Chatbots are intelligent conversational computer systems designed to mimic human
conversation to enable automated online guidance and support. The increased benefits of …

The recent success of large language models (LLMs) trained on static, pre-collected,
general datasets has sparked numerous research directions and applications. One such …

This survey provides an in-depth analysis of knowledge conflicts for large language models
(LLMs), highlighting the complex challenges they encounter when blending contextual and …

Large Language Models (LMs) are known to encode world knowledge in their parameters
as they pretrain on a vast amount of web corpus, which is often utilized for performing …

As the applications of large language models (LLMs) expand across diverse fields, their
ability to adapt to ongoing changes in data, tasks, and user preferences becomes crucial …

Language Models (LMs) become outdated as the world changes; they often fail to perform
tasks requiring recent factual information which was absent or different during training, a …

Interactive Natural Language Processing (iNLP) has emerged as a novel paradigm within
the field of NLP, aimed at addressing limitations in existing frameworks while aligning with …

Objective In this study, we investigate the potential of large language models (LLMs) to
complement biomedical knowledge graphs in the training of semantic models for the …

Learning to converse using only a few examples is a great challenge in conversational AI.
The current best conversational models, which are either good chit-chatters (eg, BlenderBot) …

Context-based fine-tuning methods, including prompting, in-context learning, soft prompting
(also known as prompt tuning), and prefix-tuning, have gained popularity due to their ability …