Results 11 to 20 of about 378,571 (361)
Developing Persona Analytics Towards Persona Science
27th International Conference on Intelligent User Interfaces, 2022 Much of the reported work on personas suffers from the lack of empirical evidence. To address this issue, we introduce Persona Analytics (PA), a system that tracks how users interact with data-driven personas. PA captures users’ mouse and gaze behavior to measure users’ interaction with algorithmically generated personas and use of system features for ...
Jung, Soon-Gyo +3 more
openaire +3 more sources
Toxicity in ChatGPT: Analyzing Persona-assigned Language Models [PDF]
Conference on Empirical Methods in Natural Language Processing, 2023 Large language models (LLMs) have shown incredible capabilities and transcended the natural language processing (NLP) community, with adoption throughout many services like healthcare, therapy, education, and customer service.
A. Deshpande +4 more
semanticscholar +1 more source
Are Personalized Stochastic Parrots More Dangerous? Evaluating Persona Biases in Dialogue Systems [PDF]
Conference on Empirical Methods in Natural Language Processing, 2023 Recent advancements in Large Language Models empower them to follow freeform instructions, including imitating generic or specific demographic personas in conversations. We define generic personas to represent demographic groups, such as"an Asian person",
Yixin Wan +4 more
semanticscholar +1 more source
Enhancing Personalized Dialogue Generation with Contrastive Latent Variables: Combining Sparse and Dense Persona [PDF]
Annual Meeting of the Association for Computational Linguistics, 2023 The personalized dialogue explores the consistent relationship between dialogue generation and personality. Existing personalized dialogue agents model persona profiles from three resources: sparse or dense persona descriptions and dialogue histories ...
Yihong Tang +6 more
semanticscholar +1 more source
MPCHAT: Towards Multimodal Persona-Grounded Conversation [PDF]
Annual Meeting of the Association for Computational Linguistics, 2023 In order to build self-consistent personalized dialogue agents, previous research has mostly focused on textual persona that delivers personal facts or personalities. However, to fully describe the multi-faceted nature of persona, image modality can help
Jaewoo Ahn +3 more
semanticscholar +1 more source
PeaCoK: Persona Commonsense Knowledge for Consistent and Engaging Narratives [PDF]
Annual Meeting of the Association for Computational Linguistics, 2023 Sustaining coherent and engaging narratives requires dialogue or storytelling agents to understandhow the personas of speakers or listeners ground the narrative. Specifically, these agents must infer personas of their listeners to produce statements that
Silin Gao +7 more
semanticscholar +1 more source
Learning to Memorize Entailment and Discourse Relations for Persona-Consistent Dialogues [PDF]
AAAI Conference on Artificial Intelligence, 2023 Maintaining engagement and consistency is particularly important in dialogue systems. Existing works have improved the performance of dialogue systems by intentionally learning interlocutor personas with sophisticated network structures.
Ruijun Chen +3 more
semanticscholar +1 more source
Long Time No See! Open-Domain Conversation with Long-Term Persona Memory [PDF]
Findings, 2022 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 understanding and memorizing long-term dialogue history information.
Xinchao Xu +6 more
semanticscholar +1 more source
A Model-agnostic Data Manipulation Method for Persona-based Dialogue Generation [PDF]
Annual Meeting of the Association for Computational Linguistics, 2022 Towards building intelligent dialogue agents, there has been a growing interest in introducing explicit personas in generation models. However, with limited persona-based dialogue data at hand, it may be difficult to train a dialogue generation model ...
Yu Cao +4 more
semanticscholar +1 more source
BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data [PDF]
Annual Meeting of the Association for Computational Linguistics, 2021 Maintaining a consistent persona is essential for dialogue agents. Although tremendous advancements have been brought, the limited-scale of annotated personalized dialogue datasets is still a barrier towards training robust and consistent persona-based ...
Haoyu Song +4 more
semanticscholar +1 more source