In recent years, remarkable achievements have been made in artificial intelligence tasks
and applications based on deep neural networks (DNNs), especially in the fields of vision …

While machine learning models rapidly advance the state-of-the-art on various real-world
tasks, out-of-domain (OOD) generalization remains a challenging problem given the …

Modern language models (LMs) pose a new challenge in capability assessment. Static
benchmarks inevitably saturate without providing confidence in the deployment tolerances …

Image captioning, which generates natural language descriptions of images, is a crucial task
in vision-language research. Previous models have typically addressed this task by aligning …

The research on text summarization for low-resource Indian languages has been limited due
to the availability of relevant datasets. This paper presents a summary of various deep …

Building natural language inference (NLI) benchmarks that are both challenging for modern
techniques, and free from shortcut biases is difficult. Chief among these biases is" single …

Shortcuts, also described as Clever Hans behavior, spurious correlations, or confounders,
present a significant challenge in machine learning and AI, critically affecting model …