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[HTML][HTML] Advances and challenges in conversational recommender systems: A survey
Recommender systems exploit interaction history to estimate user preference, having been
heavily used in a wide range of industry applications. However, static recommendation …
heavily used in a wide range of industry applications. However, static recommendation …
From matching to generation: A survey on generative information retrieval
Information Retrieval (IR) systems are crucial tools for users to access information, widely
applied in scenarios like search engines, question answering, and recommendation …
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 …
(AI) tool, ChatGPT, focusing on university students and office workers. In this study, we …
Democratizing large language models via personalized parameter-efficient fine-tuning
Personalization in large language models (LLMs) is increasingly important, aiming to align
the LLMs' interactions, content, and recommendations with individual user preferences …
the LLMs' interactions, content, and recommendations with individual user preferences …
Less is more: Learning to refine dialogue history for personalized dialogue generation
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 …
consistent with the user's personality, which has raised much attention in recent years …
Personalized language modeling from personalized human feedback
Personalized large language models (LLMs) are designed to tailor responses to individual
user preferences. While Reinforcement Learning from Human Feedback (RLHF) is a …
user preferences. While Reinforcement Learning from Human Feedback (RLHF) is a …
Sentiment analysis for personalized chatbots in e-commerce applications
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 …
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
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 …
present are crucial in long-term conversations. However, previous literature does not deal …
Memory sandbox: Transparent and interactive memory management for conversational agents
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 …
conversational agents such as ChatGPT. These agents must remember key information from …
Target-aware abstractive related work generation with contrastive learning
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 …
the contribution of the target paper in the context of the reference papers. Authors can save …