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Found 4 papers, 3 papers with code
Distributionally Robust Classifiers in Sentiment Analysis
In this paper, we propose sentiment classification models based on BERT integrated with DRO (Distributionally Robust Classifiers) to improve model performance on datasets with distributional shifts.
Playing 2048 With Reinforcement Learning
The game of 2048 is a highly addictive game.
Ranked #4 on
Playing the Game of 2048
on The Game of 2048
Ensemble ALBERT on SQuAD 2.0
In our Paper, we utilized the fine-tuned ALBERT models and implemented combinations of additional layers (e. g. attention layer, RNN layer) on top of them to improve model performance on Stanford Question Answering Dataset (SQuAD 2. 0).
Ranked #86 on
Question Answering
on SQuAD2.0
(F1 metric)
Trajectory Prediction using Generative Adversarial Network in Multi-Class Scenarios
Predicting traffic agents' trajectories is an important task for auto-piloting.
