In this paper, we present ConvoGen: an innovative framework for generating synthetic conversational data using multi-agent systems. Our method leverages few-shot learning and introduces iterative sampling from a dynamically updated few-shot hub to create diverse and realistic conversational scenarios. The generated data has numerous applications, including training and evaluating conversational AI models, and augmenting existing datasets for tasks like conversational intent classification or conversation summarization. Our experiments demonstrate the effectiveness of this method in producing high-quality diverse synthetic conversational data, highlighting its potential to enhance the development and evaluation of conversational AI systems.

Identifying user intents in information-seeking dialogs is crucial for a system to meet user's information needs. Intent prediction (IP) is challenging and demands sufficient dialogs with human-labeled intents for training. However, manually annotating intents is resource-intensive. While large language models (LLMs) have been shown to be effective in generating synthetic data, there is no study on using LLMs to generate intent-aware information-seeking dialogs. In this paper, we focus on leveraging LLMs for zero-shot generation of large-scale, open-domain, and intent-aware information-seeking dialogs. We propose SOLID, which has novel self-seeding and multi-intent self-instructing schemes. The former improves the generation quality by using the LLM's own knowledge scope to initiate dialog generation; the latter prompts the LLM to generate utterances sequentially, and mitigates the need for manual prompt design by asking the LLM to autonomously adapt its prompt instruction when generating complex multi-intent utterances. Furthermore, we propose SOLID-RL, which is further trained to generate a dialog in one step on the data generated by SOLID. We propose a length-based quality estimation mechanism to assign varying weights to SOLID-generated dialogs based on their quality during the training process of SOLID-RL. We use SOLID and SOLID-RL to generate more than 300k intent-aware dialogs, surpassing the size of existing datasets. Experiments show that IP methods trained on dialogs generated by SOLID and SOLID-RL achieve better IP quality than ones trained on human-generated dialogs.

Modern conversational agents, including anime-themed chatbots, are frequently reactive and personality-driven but fail to capture the dynamic nature of human interactions. We propose an event-driven dialogue framework to address these limitations by embedding dynamic events in conversation prompts and fine-tuning models on character-specific data. Evaluations on GPT-4 and comparisons with industry-leading baselines demonstrate that event-driven prompts significantly improve conversational engagement and naturalness while reducing hallucinations. This paper explores the application of this approach in creating lifelike chatbot interactions within the context of Honkai: Star Rail, showcasing the potential for dynamic event-based systems to transform role-playing and interactive dialogue.

It's always good to have a friendly game with the sexy person you like on Tindrars. You already know that you both like what you have read about each other in s online profiles and find each other very attractive. But knowing what to say on Tindrars is definitely the next logical step. So what are the top 5 things to say when chatting with your girl on Tindrars? First of all, never ever talk negatively about anyone on Tindrars.

Are you wondering how to text on tinder? If you're interested in the latest and hottest method for meeting women, then you'll want to keep reading. The rise of this dating app has been amazing. It's so much easier now, since there are so many more options. That said, learning how to text on tinder is critical if you want to make a good impression with women.

Conversational Intelligence requires that a person engage on informational, personal and relational levels. Advances in Natural Language Understanding have helped recent chatbots succeed at dialog on the informational level. However, current techniques still lag for conversing with humans on a personal level and fully relating to them. The University of Michigan's submission to the Alexa Prize Grand Challenge 3, Audrey, is an open-domain conversational chat-bot that aims to engage customers on these levels through interest driven conversations guided by customers' personalities and emotions. Audrey is built from socially-aware models such as Emotion Detection and a Personal Understanding Module to grasp a deeper understanding of users' interests and desires. Our architecture interacts with customers using a hybrid approach balanced between knowledge-driven response generators and context-driven neural response generators to cater to all three levels of conversations. During the semi-finals period, we achieved an average cumulative rating of 3.25 on a 1-5 Likert scale.

The perfect Tinder photo: yes, it has to get you on your good side and disguise that double chin, but is there more to it than just looking good? Hana Michels, a comedian and writer from LA, who shared a screengrab of her Tinder profile to Twitter this week, found that a lot of men whom she matched with weren't interested in her at all but in her toilet paper holder. She explained that she had been chastised by no fewer than 23 men in a year for the direction in which her toilet paper was facing – a small detail in the background of the photo. This is my tinder profile. I've had it for a year.

Lenovo is betting big on smart devices' ability to catapult the company into a future IT market dominated by artificial intelligence, and the company is giving a peek at the concept products it says will get it there. Lenovo CTO Yong Rui, in a blog post published as the company's Tech World conference kicked off in Shanghai, China, this week, said the company is investing heavily in AI, including spending on personne, and an Artificial Intelligence Lab staffed by more than 100 researchers around the world. Rui writes that in order to enable AI to "change how we live and work and how our societies operate," Lenovo must get algorithms, big data and computing power right. Lenovo this week is showing off a handful of concept products intended to show that the company has done just that.