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 …

Instruction tuning plays a critical role in aligning large language models (LLMs) with human
preference. Despite the vast amount of open instruction datasets, naively training a LLM on …

Natural Language Processing (NLP) research is increasingly focusing on the use of Large
Language Models (LLMs), with some of the most popular ones being either fully or partially …

Semi-supervised learning (SSL) is a popular setting aiming to effectively utilize unlabelled
data to improve model performance in downstream natural language processing (NLP) …

We introduce Bonito, an open-source model for conditional task generation: the task of
converting unannotated text into task-specific training datasets for instruction tuning. Our …

Abstract Large Language Models (LLMs) are being employed by end-users for various
tasks, including sensitive ones such as health counseling, disregarding potential safety …

Conversational agents have become ubiquitous in assisting with daily tasks, and are
expected to possess human-like features. One such feature is lexical entrainment (LE), a …

Session-based recommendation, which aims to predict the next item of users' interest as per
an existing sequence interaction of items, has attracted growing applications of Contrastive …

In recent years, language models (LMs) have made remarkable progress in advancing the
field of natural language processing (NLP). However, the impact of data augmentation (DA) …

Utilizing user profiles to personalize Large Language Models (LLMs) has been shown to
enhance the performance on a wide range of tasks. However, the precise role of user …