Token Trails: Navigating Contextual Depths in Conversational AI with ChatLLM

arXiv:2404.02402v1 Announce Type: cross
Abstract: Conversational modeling using Large Language Models (LLMs) requires a nuanced understanding of context to generate coherent and contextually relevant responses. In this paper, we present Token Trails, a novel approach that leverages token-type embeddings to navigate the intricate contextual nuances within conversations. Our framework utilizes token-type embeddings to distinguish between user utterances and bot responses, facilitating the generation of context-aware replies. Through comprehensive experimentation and evaluation, we demonstrate the effectiveness of Token Trails in improving …

abstract arxiv context conversational conversational ai conversations cs.ai cs.cl cs.ir cs.lg embeddings framework generate language language models large language large language models llms modeling novel paper responses token type understanding