
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ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning ...
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Weakly supervised discourse segmentation for multiparty oral conversations ...
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Searching for an Effective Defender: Benchmarking Defense against Adversarial Word Substitution ...
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Progressively Guide to Attend: An Iterative Alignment Framework for Temporal Sentence Grounding ...
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Knowledge Enhanced Fine-Tuning for Better Handling Unseen Entities in Dialogue Generation ...
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STANKER: Stacking Network based on Level-grained Attention-masked BERT for Rumor Detection on Social Media ...
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IndoNLG: Benchmark and Resources for Evaluating Indonesian Natural Language Generation ...
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SYSML: StYlometry with Structure and Multitask Learning: Implications for Darknet Forum Migrant Analysis ...
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Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes ...
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Abstract:
Anthology paper link: https://aclanthology.org/2021.emnlp-main.170/ Abstract: Empathy is a complex cognitive ability based on the reasoning of others' affective states. In order to better understand others and express stronger empathy in dialogues, we argue that two issues must be tackled at the same time: (i) identifying which word is the cause for the other's emotion from his or her utterance and (ii) reflecting those specific words in the response generation. However, previous approaches for recognizing emotion cause words in text require sub-utterance level annotations, which can be demanding. Taking inspiration from social cognition, we leverage a generative estimator to infer emotion cause words from utterances with no word-level label. Also, we introduce a novel method based on pragmatics to make dialogue models focus on targeted words in the input during generation. Our method is applicable to any dialogue models with no additional training on the fly. We show our approach improves multiple ...
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Keyword:
Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing
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URL: https://underline.io/lecture/37336-perspective-taking-and-pragmatics-for-generating-empathetic-responses-focused-on-emotion-causes https://dx.doi.org/10.48448/wj6y-vr17
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Wikily Supervised Neural Translation Tailored to Cross-Lingual Tasks ...
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