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Found 7 papers, 1 papers with code
zydhjh4593@SMM4H’22: A Generic Pre-trained BERT-based Framework for Social Media Health Text Classification
This paper describes our proposed framework for the 10 text classification tasks of Task 1a, 2a, 2b, 3a, 4, 5, 6, 7, 8, and 9, in the Social Media Mining for Health (SMM4H) 2022.
PokerGPT: An End-to-End Lightweight Solver for Multi-Player Texas Hold'em via Large Language Model
To improve fine-tuning performance, we conduct prompt engineering on raw data, including filtering useful information, selecting behaviors of players with high win rates, and further processing them into textual instruction using multiple prompt engineering techniques.
Large Foundation Models for Power Systems
Foundation models, such as Large Language Models (LLMs), can respond to a wide range of format-free queries without any task-specific data collection or model training, creating various research and application opportunities for the modeling and operation of large-scale power systems.
Deep Reinforcement Learning-Assisted Federated Learning for Robust Short-term Utility Demand Forecasting in Electricity Wholesale Markets
Considering the growing concern of data privacy, federated learning (FL) is increasingly adopted to train STLF models for utility companies (UCs) in recent research.
DearFSAC: An Approach to Optimizing Unreliable Federated Learning via Deep Reinforcement Learning
In federated learning (FL), model aggregation has been widely adopted for data privacy.
MeisterMorxrc at SemEval-2020 Task 9: Fine-Tune Bert and Multitask Learning for Sentiment Analysis of Code-Mixed Tweets
Natural language processing (NLP) has been applied to various fields including text classification and sentiment analysis.
Ferryman at SemEval-2020 Task 7: Ensemble Model for Assessing Humor in Edited News Headlines
Natural language processing (NLP) has been applied to various fields including text classification and sentiment analysis.
