b'Siva Reddy'

research

∙ 06/08/2022

Few-shot Question Generation for Personalized Feedback in Intelligent Tutoring Systems

Existing work on generating hints in Intelligent Tutoring Systems (ITS) ...

Devang Kulshreshtha, et al. ∙

research

∙ 04/22/2022

FaithDial: A Faithful Benchmark for Information-Seeking Dialogue

The goal of information-seeking dialogue is to respond to seeker queries...

Nouha Dziri, et al. ∙

research

∙ 04/17/2022

On the Origin of Hallucinations in Conversational Models: Is it the Datasets or the Models?

Knowledge-grounded conversational models are known to suffer from produc...

Nouha Dziri, et al. ∙

research

∙ 04/06/2022

Using Interactive Feedback to Improve the Accuracy and Explainability of Question Answering Systems Post-Deployment

Most research on question answering focuses on the pre-deployment stage;...

Zichao Li, et al. ∙

research

∙ 03/29/2022

Image Retrieval from Contextual Descriptions

The ability to integrate context, including perceptual and temporal cues...

Benno Krojer, et al. ∙

research

∙ 02/28/2022

Combining Modular Skills in Multitask Learning

A modular design encourages neural models to disentangle and recombine d...

Edoardo M. Ponti, et al. ∙

research

∙ 01/05/2022

Does entity abstraction help generative Transformers reason?

Pre-trained language models (LMs) often struggle to reason logically or ...

Nicolas Gontier, et al. ∙

research

∙ 10/16/2021

An Empirical Survey of the Effectiveness of Debiasing Techniques for Pre-Trained Language Models

Recent work has shown that pre-trained language models capture social bi...

Nicholas Meade, et al. ∙

research

∙ 10/16/2021

The Power of Prompt Tuning for Low-Resource Semantic Parsing

Prompt tuning has recently emerged as an effective method for adapting p...

Nathan Schucher, et al. ∙

research

∙ 10/15/2021

Evaluating the Faithfulness of Importance Measures in NLP by Recursively Masking Allegedly Important Tokens and Retraining

To explain NLP models, many methods inform which inputs tokens are impor...

Andreas Madsen, et al. ∙

research

∙ 10/13/2021

Compositional Generalization in Dependency Parsing

Compositionality, or the ability to combine familiar units like words in...

Emily Goodwin, et al. ∙

research

∙ 10/02/2021

TopiOCQA: Open-domain Conversational Question Answeringwith Topic Switching

In a conversational question answering scenario, a questioner seeks to e...

Vaibhav Adlakha, et al. ∙

research

∙ 08/10/2021

Post-hoc Interpretability for Neural NLP: A Survey

Natural Language Processing (NLP) models have become increasingly more c...

Andreas Madsen, et al. ∙

research

∙ 07/23/2021

Modelling Latent Translations for Cross-Lingual Transfer

While achieving state-of-the-art results in multiple tasks and languages...

Edoardo Maria Ponti, et al. ∙

research

∙ 06/09/2021

End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering

We present an end-to-end differentiable training method for retrieval-au...

Devendra Singh Sachan, et al. ∙

research

∙ 06/02/2021

Minimax and Neyman-Pearson Meta-Learning for Outlier Languages

Model-agnostic meta-learning (MAML) has been recently put forth as a str...

Edoardo Maria Ponti, et al. ∙

research

∙ 05/07/2021

Understanding by Understanding Not: Modeling Negation in Language Models

Negation is a core construction in natural language. Despite being very ...

Arian Hosseini, et al. ∙

research

∙ 04/18/2021

Back-Training excels Self-Training at Unsupervised Domain Adaptation of Question Generation and Passage Retrieval

In this paper, we propose a new domain adaptation method called back-tra...

Devang Kulshreshtha, et al. ∙

research

∙ 12/27/2020

MeDAL: Medical Abbreviation Disambiguation Dataset for Natural Language Understanding Pretraining

One of the biggest challenges that prohibit the use of many current NLP ...

Zhi Wen, et al. ∙

research

∙ 10/14/2020

Learning Improvised Chatbots from Adversarial Modifications of Natural Language Feedback

The ubiquitous nature of chatbots and their interaction with users gener...

Makesh Narsimhan Sreedhar, et al. ∙

research

∙ 09/30/2020

Measuring Systematic Generalization in Neural Proof Generation with Transformers

We are interested in understanding how well Transformer language models ...

Nicolas Gontier, et al. ∙

research

∙ 05/04/2020

Words aren't enough, their order matters: On the Robustness of Grounding Visual Referring Expressions

Visual referring expression recognition is a challenging task that requi...

Arjun R Akula, et al. ∙

research

∙ 04/20/2020

StereoSet: Measuring stereotypical bias in pretrained language models

A stereotype is an over-generalized belief about a particular group of p...

Moin Nadeem, et al. ∙

research

∙ 12/25/2018

Building a Neural Semantic Parser from a Domain Ontology

Semantic parsing is the task of converting natural language utterances i...

Jianpeng Cheng, et al. ∙

research

∙ 08/21/2018

CoQA: A Conversational Question Answering Challenge

Humans gather information by engaging in conversations involving a serie...

Siva Reddy, et al. ∙

research

∙ 11/14/2017

Learning an Executable Neural Semantic Parser

This paper describes a neural semantic parser that maps natural language...

Jianpeng Cheng, et al. ∙

research

∙ 08/20/2017

Learning to Paraphrase for Question Answering

Question answering (QA) systems are sensitive to the many different ways...

Li Dong, et al. ∙

research

∙ 04/27/2017

Learning Structured Natural Language Representations for Semantic Parsing

We introduce a neural semantic parser that converts natural language utt...

Jianpeng Cheng, et al. ∙

research

∙ 04/27/2017

Question Answering on Knowledge Bases and Text using Universal Schema and Memory Networks

Existing question answering methods infer answers either from a knowledg...

Rajarshi Das, et al. ∙

research

∙ 02/10/2017

Universal Dependencies to Logical Forms with Negation Scope

Many language technology applications would benefit from the ability to ...

Federico Fancellu, et al. ∙

research

∙ 02/10/2017

Universal Semantic Parsing

Universal Dependencies (UD) offer a uniform cross-lingual syntactic repr...

Siva Reddy, et al. ∙

research

∙ 02/03/2017

Predicting Target Language CCG Supertags Improves Neural Machine Translation

Neural machine translation (NMT) models are able to partially learn synt...

Maria Nădejde, et al. ∙

research

∙ 09/29/2016

Evaluating Induced CCG Parsers on Grounded Semantic Parsing

We compare the effectiveness of four different syntactic CCG parsers for...

Yonatan Bisk, et al. ∙

research

∙ 08/18/2016

DNN-based Speech Synthesis for Indian Languages from ASCII text

Text-to-Speech synthesis in Indian languages has a seen lot of progress ...

Srikanth Ronanki, et al. ∙

research

∙ 03/03/2016

Question Answering on Freebase via Relation Extraction and Textual Evidence

Existing knowledge-based question answering systems often rely on small ...

Kun Xu, et al. ∙

research

∙ 01/22/2016

Paraphrase Generation from Latent-Variable PCFGs for Semantic Parsing

One of the limitations of semantic parsing approaches to open-domain que...

Shashi Narayan, et al. ∙

Siva Reddy

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