b'Siva Reddy'

research

∙ 09/19/2023

In-Context Learning for Text Classification with Many Labels

In-context learning (ICL) using large language models for tasks with man...

0 Aristides Milios, et al. ∙

research

∙ 07/31/2023

Evaluating Correctness and Faithfulness of Instruction-Following Models for Question Answering

Retriever-augmented instruction-following models are attractive alternat...

0 Vaibhav Adlakha, et al. ∙

research

∙ 05/31/2023

The Impact of Positional Encoding on Length Generalization in Transformers

Length generalization, the ability to generalize from small training con...

4 Amirhossein Kazemnejad, et al. ∙

research

∙ 05/25/2023

Are Diffusion Models Vision-And-Language Reasoners?

Text-conditioned image generation models have recently shown immense qua...

0 Benno Krojer, et al. ∙

research

∙ 05/09/2023

StarCoder: may the source be with you!

The BigCode community, an open-scientific collaboration working on the r...

12 Raymond Li, et al. ∙

research

∙ 04/03/2023

The StatCan Dialogue Dataset: Retrieving Data Tables through Conversations with Genuine Intents

We introduce the StatCan Dialogue Dataset consisting of 19,379 conversat...

0 Xing Han Lu, et al. ∙

research

∙ 12/18/2022

Can Retriever-Augmented Language Models Reason? The Blame Game Between the Retriever and the Language Model

The emergence of large pretrained models has enabled language models to ...

0 Parishad BehnamGhader, et al. ∙

research

∙ 11/29/2022

Syntactic Substitutability as Unsupervised Dependency Syntax

Syntax is a latent hierarchical structure which underpins the robust and...

0 Jasper Jian, et al. ∙

research

∙ 10/23/2022

The Curious Case of Absolute Position Embeddings

Transformer language models encode the notion of word order using positi...

0 Koustuv Sinha, et al. ∙

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) ...

3 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...

6 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...

7 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;...

0 Zichao Li, et al. ∙

research

∙ 03/29/2022

Image Retrieval from Contextual Descriptions

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

4 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...

9 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 ...

14 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...

0 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...

0 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...

9 Andreas Madsen, et al. ∙

research

∙ 10/13/2021

Compositional Generalization in Dependency Parsing

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

0 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...

1 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...

23 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...

7 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...

0 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...

0 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 ...

0 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...

0 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 ...

0 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...

0 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 ...

6 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...

11 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...

0 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...

0 Jianpeng Cheng, et al. ∙

research

∙ 08/21/2018

CoQA: A Conversational Question Answering Challenge

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

4 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...

0 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...

0 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...

0 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...

0 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 ...

0 Federico Fancellu, et al. ∙

research

∙ 02/10/2017

Universal Semantic Parsing

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

0 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...

0 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...

0 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 ...

0 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 ...

0 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...

0 Shashi Narayan, et al. ∙

Siva Reddy

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