Question answering (QA) is a critical task for speech-based retrieval fr...
This paper studies the problem of open-domain question answering, with t...
To build open-domain chatbots that are able to use diverse communicative...
Embeddings, which compress information in raw text into semantics-preser...
In this paper, we propose to leverage the unique characteristics of dial...
Commonsense reasoning systems should be able to generalize to diverse
re...
Deep learning for Information Retrieval (IR) requires a large amount of
...
Language models (LMs) have shown great potential as implicit knowledge b...
Code completion, which aims to predict the following code token(s) accor...
This paper introduces a simple yet effective data-centric approach for t...
Active learning can be defined as iterations of data labeling, model
tra...
This paper studies the bias problem of multi-hop question answering mode...
Graph neural networks (GNNs) have been widely used in representation lea...
Can a text classifier generalize well for datasets where the text length...
Question answering (QA) has become a popular way for humans to access
bi...
The performance of text classification has improved tremendously using
i...
Question answering (QA) extracting answers from text to the given questi...
Word sense induction (WSI), or the task of automatically discovering mul...
The task of answering a question given a text passage has shown great
de...
In sentence classification tasks, additional contexts, such as the
neigh...
The use of user/product information in sentiment analysis is important,
...
A major proportion of a text summary includes important entities found i...
This paper aims at an aspect sentiment model for aspect-based sentiment
...
Verbs are important in semantic understanding of natural language.
Tradi...