Large Language Models (LLMs) have recently demonstrated remarkable capabilities in
natural language processing tasks and beyond. This success of LLMs has led to a large …

In recent years, the exponential growth of digital documents has been met by rapid progress
in text classification techniques. Newly proposed machine learning algorithms leverage the …

Recent language models have shown impressive multilingual performance, even when not
explicitly trained for it. Despite this, there are concerns about the quality of their outputs …

With the ability to generate high-quality images, text-to-image (T2I) models can be exploited
for creating inappropriate content. To prevent misuse, existing safety measures are either …

Multimodal models are becoming increasingly effective, in part due to unified components,
such as the Transformer architecture. However, multimodal models still often consist of many …

This survey paper provides a comprehensive overview of the recent advancements and
challenges in applying large language models to the field of audio signal processing. Audio …

Deep neural-network-based language models (LMs) are increasingly applied to large-scale
protein sequence data to predict protein function. However, being largely black-box models …

This paper introduces mGPT, a multilingual variant of GPT-3, pretrained on 61 languages
from 25 linguistically diverse language families using Wikipedia and the C4 Corpus. We …

The form of a word sometimes conveys semantic information. For example, the iconic word
gurgle sounds like what it means, and busy is easy to identify as an English adjective …

Molecular Property Prediction (MPP) is vital for drug discovery, crop protection, and
environmental science. Over the last decades, diverse computational techniques have been …