To foster the development of new models for collaborative AI-assisted re...
Learning template based information extraction from documents is a cruci...
One of the ultimate quests of question answering (QA) is to deploy a sys...
Large language models (LLMs) show impressive abilities via few-shot
prom...
Question Answering (QA) systems require a large amount of annotated data...
Model calibration aims to adjust (calibrate) models' confidence so that ...
This paper develops automatic song translation (AST) for tonal languages...
Pretrained multilingual models enable zero-shot learning even for unseen...
Open-domain question answering answers a question based on evidence retr...
A flaw in QA evaluation is that annotations often only provide one gold
...
Topic model evaluation, like evaluation of other unsupervised methods, c...
Training coreference resolution models require comprehensively labeled d...
Question Answering (QA) tasks are used as benchmarks of general machine
...
Complex question answering often requires finding a reasoning chain that...
We release FoolMeTwice (FM2 for short), a large dataset of challenging
e...
We introduce DELFT, a factoid question answering system which combines t...
We review the EfficientQA competition from NeurIPS 2020. The competition...
We introduce CLIMATE-FEVER, a new publicly available dataset for verific...
Climate change communication in the mass media and other textual sources...
Large-scale semantic parsing datasets annotated with logical forms have
...
Active learning strives to reduce annotation costs by choosing the most
...
Cross-lingual word embeddings (CLWE) are often evaluated on bilingual le...
We investigate a framework for machine reading, inspired by real world
i...
Cross-lingual word embeddings transfer knowledge between languages: mode...
In addition to the traditional task of getting machines to answer questi...
Natural language processing systems are often downstream of unreliable
i...
Cross-lingual word embeddings encode the meaning of words from different...
Cross-lingual word embeddings (CLWE) underlie many multilingual natural
...
To address the lack of comparative evaluation of Human-in-the-Loop Topic...
Topic models are typically evaluated with respect to the global topic
di...
Recent work establishes dataset difficulty and removes annotation artifa...
Quizbowl is a scholastic trivia competition that tests human knowledge a...
Text classification must sometimes be applied in situations with no trai...
Machine learning is an important tool for decision making, but its ethic...
Local model interpretation methods explain individual predictions by
ass...
Modern natural language processing systems have been touted as approachi...
Simultaneous interpretation, translation of the spoken word in real-time...
Multilingual topic models enable document analysis across languages thro...
Methods for learning word sense embeddings represent a single word with
...
Exposing the weaknesses of neural models is crucial for improving their
...
Automatic colorization is the process of adding color to greyscale image...
Machine translation is a natural candidate problem for reinforcement lea...
Visual narrative is often a combination of explicit information and judi...
Interpersonal relations are fickle, with close friendships often dissolv...
Latent feature models are attractive for image modeling, since images
ge...
We develop the multilingual topic model for unaligned text (MuTo), a
pro...
Latent Dirichlet Allocation (LDA) is a popular topic modeling technique ...
The syntactic topic model (STM) is a Bayesian nonparametric model of lan...