4 citations · 4 across the 3 of their papers we have counts for
5 papers
DocTalk: Scalable Graph-based Dialogue Synthesis for Enhancing LLM Conversational Capabilities
Jing Yang Lee, Hamed Bonab, Nasser Zalmout +6
Large Language Models (LLMs) are increasingly employed in multi-turn conversational tasks, yet their pre-training data predominantly consists of continuous prose, creating a potent…
Modeling the One-to-Many Property in Open-Domain Dialogue with LLMs
Jing Yang Lee, Kong-Aik Lee, Woon-Seng Gan
Open-domain Dialogue (OD) exhibits a one-to-many (o2m) property, whereby multiple appropriate responses exist for a single dialogue context. Despite prior research showing that mod…
Redefining Proactivity for Information Seeking Dialogue
Jing Yang Lee, Seokhwan Kim, Kartik Mehta +3
Information-Seeking Dialogue (ISD) agents aim to provide accurate responses to user queries. While proficient in directly addressing user queries, these agents, as well as LLMs in…
Improving Contextual Coherence in Variational Personalized and Empathetic Dialogue Agents
Jing Yang Lee, Kong Aik Lee, Woon Seng Gan
In recent years, latent variable models, such as the Conditional Variational Auto Encoder (CVAE), have been applied to both personalized and empathetic dialogue generation. Prior w…
Generating Personalized Dialogue via Multi-Task Meta-Learning
Jing Yang Lee, Kong Aik Lee, Woon Seng Gan
Conventional approaches to personalized dialogue generation typically require a large corpus, as well as predefined persona information. However, in a real-world setting, neither a…