Nazneen Fatema Rajani | DeepAI

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∙ 10/14/2021

MoFE: Mixture of Factual Experts for Controlling Hallucinations in Abstractive Summarization

Neural abstractive summarization models are susceptible to generating fa...

5 Prafulla Kumar Choubey, et al. ∙

∙ 10/08/2021

HydraSum – Disentangling Stylistic Features in Text Summarization using Multi-Decoder Models

Existing abstractive summarization models lack explicit control mechanis...

0 Tanya Goyal, et al. ∙

∙ 04/15/2021

SummVis: Interactive Visual Analysis of Models, Data, and Evaluation for Text Summarization

Novel neural architectures, training strategies, and the availability of...

21 Jesse Vig, et al. ∙

∙ 12/31/2020

FastIF: Scalable Influence Functions for Efficient Model Interpretation and Debugging

Influence functions approximate the 'influences' of training data-points...

9 Han Guo, et al. ∙

∙ 12/01/2020

Profile Prediction: An Alignment-Based Pre-Training Task for Protein Sequence Models

For protein sequence datasets, unlabeled data has greatly outpaced label...

6 Pascal Sturmfels, et al. ∙

∙ 10/18/2020

Explaining and Improving Model Behavior with k Nearest Neighbor Representations

Interpretability techniques in NLP have mainly focused on understanding ...

0 Nazneen Fatema Rajani, et al. ∙

∙ 10/14/2020

Explaining Creative Artifacts

Human creativity is often described as the mental process of combining a...

0 Lav R. Varshney, et al. ∙

∙ 10/13/2020

ReviewRobot: Explainable Paper Review Generation based on Knowledge Synthesis

To assist human review process, we build a novel ReviewRobot to automati...

0 Qingyun Wang, et al. ∙

∙ 10/06/2020

Universal Natural Language Processing with Limited Annotations: Try Few-shot Textual Entailment as a Start

A standard way to address different NLP problems is by first constructin...

0 Wenpeng Yin, et al. ∙

∙ 09/14/2020

GeDi: Generative Discriminator Guided Sequence Generation

Class-conditional language models (CC-LMs) can be used to generate natur...

0 Ben Krause, et al. ∙

∙ 07/06/2020

DART: Open-Domain Structured Data Record to Text Generation

We introduce DART, a large dataset for open-domain structured data recor...

0 Dragomir Radev, et al. ∙

∙ 06/26/2020

BERTology Meets Biology: Interpreting Attention in Protein Language Models

Transformer architectures have proven to learn useful representations fo...

0 Jesse Vig, et al. ∙

∙ 05/03/2020

Double-Hard Debias: Tailoring Word Embeddings for Gender Bias Mitigation

Word embeddings derived from human-generated corpora inherit strong gend...

0 Tianlu Wang, et al. ∙

∙ 05/02/2020

ESPRIT: Explaining Solutions to Physical Reasoning Tasks

Neural networks lack the ability to reason about qualitative physics and...

0 Nazneen Fatema Rajani, et al. ∙

∙ 11/08/2019

ERASER: A Benchmark to Evaluate Rationalized NLP Models

State-of-the-art models in NLP are now predominantly based on deep neura...

35 Jay DeYoung, et al. ∙

∙ 06/06/2019

Explain Yourself! Leveraging Language Models for Commonsense Reasoning

Deep learning models perform poorly on tasks that require commonsense re...

0 Nazneen Fatema Rajani, et al. ∙

∙ 05/27/2016

Stacking With Auxiliary Features

Ensembling methods are well known for improving prediction accuracy. How...

0 Nazneen Fatema Rajani, et al. ∙

∙ 04/16/2016

Supervised and Unsupervised Ensembling for Knowledge Base Population

We present results on combining supervised and unsupervised methods to e...

0 Nazneen Fatema Rajani, et al. ∙

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