Pre-trained language models have achieved striking success in natural language
processing (NLP), leading to a paradigm shift from supervised learning to pre-training …

Large language models (LLMs) have shown the potential of revolutionizing natural
language processing tasks in diverse domains, sparking great interest in finance. Accessing …

Most of the open-domain dialogue models tend to perform poorly in the setting of long-term
human-bot conversations. The possible reason is that they lack the capability of …

We introduce GODEL (Grounded Open Dialogue Language Model), a large pre-trained
language model for dialog. In contrast with earlier models such as DialoGPT, GODEL …

Recently, pre-training methods have shown remarkable success in task-oriented dialog
(TOD) systems. However, most existing pre-trained models for TOD focus on either dialog …

Large-scale pre-training has shown remarkable performance in building open-domain
dialogue systems. However, previous works mainly focus on showing and evaluating the …

This paper introduces Stochastic RAG--a novel approach for end-to-end optimization of
retrieval-augmented generation (RAG) models that relaxes the simplifying assumptions of …

This paper presents a comprehensive review of deep learning applications in the video
game industry, focusing on how these techniques can be utilized in game development …

Large Language Models (LLMs) represent a class of deep learning models adept at
understanding natural language and generating coherent responses to various prompts or …

With the rapid progress of deep neural models and the explosion of available data
resources, dialogue systems that supports extensive topics and chit-chat conversations are …