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1906.02361
Cited By
Explain Yourself! Leveraging Language Models for Commonsense Reasoning
6 June 2019
Nazneen Rajani
Bryan McCann
Caiming Xiong
R. Socher
ReLM
LRM
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Papers citing
"Explain Yourself! Leveraging Language Models for Commonsense Reasoning"
50 / 399 papers shown
Title
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Re-Examining Human Annotations for Interpretable NLP
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Can language models learn from explanations in context?
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Stephanie C. Y. Chan
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Jane X. Wang
Felix Hill
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188
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Interpretation of Black Box NLP Models: A Survey
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N. Chatterjee
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STaR: Bootstrapping Reasoning With Reasoning
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Jesse Mu
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157
512
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elBERto: Self-supervised Commonsense Learning for Question Answering
Xunlin Zhan
Yuan Li
Xiao Dong
Xiaodan Liang
Zhiting Hu
Lawrence Carin
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77
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E-KAR: A Benchmark for Rationalizing Natural Language Analogical Reasoning
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Rui Xu
Ziquan Fu
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108
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NLX-GPT: A Model for Natural Language Explanations in Vision and Vision-Language Tasks
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Nikos Deligiannis
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An Empirical Study on Explanations in Out-of-Domain Settings
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CAKE: A Scalable Commonsense-Aware Framework For Multi-View Knowledge Graph Completion
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Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
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Natural Language Descriptions of Deep Visual Features
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Sarah Schwettmann
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Jacob Andreas
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313
126
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26 Jan 2022
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI
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Jan Trienes
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Yasmin Schmitt
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178
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COPA-SSE: Semi-structured Explanations for Commonsense Reasoning
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Grow-and-Clip: Informative-yet-Concise Evidence Distillation for Answer Explanation
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UNIREX: A Unified Learning Framework for Language Model Rationale Extraction
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Hamed Firooz
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Reframing Human-AI Collaboration for Generating Free-Text Explanations
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Mark O. Riedl
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DREAM: Improving Situational QA by First Elaborating the Situation
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Bhavana Dalvi
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KGR^4: Retrieval, Retrospect, Refine and Rethink for Commonsense Generation
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Dayiheng Liu
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Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations in a Label-Abundant Setup
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Explainable Deep Learning in Healthcare: A Methodological Survey from an Attribution View
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Few-Shot Self-Rationalization with Natural Language Prompts
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Iz Beltagy
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"How Does It Detect A Malicious App?" Explaining the Predictions of AI-based Android Malware Detector
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Interpreting Deep Learning Models in Natural Language Processing: A Review
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Think Before You Speak: Explicitly Generating Implicit Commonsense Knowledge for Response Generation
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Generated Knowledge Prompting for Commonsense Reasoning
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Combining Transformers with Natural Language Explanations
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iReason: Multimodal Commonsense Reasoning using Videos and Natural Language with Interpretability
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