Large language models (LLMs) are widely deployed in various downstream tasks, eg, auto-
completion, aided writing, or chat-based text generation. However, the considered output …

With the advent of large language models (LLMs), the trend in NLP has been to train LLMs
on vast amounts of data to solve diverse language understanding and generation tasks. The …

Generics are expressions used to communicate abstractions about categories. While
conveying general truths (eg,“Birds fly”), generics have the interesting property to admit …

To harness the power of large language models in safety-critical domains, we need to
ensure the explainability of their predictions. However, despite the significant attention to …

With their increasing size, large language models (LLMs) are becoming increasingly good at
language understanding tasks. But even with high performance on specific downstream …

The growing popularity of generative language models has amplified interest in interactive
methods to guide model outputs. Prompt refinement is considered one of the most effective …

Previous research in computational linguistics dedicated a lot of effort to using language
modeling and/or distributional semantic models to predict metrics extracted from eye …

Causal language models have emerged as the leading technology for automating text
generation tasks. Although these models tend to produce outputs that resemble human …

Despite the significant advancements in deep learning, understanding the inner workings of
such models remains a considerable challenge. While this opacity hinders trustworthiness …

Аннотация Целью настоящего исследования является определение того, как
лингвистические компоненты влияют на когнитивное развитие в рамках теории …