Spaceflight associated neuro-ocular syndrome (SANS) is a unique phenomenon that has
been observed in astronauts who have undergone long-duration spaceflight (LDSF). The …

We propose a geographically reproducible approach to urban scene sensing based on
large-scale pre-trained models. With the rise of GeoAI research, many high-quality urban …

Aspect-based sentiment analysis (ABSA) means to identify fine-grained aspects, opinions,
and sentiment polarities. Recent ABSA research focuses on utilizing multi-task learning …

Labeling training data has become one of the major roadblocks to using machine learning.
Among various weak supervision paradigms, programmatic weak supervision (PWS) has …

Recent Weak Supervision (WS) approaches have had widespread success in easing the
bottleneck of labeling training data for machine learning by synthesizing labels from multiple …

Strong student models can learn from weaker teachers: when trained on the predictions of a
weaker model, a strong pretrained student can learn to correct the weak model's errors and …

Despite its flexibility to learn diverse inductive biases in machine learning programs, meta
learning (ie,\learning to learn) has long been recognized to suffer from poor scalability due …

Math Word Problem (MWP) solving needs to discover the quantitative relationships over
natural language narratives. Recent work shows that existing models memorize procedures …

Weakly-supervised learning (WSL) has shown promising results in addressing label scarcity
on many NLP tasks, but manually designing a comprehensive, high-quality labeling rule set …

Current NLP models heavily rely on effective representation learning algorithms. Contrastive
learning is one such technique to learn an embedding space such that similar data sample …