b'Dipanjan Das'

research

∙ 05/22/2023

SEAHORSE: A Multilingual, Multifaceted Dataset for Summarization Evaluation

Reliable automatic evaluation of summarization systems is challenging du...

0 Elizabeth Clark, et al. ∙

research

∙ 04/28/2023

Text-Blueprint: An Interactive Platform for Plan-based Conditional Generation

While conditional generation models can now generate natural language we...

0 Fantine Huot, et al. ∙

research

∙ 02/17/2023

Columbus: Android App Testing Through Systematic Callback Exploration

With the continuous rise in the popularity of Android mobile devices, au...

0 Priyanka Bose, et al. ∙

research

∙ 01/24/2023

Demystifying NFT Promotion and Phishing Scams

The popularity and hype around purchasing digital assets such as art, vi...

0 Sayak Saha Roy, et al. ∙

research

∙ 11/15/2022

QAmeleon: Multilingual QA with Only 5 Examples

The availability of large, high-quality datasets has been one of the mai...

0 Priyanka Agrawal, et al. ∙

research

∙ 10/31/2022

Query Refinement Prompts for Closed-Book Long-Form Question Answering

Large language models (LLMs) have been shown to perform well in answerin...

0 Reinald Kim Amplayo, et al. ∙

research

∙ 10/06/2022

Language Models are Multilingual Chain-of-Thought Reasoners

We evaluate the reasoning abilities of large language models in multilin...

0 Freda Shi, et al. ∙

research

∙ 07/01/2022

Conditional Generation with a Question-Answering Blueprint

The ability to convey relevant and faithful information is critical for ...

0 Shashi Narayan, et al. ∙

research

∙ 03/28/2022

A Well-Composed Text is Half Done! Composition Sampling for Diverse Conditional Generation

We propose Composition Sampling, a simple but effective method to genera...

0 Shashi Narayan, et al. ∙

research

∙ 12/23/2021

Measuring Attribution in Natural Language Generation Models

With recent improvements in natural language generation (NLG) models for...

9 Hannah Rashkin, et al. ∙

research

∙ 11/17/2021

Understanding Security Issues in the NFT Ecosystem

Non-Fungible Tokens (NFTs) have emerged as a way to collect digital art ...

0 Dipanjan Das, et al. ∙

research

∙ 07/14/2021

Increasing Faithfulness in Knowledge-Grounded Dialogue with Controllable Features

Knowledge-grounded dialogue systems are intended to convey information t...

0 Hannah Rashkin, et al. ∙

research

∙ 06/30/2021

The MultiBERTs: BERT Reproductions for Robustness Analysis

Experiments with pretrained models such as BERT are often based on a sin...

0 Thibault Sellam, et al. ∙

research

∙ 02/09/2021

Decontextualization: Making Sentences Stand-Alone

Models for question answering, dialogue agents, and summarization often ...

7 Eunsol Choi, 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

∙ 10/08/2020

Learning to Evaluate Translation Beyond English: BLEURT Submissions to the WMT Metrics 2020 Shared Task

The quality of machine translation systems has dramatically improved ove...

0 Thibault Sellam, et al. ∙

research

∙ 05/10/2020

Variational Clustering: Leveraging Variational Autoencoders for Image Clustering

Recent advances in deep learning have shown their ability to learn stron...

42 Vignesh Prasad, et al. ∙

research

∙ 04/29/2020

ToTTo: A Controlled Table-To-Text Generation Dataset

We present ToTTo, an open-domain English table-to-text dataset with over...

0 Ankur P. Parikh, et al. ∙

research

∙ 04/24/2020

Syntactic Data Augmentation Increases Robustness to Inference Heuristics

Pretrained neural models such as BERT, when fine-tuned to perform natura...

0 Junghyun Min, et al. ∙

research

∙ 04/09/2020

BLEURT: Learning Robust Metrics for Text Generation

Text generation has made significant advances in the last few years. Yet...

0 Thibault Sellam, et al. ∙

research

∙ 06/03/2019

Handling Divergent Reference Texts when Evaluating Table-to-Text Generation

Automatically constructed datasets for generating text from semi-structu...

0 Bhuwan Dhingra, et al. ∙

research

∙ 05/15/2019

What do you learn from context? Probing for sentence structure in contextualized word representations

Contextualized representation models such as ELMo (Peters et al., 2018a)...

0 Ian Tenney, et al. ∙

research

∙ 05/15/2019

BERT Rediscovers the Classical NLP Pipeline

Pre-trained text encoders have rapidly advanced the state of the art on ...

0 Ian Tenney, et al. ∙

research

∙ 04/09/2019

Text Generation with Exemplar-based Adaptive Decoding

We propose a novel conditioned text generation model. It draws inspirati...

0 Hao Peng, et al. ∙

research

∙ 01/19/2019

Deep Representation Learning Characterized by Inter-class Separation for Image Clustering

Despite significant advances in clustering methods in recent years, the ...

0 Dipanjan Das, et al. ∙

research

∙ 12/23/2018

Epipolar Geometry based Learning of Multi-view Depth and Ego-Motion from Monocular Sequences

Deep approaches to predict monocular depth and ego-motion have grown in ...

0 Vignesh Prasad, et al. ∙

research

∙ 08/28/2018

Learning To Split and Rephrase From Wikipedia Edit History

Split and rephrase is the task of breaking down a sentence into shorter ...

0 Jan A. Botha, et al. ∙

research

∙ 08/28/2018

WikiAtomicEdits: A Multilingual Corpus of Wikipedia Edits for Modeling Language and Discourse

We release a corpus of 43 million atomic edits across 8 languages. These...

0 Manaal Faruqui, et al. ∙

research

∙ 08/28/2018

Identifying Well-formed Natural Language Questions

Understanding search queries is a hard problem as it involves dealing wi...

0 Manaal Faruqui, et al. ∙

research

∙ 04/15/2017

Neural Paraphrase Identification of Questions with Noisy Pretraining

We present a solution to the problem of paraphrase identification of que...

0 Gaurav Singh Tomar, et al. ∙

research

∙ 11/04/2016

Learning Recurrent Span Representations for Extractive Question Answering

The reading comprehension task, that asks questions about a given eviden...

0 Kenton Lee, et al. ∙

research

∙ 06/06/2016

A Decomposable Attention Model for Natural Language Inference

We propose a simple neural architecture for natural language inference. ...

0 Ankur P. Parikh, et al. ∙

Dipanjan Das

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