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[HTML][HTML] Pre-trained language models and their applications
Pre-trained language models have achieved striking success in natural language
processing (NLP), leading to a paradigm shift from supervised learning to pre-training …
processing (NLP), leading to a paradigm shift from supervised learning to pre-training …
[HTML][HTML] A survey on text classification algorithms: From text to predictions
A Gasparetto, M Marcuzzo, A Zangari, A Albarelli - Information, 2022 - mdpi.com
In recent years, the exponential growth of digital documents has been met by rapid progress
in text classification techniques. Newly proposed machine learning algorithms leverage the …
in text classification techniques. Newly proposed machine learning algorithms leverage the …
Text classification via large language models
Despite the remarkable success of large-scale Language Models (LLMs) such as GPT-3,
their performances still significantly underperform fine-tuned models in the task of text …
their performances still significantly underperform fine-tuned models in the task of text …
How would stance detection techniques evolve after the launch of chatgpt?
Stance detection refers to the task of extracting the standpoint (Favor, Against or Neither)
towards a target in given texts. Such research gains increasing attention with the …
towards a target in given texts. Such research gains increasing attention with the …
DeepBIO: an automated and interpretable deep-learning platform for high-throughput biological sequence prediction, functional annotation and visualization analysis
Here, we present DeepBIO, the first-of-its-kind automated and interpretable deep-learning
platform for high-throughput biological sequence functional analysis. DeepBIO is a one-stop …
platform for high-throughput biological sequence functional analysis. DeepBIO is a one-stop …
[HTML][HTML] Hierarchical graph-based text classification framework with contextual node embedding and BERT-based dynamic fusion
A Onan - Journal of king saud university-computer and …, 2023 - Elsevier
We propose a novel hierarchical graph-based text classification framework that leverages
the power of contextual node embedding and BERT-based dynamic fusion to capture the …
the power of contextual node embedding and BERT-based dynamic fusion to capture the …
Causerec: Counterfactual user sequence synthesis for sequential recommendation
Learning user representations based on historical behaviors lies at the core of modern
recommender systems. Recent advances in sequential recommenders have convincingly …
recommender systems. Recent advances in sequential recommenders have convincingly …
Pushing the limit of LLM capacity for text classification
The value of text classification's future research has encountered challenges and
uncertainties, due to the extraordinary efficacy demonstrated by large language models …
uncertainties, due to the extraordinary efficacy demonstrated by large language models …
Ml-ljp: Multi-law aware legal judgment prediction
Legal judgment prediction (LJP) is a significant task in legal intelligence, which aims to
assist the judges and determine the judgment result based on the case's fact description …
assist the judges and determine the judgment result based on the case's fact description …
Sentiment analysis through llm negotiations
A standard paradigm for sentiment analysis is to rely on a singular LLM and makes the
decision in a single round under the framework of in-context learning. This framework suffers …
decision in a single round under the framework of in-context learning. This framework suffers …