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On the opportunities and risks of foundation models
AI is undergoing a paradigm shift with the rise of models (eg, BERT, DALL-E, GPT-3) that are
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …
Transfer learning for sentiment analysis using BERT based supervised fine-tuning
The growth of the Internet has expanded the amount of data expressed by users across
multiple platforms. The availability of these different worldviews and individuals' emotions …
multiple platforms. The availability of these different worldviews and individuals' emotions …
A primer in BERTology: What we know about how BERT works
Transformer-based models have pushed state of the art in many areas of NLP, but our
understanding of what is behind their success is still limited. This paper is the first survey of …
understanding of what is behind their success is still limited. This paper is the first survey of …
IndicNLPSuite: Monolingual corpora, evaluation benchmarks and pre-trained multilingual language models for Indian languages
In this paper, we introduce NLP resources for 11 major Indian languages from two major
language families. These resources include:(a) large-scale sentence-level monolingual …
language families. These resources include:(a) large-scale sentence-level monolingual …
SimAlign: High quality word alignments without parallel training data using static and contextualized embeddings
Word alignments are useful for tasks like statistical and neural machine translation (NMT)
and cross-lingual annotation projection. Statistical word aligners perform well, as do …
and cross-lingual annotation projection. Statistical word aligners perform well, as do …
Bangla-bert: transformer-based efficient model for transfer learning and language understanding
The advent of pre-trained language models has directed a new era of Natural Language
Processing (NLP), enabling us to create powerful language models. Among these models …
Processing (NLP), enabling us to create powerful language models. Among these models …
Reliability of electric vehicle charging infrastructure: A cross-lingual deep learning approach
Vehicle electrification has emerged as a global strategy to address climate change and
emissions externalities from the transportation sector. Deployment of charging infrastructure …
emissions externalities from the transportation sector. Deployment of charging infrastructure …
Abusive Bangla comments detection on Facebook using transformer-based deep learning models
In the era of social networking platforms, user-generated content is flooding every second on
online social media platforms like Facebook. So observing and identifying many contents …
online social media platforms like Facebook. So observing and identifying many contents …
Lost in translation: large language models in non-English content analysis
In recent years, large language models (eg, Open AI's GPT-4, Meta's LLaMa, Google's
PaLM) have become the dominant approach for building AI systems to analyze and …
PaLM) have become the dominant approach for building AI systems to analyze and …
Semantic relation extraction: a review of approaches, datasets, and evaluation methods with looking at the methods and datasets in the Persian language
A large volume of unstructured data, especially text data, is generated and exchanged daily.
Consequently, the importance of extracting patterns and discovering knowledge from textual …
Consequently, the importance of extracting patterns and discovering knowledge from textual …