Search Results for author:
Found 8 papers, 5 papers with code
ACE : Off-Policy Actor-Critic with Causality-Aware Entropy Regularization
The varying significance of distinct primitive behaviors during the policy learning process has been overlooked by prior model-free RL algorithms.
DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization
To quantify this inactivity, we adopt dormant ratio as a metric to measure inactivity in the RL agent's network.
Towards Arbitrary Text-driven Image Manipulation via Space Alignment
Then, the text input can be directly accessed into the StyleGAN space and be used to find the semantic shift according to the text description.
Automatic Task Requirements Writing Evaluation via Machine Reading Comprehension
A TR writing question may include multiple requirements and a high-quality essay must respond to each requirement thoroughly and accurately.
Robust Learning for Text Classification with Multi-source Noise Simulation and Hard Example Mining
Despite that pre-trained models achieve state-of-the-art performance in many NLP benchmarks, we prove that they are not robust to noisy texts generated by real OCR engines.
Optical Character Recognition
Optical Character Recognition (OCR)
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Representation Learning from Limited Educational Data with Crowdsourced Labels
Extensive experiments conducted on three real-world data sets demonstrate the superiority of our framework on learning representations from limited data with crowdsourced labels, comparing with various state-of-the-art baselines.
Dolphin: A Spoken Language Proficiency Assessment System for Elementary Education
In our offline experiments, we show that Dolphin improves both phonological fluency and semantic relevance evaluation performance when compared to state-of-the-art baselines on real-world educational data sets.
Learning Effective Embeddings From Crowdsourced Labels: An Educational Case Study
In practice, the crowdsourced labels are usually inconsistent among crowd workers given their diverse expertise and the number of crowdsourced labels is very limited.
