Abstract Chat Generative Pre-trained Transformer (ChatGPT) has gained significant interest
and attention since its launch in November 2022. It has shown impressive performance in …

The field of machine translation (MT), the automatic translation of written text from one
natural language into another, has experienced a major paradigm shift in recent years …

Heterogeneous tabular data are the most commonly used form of data and are essential for
numerous critical and computationally demanding applications. On homogeneous datasets …

Pretrained masked language models (MLMs) require finetuning for most NLP tasks. Instead,
we evaluate MLMs out of the box via their pseudo-log-likelihood scores (PLLs), which are …

Recent developments in deep learning, coupled with an increasing number of sequenced
proteins, have led to a breakthrough in life science applications, in particular in protein …

As natural language processing methods are increasingly deployed in real-world scenarios
such as healthcare, legal systems, and social science, it becomes necessary to recognize …

Abstract Compositional Zero-Shot learning (CZSL) requires to recognize state-object
compositions unseen during training. In this work, instead of assuming prior knowledge …

Almost all existing machine translation models are built on top of character-based
vocabularies: characters, subwords or words. Rare characters from noisy text or character …

Realizing the potential of near-term quantum computers to solve industry-relevant
constrained-optimization problems is a promising path to quantum advantage. In this work …

Video moment retrieval is to search the moment that is most relevant to the given natural
language query. Existing methods are mostly trained in a fully-supervised setting, which …