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MAUVE: Human-Machine Divergence Curves for Evaluating Open-Ended Text Generation
Despite major advances in open-ended text generation, there has been lim...
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MultiTalk: A Highly-Branching Dialog Testbed for Diverse Conversations
We study conversational dialog in which there are many possible response...
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Challenges in Automated Debiasing for Toxic Language Detection
Biased associations have been a challenge in the development of classifi...
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GENIE: A Leaderboard for Human-in-the-Loop Evaluation of Text Generation
Leaderboards have eased model development for many NLP datasets by stand...
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VinVL: Making Visual Representations Matter in Vision-Language Models
This paper presents a detailed study of improving visual representations...
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On-the-Fly Attention Modularization for Neural Generation
Despite considerable advancements with deep neural language models (LMs)...
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Understanding Few-Shot Commonsense Knowledge Models
Providing natural language processing systems with commonsense knowledge...
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Moral Stories: Situated Reasoning about Norms, Intents, Actions, and their Consequences
In social settings, much of human behavior is governed by unspoken rules...
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Learning to Rationalize for Nonmonotonic Reasoning with Distant Supervision
The black-box nature of neural models has motivated a line of research t...
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Edited Media Understanding: Reasoning About Implications of Manipulated Images
Multimodal disinformation, from `deepfakes' to simple edits that deceive...
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Social Chemistry 101: Learning to Reason about Social and Moral Norms
Social norms—the unspoken commonsense rules about acceptable social beha...
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PowerTransformer: Unsupervised Controllable Revision for Biased Language Correction
Unconscious biases continue to be prevalent in modern text and media, ca...
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NeuroLogic Decoding: (Un)supervised Neural Text Generation with Predicate Logic Constraints
Conditional text generation often requires lexical constraints, i.e., wh...
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Go Figure! A Meta Evaluation of Factuality in Summarization
Text generation models can generate factually inconsistent text containi...
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Reflective Decoding: Unsupervised Paraphrasing and Abductive Reasoning
Pretrained Language Models (LMs) generate text with remarkable quality, ...
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Natural Language Rationales with Full-Stack Visual Reasoning: From Pixels to Semantic Frames to Commonsense Graphs
Natural language rationales could provide intuitive, higher-level explan...
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COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge Graphs
Recent years have brought about a renewed interest in commonsense repres...
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Back to the Future: Unsupervised Backprop-based Decoding for Counterfactual and Abductive Commonsense Reasoning
Abductive and counterfactual reasoning, core abilities of everyday human...
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Paragraph-Level Commonsense Transformers with Recurrent Memory
Human understanding of narrative texts requires making commonsense infer...
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RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models
Pretrained neural language models (LMs) are prone to generating racist, ...
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Scruples: A Corpus of Community Ethical Judgments on 32,000 Real-Life Anecdotes
As AI systems become an increasing part of people's everyday lives, it b...
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PlotMachines: Outline-Conditioned Generation with Dynamic Plot State Tracking
We propose the task of outline-conditioned story generation: given an ou...
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G-DAUG: Generative Data Augmentation for Commonsense Reasoning
Recent advances in commonsense reasoning depend on large-scale human-ann...
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Visual Commonsense Graphs: Reasoning about the Dynamic Context of a Still Image
Even from a single frame of a still image, people can reason about the d...
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Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks
Large-scale pre-training methods of learning cross-modal representations...
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Unsupervised Commonsense Question Answering with Self-Talk
Natural language understanding involves reading between the lines with i...
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Evaluating Machines by their Real-World Language Use
There is a fundamental gap between how humans understand and use languag...
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Procedural Reading Comprehension with Attribute-Aware Context Flow
Procedural texts often describe processes (e.g., photosynthesis and cook...
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Multi-View Learning for Vision-and-Language Navigation
Learning to navigate in a visual environment following natural language ...
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Adversarial Filters of Dataset Biases
Large neural models have demonstrated human-level performance on languag...
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PIQA: Reasoning about Physical Commonsense in Natural Language
To apply eyeshadow without a brush, should I use a cotton swab or a toot...
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Social Bias Frames: Reasoning about Social and Power Implications of Language
Language has the power to reinforce stereotypes and project social biase...
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Dynamic Knowledge Graph Construction for Zero-shot Commonsense Question Answering
Understanding narratives requires dynamically reasoning about the implic...
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Exploiting Structural and Semantic Context for Commonsense Knowledge Base Completion
Automatic KB completion for commonsense knowledge graphs (e.g., ATOMIC a...
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BottleSum: Unsupervised and Self-supervised Sentence Summarization using the Information Bottleneck Principle
The principle of the Information Bottleneck (Tishby et al. 1999) is to p...
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Counterfactual Story Reasoning and Generation
Counterfactual reasoning requires predicting how alternative events, con...
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Robust Navigation with Language Pretraining and Stochastic Sampling
Core to the vision-and-language navigation (VLN) challenge is building r...
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Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning
Understanding narratives requires reading between the lines, which in tu...
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Abductive Commonsense Reasoning
Abductive reasoning is inference to the most plausible explanation. For ...
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Do Neural Language Representations Learn Physical Commonsense?
Humans understand language based on the rich background knowledge about ...
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WINOGRANDE: An Adversarial Winograd Schema Challenge at Scale
The Winograd Schema Challenge (WSC), proposed by Levesque et al. (2011) ...
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Cooperative Generator-Discriminator Networks for Abstractive Summarization with Narrative Flow
We introduce Cooperative Generator-Discriminator Networks (Co-opNet), a ...
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COMET: Commonsense Transformers for Automatic Knowledge Graph Construction
We present the first comprehensive study on automatic knowledge base con...
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Conversing by Reading: Contentful Neural Conversation with On-demand Machine Reading
Although neural conversation models are effective in learning how to pro...
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Efficient Adaptation of Pretrained Transformers for Abstractive Summarization
Large-scale learning of transformer language models has yielded improvem...
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MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms
We introduce a large-scale dataset of math word problems and an interpre...
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Defending Against Neural Fake News
Recent progress in natural language generation has raised dual-use conce...
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HellaSwag: Can a Machine Really Finish Your Sentence?
Recent work by Zellers et al. (2018) introduced a new task of commonsens...
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The Curious Case of Neural Text Degeneration
Despite considerable advancements with deep neural language models, the ...
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SocialIQA: Commonsense Reasoning about Social Interactions
We introduce SocialIQa, the first large-scale benchmark for commonsense ...
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