b'Yejin Choi'

research

∙ 10/14/2021

Delphi: Towards Machine Ethics and Norms

What would it take to teach a machine to behave ethically? While broad e...

Liwei Jiang, et al. ∙

research

∙ 10/14/2021

Symbolic Knowledge Distillation: from General Language Models to Commonsense Models

The common practice for training commonsense models has gone from-human-...

Peter West, et al. ∙

research

∙ 09/28/2021

Symbolic Brittleness in Sequence Models: on Systematic Generalization in Symbolic Mathematics

Neural sequence models trained with maximum likelihood estimation have l...

Sean Welleck, et al. ∙

research

∙ 09/17/2021

Conversational Multi-Hop Reasoning with Neural Commonsense Knowledge and Symbolic Logic Rules

One of the challenges faced by conversational agents is their inability ...

Forough Arabshahi, et al. ∙

research

∙ 09/16/2021

Reframing Instructional Prompts to GPTk's Language

How can model designers turn task instructions into effective prompts fo...

Swaroop Mishra, et al. ∙

research

∙ 08/31/2021

It's not Rocket Science : Interpreting Figurative Language in Narratives

Figurative language is ubiquitous in English. Yet, the vast majority of ...

Tuhin Chakrabarty, et al. ∙

research

∙ 07/02/2021

Scarecrow: A Framework for Scrutinizing Machine Text

Modern neural text generation systems can produce remarkably fluent and ...

Yao Dou, et al. ∙

research

∙ 06/15/2021

Divergence Frontiers for Generative Models: Sample Complexity, Quantization Level, and Frontier Integral

The spectacular success of deep generative models calls for quantitative...

Lang Liu, et al. ∙

research

∙ 06/08/2021

TIMEDIAL: Temporal Commonsense Reasoning in Dialog

Everyday conversations require understanding everyday events, which in t...

Lianhui Qin, et al. ∙

research

∙ 06/04/2021

MERLOT: Multimodal Neural Script Knowledge Models

As humans, we understand events in the visual world contextually, perfor...

Rowan Zellers, et al. ∙

research

∙ 06/01/2021

PIGLeT: Language Grounding Through Neuro-Symbolic Interaction in a 3D World

We propose PIGLeT: a model that learns physical commonsense knowledge th...

Rowan Zellers, et al. ∙

research

∙ 05/07/2021

On-the-Fly Controlled Text Generation with Experts and Anti-Experts

Despite recent advances in natural language generation, it remains chall...

Alisa Liu, et al. ∙

research

∙ 04/18/2021

Misinfo Belief Frames: A Case Study on Covid Climate News

Prior beliefs of readers impact the way in which they project meaning on...

Saadia Gabriel, et al. ∙

research

∙ 04/18/2021

CLIPScore: A Reference-free Evaluation Metric for Image Captioning

Image captioning has conventionally relied on reference-based automatic ...

Jack Hessel, et al. ∙

research

∙ 04/16/2021

Surface Form Competition: Why the Highest Probability Answer Isn't Always Right

Large language models have shown promising results in zero-shot settings...

Ari Holtzman, et al. ∙

research

∙ 04/16/2021

proScript: Partially Ordered Scripts Generation via Pre-trained Language Models

Scripts - standardized event sequences describing typical everyday activ...

Keisuke Sakaguchi, et al. ∙

research

∙ 04/13/2021

"I'm Not Mad": Commonsense Implications of Negation and Contradiction

Natural language inference requires reasoning about contradictions, nega...

Liwei Jiang, et al. ∙

research

∙ 03/24/2021

UNICORN on RAINBOW: A Universal Commonsense Reasoning Model on a New Multitask Benchmark

Commonsense AI has long been seen as a near impossible goal – until rece...

Nicholas Lourie, et al. ∙

research

∙ 03/24/2021

NaturalProofs: Mathematical Theorem Proving in Natural Language

Understanding and creating mathematics using natural mathematical langua...

Sean Welleck, et al. ∙

research

∙ 03/02/2021

Contrastive Explanations for Model Interpretability

Contrastive explanations clarify why an event occurred in contrast to an...

Alon Jacovi, et al. ∙

research

∙ 02/02/2021

MAUVE: Human-Machine Divergence Curves for Evaluating Open-Ended Text Generation

Despite major advances in open-ended text generation, there has been lim...

Krishna Pillutla, et al. ∙

research

∙ 02/02/2021

MultiTalk: A Highly-Branching Dialog Testbed for Diverse Conversations

We study conversational dialog in which there are many possible response...

Yao Dou, et al. ∙

research

∙ 01/29/2021

Challenges in Automated Debiasing for Toxic Language Detection

Biased associations have been a challenge in the development of classifi...

Xuhui Zhou, et al. ∙

research

∙ 01/17/2021

GENIE: A Leaderboard for Human-in-the-Loop Evaluation of Text Generation

Leaderboards have eased model development for many NLP datasets by stand...

Daniel Khashabi, et al. ∙

research

∙ 01/02/2021

VinVL: Making Visual Representations Matter in Vision-Language Models

This paper presents a detailed study of improving visual representations...

Pengchuan Zhang, et al. ∙

research

∙ 01/02/2021

On-the-Fly Attention Modularization for Neural Generation

Despite considerable advancements with deep neural language models (LMs)...

Yue Dong, et al. ∙

research

∙ 01/01/2021

Understanding Few-Shot Commonsense Knowledge Models

Providing natural language processing systems with commonsense knowledge...

Jeff Da, et al. ∙

research

∙ 12/31/2020

Moral Stories: Situated Reasoning about Norms, Intents, Actions, and their Consequences

In social settings, much of human behavior is governed by unspoken rules...

Denis Emelin, et al. ∙

research

∙ 12/14/2020

Learning to Rationalize for Nonmonotonic Reasoning with Distant Supervision

The black-box nature of neural models has motivated a line of research t...

Faeze Brahman, et al. ∙

research

∙ 12/08/2020

Edited Media Understanding: Reasoning About Implications of Manipulated Images

Multimodal disinformation, from `deepfakes' to simple edits that deceive...

Jeff Da, et al. ∙

research

∙ 11/01/2020

Social Chemistry 101: Learning to Reason about Social and Moral Norms

Social norms—the unspoken commonsense rules about acceptable social beha...

Maxwell Forbes, et al. ∙

research

∙ 10/26/2020

PowerTransformer: Unsupervised Controllable Revision for Biased Language Correction

Unconscious biases continue to be prevalent in modern text and media, ca...

Xinyao Ma, et al. ∙

research

∙ 10/24/2020

NeuroLogic Decoding: (Un)supervised Neural Text Generation with Predicate Logic Constraints

Conditional text generation often requires lexical constraints, i.e., wh...

Ximing Lu, et al. ∙

research

∙ 10/24/2020

Go Figure! A Meta Evaluation of Factuality in Summarization

Text generation models can generate factually inconsistent text containi...

Saadia Gabriel, et al. ∙

research

∙ 10/16/2020

Reflective Decoding: Unsupervised Paraphrasing and Abductive Reasoning

Pretrained Language Models (LMs) generate text with remarkable quality, ...

Peter West, et al. ∙

research

∙ 10/15/2020

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...

Ana Marasović, et al. ∙

research

∙ 10/12/2020

COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge Graphs

Recent years have brought about a renewed interest in commonsense repres...

Jena D. Hwang, et al. ∙

research

∙ 10/12/2020

Back to the Future: Unsupervised Backprop-based Decoding for Counterfactual and Abductive Commonsense Reasoning

Abductive and counterfactual reasoning, core abilities of everyday human...

Lianhui Qin, et al. ∙

research

∙ 10/04/2020

Paragraph-Level Commonsense Transformers with Recurrent Memory

Human understanding of narrative texts requires making commonsense infer...

Saadia Gabriel, et al. ∙

research

∙ 09/24/2020

RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models

Pretrained neural language models (LMs) are prone to generating racist, ...

Samuel Gehman, et al. ∙

research

∙ 08/20/2020

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...

Nicholas Lourie, et al. ∙

research

∙ 04/30/2020

PlotMachines: Outline-Conditioned Generation with Dynamic Plot State Tracking

We propose the task of outline-conditioned story generation: given an ou...

Hannah Rashkin, et al. ∙

research

∙ 04/24/2020

G-DAUG: Generative Data Augmentation for Commonsense Reasoning

Recent advances in commonsense reasoning depend on large-scale human-ann...

Yiben Yang, et al. ∙

research

∙ 04/22/2020

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...

Jae Sung Park, et al. ∙

research

∙ 04/13/2020

Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks

Large-scale pre-training methods of learning cross-modal representations...

Xiujun Li, et al. ∙

research

∙ 04/11/2020

Unsupervised Commonsense Question Answering with Self-Talk

Natural language understanding involves reading between the lines with i...

Vered Shwartz, et al. ∙

research

∙ 04/07/2020

Evaluating Machines by their Real-World Language Use

There is a fundamental gap between how humans understand and use languag...

Rowan Zellers, et al. ∙

research

∙ 03/31/2020

Procedural Reading Comprehension with Attribute-Aware Context Flow

Procedural texts often describe processes (e.g., photosynthesis and cook...

Aida Amini, et al. ∙

research

∙ 03/02/2020

Multi-View Learning for Vision-and-Language Navigation

Learning to navigate in a visual environment following natural language ...

Qiaolin Xia, et al. ∙

research

∙ 02/10/2020

Adversarial Filters of Dataset Biases

Large neural models have demonstrated human-level performance on languag...

Ronan Le Bras, et al. ∙

Yejin Choi

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