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09/19/2023
In-Context Learning for Text Classification with Many Labels
In-context learning (ICL) using large language models for tasks with man...
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07/31/2023
Evaluating Correctness and Faithfulness of Instruction-Following Models for Question Answering
Retriever-augmented instruction-following models are attractive alternat...
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05/31/2023
The Impact of Positional Encoding on Length Generalization in Transformers
Length generalization, the ability to generalize from small training con...
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05/25/2023
Are Diffusion Models Vision-And-Language Reasoners?
Text-conditioned image generation models have recently shown immense qua...
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05/09/2023
StarCoder: may the source be with you!
The BigCode community, an open-scientific collaboration working on the r...
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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...
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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 ...
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11/29/2022
Syntactic Substitutability as Unsupervised Dependency Syntax
Syntax is a latent hierarchical structure which underpins the robust and...
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10/23/2022
The Curious Case of Absolute Position Embeddings
Transformer language models encode the notion of word order using positi...
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06/08/2022
Few-shot Question Generation for Personalized Feedback in Intelligent Tutoring Systems
Existing work on generating hints in Intelligent Tutoring Systems (ITS) ...
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04/22/2022
FaithDial: A Faithful Benchmark for Information-Seeking Dialogue
The goal of information-seeking dialogue is to respond to seeker queries...
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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...
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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;...
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03/29/2022
Image Retrieval from Contextual Descriptions
The ability to integrate context, including perceptual and temporal cues...
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02/28/2022
Combining Modular Skills in Multitask Learning
A modular design encourages neural models to disentangle and recombine d...
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01/05/2022
Does entity abstraction help generative Transformers reason?
Pre-trained language models (LMs) often struggle to reason logically or ...
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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...
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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...
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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...
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10/13/2021
Compositional Generalization in Dependency Parsing
Compositionality, or the ability to combine familiar units like words in...
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10/02/2021
TopiOCQA: Open-domain Conversational Question Answeringwith Topic Switching
In a conversational question answering scenario, a questioner seeks to e...
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08/10/2021
Post-hoc Interpretability for Neural NLP: A Survey
Natural Language Processing (NLP) models have become increasingly more c...
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07/23/2021
Modelling Latent Translations for Cross-Lingual Transfer
While achieving state-of-the-art results in multiple tasks and languages...
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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...
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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...
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05/07/2021
Understanding by Understanding Not: Modeling Negation in Language Models
Negation is a core construction in natural language. Despite being very ...
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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...
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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 ...
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10/14/2020
Learning Improvised Chatbots from Adversarial Modifications of Natural Language Feedback
The ubiquitous nature of chatbots and their interaction with users gener...
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09/30/2020
Measuring Systematic Generalization in Neural Proof Generation with Transformers
We are interested in understanding how well Transformer language models ...
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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...
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04/20/2020
StereoSet: Measuring stereotypical bias in pretrained language models
A stereotype is an over-generalized belief about a particular group of p...
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12/25/2018
Building a Neural Semantic Parser from a Domain Ontology
Semantic parsing is the task of converting natural language utterances i...
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08/21/2018
CoQA: A Conversational Question Answering Challenge
Humans gather information by engaging in conversations involving a serie...
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11/14/2017
Learning an Executable Neural Semantic Parser
This paper describes a neural semantic parser that maps natural language...
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08/20/2017
Learning to Paraphrase for Question Answering
Question answering (QA) systems are sensitive to the many different ways...
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04/27/2017
Learning Structured Natural Language Representations for Semantic Parsing
We introduce a neural semantic parser that converts natural language utt...
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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...
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02/10/2017
Universal Dependencies to Logical Forms with Negation Scope
Many language technology applications would benefit from the ability to ...
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02/10/2017
Universal Semantic Parsing
Universal Dependencies (UD) offer a uniform cross-lingual syntactic repr...
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02/03/2017
Predicting Target Language CCG Supertags Improves Neural Machine Translation
Neural machine translation (NMT) models are able to partially learn synt...
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09/29/2016
Evaluating Induced CCG Parsers on Grounded Semantic Parsing
We compare the effectiveness of four different syntactic CCG parsers for...
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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 ...
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03/03/2016
Question Answering on Freebase via Relation Extraction and Textual Evidence
Existing knowledge-based question answering systems often rely on small ...
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01/22/2016
