Antoine Bosselut

research

∙ 05/28/2023

Mitigating Label Biases for In-context Learning

Various design settings for in-context learning (ICL), such as the choic...

0 Yu Fei, et al. ∙

research

∙ 05/10/2023

RECKONING: Reasoning through Dynamic Knowledge Encoding

Recent studies on transformer-based language models show that they can a...

0 Zeming Chen, et al. ∙

research

∙ 05/03/2023

PeaCoK: Persona Commonsense Knowledge for Consistent and Engaging Narratives

Sustaining coherent and engaging narratives requires dialogue or storyte...

0 Silin Gao, et al. ∙

research

∙ 04/04/2023

REFINER: Reasoning Feedback on Intermediate Representations

Language models (LMs) have recently shown remarkable performance on reas...

3 Debjit Paul, et al. ∙

research

∙ 12/20/2022

DISCO: Distilling Phrasal Counterfactuals with Large Language Models

Recent methods demonstrate that data augmentation using counterfactual k...

0 Zeming Chen, et al. ∙

research

∙ 11/15/2022

kogito: A Commonsense Knowledge Inference Toolkit

In this paper, we present kogito, an open-source tool for generating com...

0 Mete Ismayilzada, et al. ∙

research

∙ 10/23/2022

ComFact: A Benchmark for Linking Contextual Commonsense Knowledge

Understanding rich narratives, such as dialogues and stories, often requ...

0 Silin Gao, et al. ∙

research

∙ 10/17/2022

Deep Bidirectional Language-Knowledge Graph Pretraining

Pretraining a language model (LM) on text has been shown to help various...

4 Michihiro Yasunaga, et al. ∙

research

∙ 06/13/2022

Memory-Based Model Editing at Scale

Even the largest neural networks make errors, and once-correct predictio...

8 Eric Mitchell, et al. ∙

research

∙ 05/25/2022

Discovering Language-neutral Sub-networks in Multilingual Language Models

Multilingual pre-trained language models perform remarkably well on cros...

0 Negar Foroutan, et al. ∙

research

∙ 05/25/2022

Conditional set generation using Seq2seq models

Conditional set generation learns a mapping from an input sequence of to...

0 Aman Madaan, et al. ∙

research

∙ 02/18/2022

Synthetic Disinformation Attacks on Automated Fact Verification Systems

Automated fact-checking is a needed technology to curtail the spread of ...

0 Yibing Du, et al. ∙

research

∙ 01/21/2022

GreaseLM: Graph REASoning Enhanced Language Models for Question Answering

Answering complex questions about textual narratives requires reasoning ...

1 Xikun Zhang, et al. ∙

research

∙ 10/21/2021

Fast Model Editing at Scale

While large pre-trained models have enabled impressive results on a vari...

16 Eric Mitchell, 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 ...

8 Forough Arabshahi, et al. ∙

research

∙ 04/13/2021

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

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

0 Liwei Jiang, et al. ∙

research

∙ 04/13/2021

QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering

The problem of answering questions using knowledge from pre-trained lang...

15 Michihiro Yasunaga, et al. ∙

research

∙ 02/02/2021

The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics

We introduce GEM, a living benchmark for natural language Generation (NL...

5 Sebastian Gehrmann, et al. ∙

research

∙ 01/02/2021

On-the-Fly Attention Modularization for Neural Generation

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

0 Yue Dong, et al. ∙

research

∙ 01/01/2021

Understanding Few-Shot Commonsense Knowledge Models

Providing natural language processing systems with commonsense knowledge...

0 Jeff Da, et al. ∙

research

∙ 12/08/2020

Edited Media Understanding: Reasoning About Implications of Manipulated Images

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

0 Jeff Da, 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...

0 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...

0 Lianhui Qin, et al. ∙

research

∙ 03/31/2020

Procedural Reading Comprehension with Attribute-Aware Context Flow

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

0 Aida Amini, et al. ∙

research

∙ 11/10/2019

Dynamic Knowledge Graph Construction for Zero-shot Commonsense Question Answering

Understanding narratives requires dynamically reasoning about the implic...

0 Antoine Bosselut, et al. ∙

research

∙ 10/07/2019

Exploiting Structural and Semantic Context for Commonsense Knowledge Base Completion

Automatic KB completion for commonsense knowledge graphs (e.g., ATOMIC a...

11 Chaitanya Malaviya, et al. ∙

research

∙ 09/10/2019

Everything Happens for a Reason: Discovering the Purpose of Actions in Procedural Text

Our goal is to better comprehend procedural text, e.g., a paragraph abou...

0 Bhavana Dalvi Mishra, et al. ∙

research

∙ 09/10/2019

WIQA: A dataset for "What if..." reasoning over procedural text

We introduce WIQA, the first large-scale dataset of "What if..." questio...

0 Niket Tandon, et al. ∙

research

∙ 09/09/2019

Counterfactual Story Reasoning and Generation

Counterfactual reasoning requires predicting how alternative events, con...

0 Lianhui Qin, et al. ∙

research

∙ 07/02/2019

Cooperative Generator-Discriminator Networks for Abstractive Summarization with Narrative Flow

We introduce Cooperative Generator-Discriminator Networks (Co-opNet), a ...

0 Saadia Gabriel, et al. ∙

research

∙ 06/21/2019

Be Consistent! Improving Procedural Text Comprehension using Label Consistency

Our goal is procedural text comprehension, namely tracking how the prope...

0 Xinya Du, et al. ∙

research

∙ 06/12/2019

COMET: Commonsense Transformers for Automatic Knowledge Graph Construction

We present the first comprehensive study on automatic knowledge base con...

25 Antoine Bosselut, et al. ∙

research

∙ 06/01/2019

Efficient Adaptation of Pretrained Transformers for Abstractive Summarization

Large-scale learning of transformer language models has yielded improvem...

0 Andrew Hoang, et al. ∙

research

∙ 08/29/2018

Reasoning about Actions and State Changes by Injecting Commonsense Knowledge

Comprehending procedural text, e.g., a paragraph describing photosynthes...

0 Niket Tandon, et al. ∙

research

∙ 05/16/2018

Modeling Naive Psychology of Characters in Simple Commonsense Stories

Understanding a narrative requires reading between the lines and reasoni...

1 Hannah Rashkin, et al. ∙

research

∙ 05/16/2018

Learning to Write with Cooperative Discriminators

Recurrent Neural Networks (RNNs) are powerful autoregressive sequence mo...

0 Ari Holtzman, et al. ∙

research

∙ 05/10/2018

Discourse-Aware Neural Rewards for Coherent Text Generation

In this paper, we investigate the use of discourse-aware rewards with re...

0 Antoine Bosselut, et al. ∙

research

∙ 03/27/2018

Deep Communicating Agents for Abstractive Summarization

We present deep communicating agents in an encoder-decoder architecture ...

0 Asli Celikyilmaz, et al. ∙

research

∙ 11/14/2017

Simulating Action Dynamics with Neural Process Networks

Understanding procedural language requires anticipating the causal effec...

0 Antoine Bosselut, et al. ∙

Antoine Bosselut

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