18 citations · 22 across the 6 of their papers we have counts for
6 papers
GRAG: Generic Response-Augmented Generation Framework for Personalized Conversational Systems
Junfeng Liu, Christopher T. Symons, Ranga Raju Vatsavai
Deploying highly capable personalized conversational agents in resource-constrained or privacy-sensitive environments remains a significant challenge. We identify a fundamental bot…
CoMAC: Conversational Agent for Multi-Source Auxiliary Context with Sparse and Symmetric Latent Interactions
Junfeng Liu, Christopher T. Symons, Ranga Raju Vatsavai
Recent advancements in AI-driven conversational agents have exhibited immense potential of AI applications. Effective response generation is crucial to the success of these agents.…
Context Retrieval via Normalized Contextual Latent Interaction for Conversational Agent
Junfeng Liu, Zhuocheng Mei, Kewen Peng +1
Conversational agents leveraging AI, particularly deep learning, are emerging in both academic research and real-world applications. However, these applications still face challeng…
Persona-Coded Poly-Encoder: Persona-Guided Multi-Stream Conversational Sentence Scoring
Junfeng Liu, Christopher Symons, Ranga Raju Vatsavai
Recent advances in machine learning and deep learning have led to the widespread use of Conversational AI in many practical applications. However, it is still very challenging to l…
Persona-Based Conversational AI: State of the Art and Challenges
Junfeng Liu, Christopher Symons, Ranga Raju Vatsavai
Conversational AI has become an increasingly prominent and practical application of machine learning. However, existing conversational AI techniques still suffer from various limit…
On the Unreasonable Efficiency of State Space Clustering in Personalization Tasks
Anton Dereventsov, Ranga Raju Vatsavai, Clayton Webster
In this effort we consider a reinforcement learning (RL) technique for solving personalization tasks with complex reward signals. In particular, our approach is based on state spac…