1 |
How does the pre-training objective affect what large language models learn about linguistic properties? ...
|
|
|
|
BASE
|
|
Show details
|
|
2 |
Automatic Identification and Classification of Bragging in Social Media ...
|
|
|
|
BASE
|
|
Show details
|
|
7 |
Frustratingly Simple Pretraining Alternatives to Masked Language Modeling ...
|
|
|
|
BASE
|
|
Show details
|
|
9 |
Improving the Faithfulness of Attention-based Explanations with Task-specific Information for Text Classification ...
|
|
|
|
BASE
|
|
Show details
|
|
10 |
Enjoy the Salience: Towards Better Transformer-based Faithful Explanations with Word Salience ...
|
|
|
|
BASE
|
|
Show details
|
|
13 |
In Factuality: Efficient Integration of Relevant Facts for Visual Question Answering ...
|
|
|
|
BASE
|
|
Show details
|
|
14 |
Frustratingly Simple Pretraining Alternatives to Masked Language Modeling ...
|
|
|
|
BASE
|
|
Show details
|
|
16 |
Machine Extraction of Tax Laws from Legislative Texts
|
|
|
|
In: Proceedings of the Natural Legal Language Processing Workshop 2021 (2021)
|
|
BASE
|
|
Show details
|
|
17 |
Point-of-Interest Type Prediction using Text and Images ...
|
|
|
|
Abstract:
Point-of-interest (POI) type prediction is the task of inferring the type of a place from where a social media post was shared. Inferring a POI's type is useful for studies in computational social science including sociolinguistics, geosemiotics, and cultural geography, and has applications in geosocial networking technologies such as recommendation and visualization systems. Prior efforts in POI type prediction focus solely on text, without taking visual information into account. However in reality, the variety of modalities, as well as their semiotic relationships with one another, shape communication and interactions in social media. This paper presents a study on POI type prediction using multimodal information from text and images available at posting time. For that purpose, we enrich a currently available data set for POI type prediction with the images that accompany the text messages. Our proposed method extracts relevant information from each modality to effectively capture interactions between text ... : Accepted at EMNLP 2021 ...
|
|
Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
|
|
URL: https://arxiv.org/abs/2109.00602 https://dx.doi.org/10.48550/arxiv.2109.00602
|
|
BASE
|
|
Hide details
|
|
18 |
Point-of-Interest Type Prediction using Text and Images ...
|
|
|
|
BASE
|
|
Show details
|
|
19 |
An Empirical Study on Leveraging Position Embeddings for Target-oriented Opinion Words Extraction ...
|
|
|
|
BASE
|
|
Show details
|
|
|
|