53 citations · 78 across the 19 of their papers we have counts for
8 papers · 1 filter
PENTATRON: PErsonalized coNText-Aware Transformer for Retrieval-based cOnversational uNderstanding
Niranjan Uma Naresh, Ziyan Jiang, Ankit +4
Conversational understanding is an integral part of modern intelligent devices. In a large fraction of the global traffic from customers using smart digital assistants, frictions i…
Constrained Policy Optimization for Controlled Self-Learning in Conversational AI Systems
Mohammad Kachuee, Sungjin Lee
Recently, self-learning methods based on user satisfaction metrics and contextual bandits have shown promising results to enable consistent improvements in conversational AI system…
Learning Personalized Representations using Graph Convolutional Network
Hongyu Shen, Jinoh Oh, Shuai Zhao +3
Generating representations that precisely reflect customers' behavior is an important task for providing personalized skill routing experience in Alexa. Currently, Dynamic Routing…
Scalable and Robust Self-Learning for Skill Routing in Large-Scale Conversational AI Systems
Mohammad Kachuee, Jinseok Nam, Sarthak Ahuja +2
Skill routing is an important component in large-scale conversational systems. In contrast to traditional rule-based skill routing, state-of-the-art systems use a model-based appro…
Domain-Aware Contrastive Knowledge Transfer for Multi-domain Imbalanced Data
Zixuan Ke, Mohammad Kachuee, Sungjin Lee
In many real-world machine learning applications, samples belong to a set of domains e.g., for product reviews each review belongs to a product category. In this paper, we study mu…
Learning Slice-Aware Representations with Mixture of Attentions
Cheng Wang, Sungjin Lee, Sunghyun Park +3
Real-world machine learning systems are achieving remarkable performance in terms of coarse-grained metrics like overall accuracy and F-1 score. However, model improvement and deve…
Handling Long-Tail Queries with Slice-Aware Conversational Systems
Cheng Wang, Sun Kim, Taiwoo Park +5
We have been witnessing the usefulness of conversational AI systems such as Siri and Alexa, directly impacting our daily lives. These systems normally rely on machine learning mode…
Self-Supervised Contrastive Learning for Efficient User Satisfaction Prediction in Conversational Agents
Mohammad Kachuee, Hao Yuan, Young-Bum Kim +1
Turn-level user satisfaction is one of the most important performance metrics for conversational agents. It can be used to monitor the agent's performance and provide insights abou…