[HTML][HTML] Advances and challenges in conversational recommender systems: A survey

C Gao, W Lei, X He, M de Rijke, TS Chua - AI open, 2021‏ - Elsevier
Recommender systems exploit interaction history to estimate user preference, having been
heavily used in a wide range of industry applications. However, static recommendation …

From matching to generation: A survey on generative information retrieval

X Li, J **, Y Zhou, Y Zhang, P Zhang, Y Zhu… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Information Retrieval (IR) systems are crucial tools for users to access information, widely
applied in scenarios like search engines, question answering, and recommendation …

Understanding AI tool engagement: A study of ChatGPT usage and word-of-mouth among university students and office workers

H Jo - Telematics and Informatics, 2023‏ - Elsevier
This study aims to explore the determinants of user behaviors toward an artificial intelligence
(AI) tool, ChatGPT, focusing on university students and office workers. In this study, we …

Democratizing large language models via personalized parameter-efficient fine-tuning

Z Tan, Q Zeng, Y Tian, Z Liu, B Yin, M Jiang - arxiv preprint arxiv …, 2024‏ - arxiv.org
Personalization in large language models (LLMs) is increasingly important, aiming to align
the LLMs' interactions, content, and recommendations with individual user preferences …

Less is more: Learning to refine dialogue history for personalized dialogue generation

H Zhong, Z Dou, Y Zhu, H Qian, JR Wen - arxiv preprint arxiv:2204.08128, 2022‏ - arxiv.org
Personalized dialogue systems explore the problem of generating responses that are
consistent with the user's personality, which has raised much attention in recent years …

Personalized language modeling from personalized human feedback

X Li, R Zhou, ZC Lipton, L Leqi - arxiv preprint arxiv:2402.05133, 2024‏ - arxiv.org
Personalized large language models (LLMs) are designed to tailor responses to individual
user preferences. While Reinforcement Learning from Human Feedback (RLHF) is a …

Sentiment analysis for personalized chatbots in e-commerce applications

A El-Ansari, A Beni-Hssane - Wireless Personal Communications, 2023‏ - Springer
Chatbots and question-answering systems aim to provide precise answers to user inquiries,
as opposed to simply providing a list of related documents as is typical of traditional search …

Keep me updated! memory management in long-term conversations

S Bae, D Kwak, S Kang, MY Lee, S Kim… - arxiv preprint arxiv …, 2022‏ - arxiv.org
Remembering important information from the past and continuing to talk about it in the
present are crucial in long-term conversations. However, previous literature does not deal …

Memory sandbox: Transparent and interactive memory management for conversational agents

Z Huang, S Gutierrez, H Kamana… - Adjunct Proceedings of the …, 2023‏ - dl.acm.org
The recent advent of large language models (LLM) has resulted in high-performing
conversational agents such as ChatGPT. These agents must remember key information from …

Target-aware abstractive related work generation with contrastive learning

X Chen, H Alamro, M Li, S Gao, R Yan, X Gao… - Proceedings of the 45th …, 2022‏ - dl.acm.org
The related work section is an important component of a scientific paper, which highlights
the contribution of the target paper in the context of the reference papers. Authors can save …