83 citations · 142 across the 8 of their papers we have counts for
8 papers
NUANCED: Natural Utterance Annotation for Nuanced Conversation with Estimated Distributions
Zhiyu Chen, Honglei Liu, Hu Xu +3
Existing conversational systems are mostly agent-centric, which assumes the user utterances would closely follow the system ontology (for NLU or dialogue state tracking). However,…
Adding Chit-Chat to Enhance Task-Oriented Dialogues
Kai Sun, Seungwhan Moon, Paul Crook +7
Existing dialogue corpora and models are typically designed under two disjoint motives: while task-oriented systems focus on achieving functional goals (e.g., booking hotels), open…
User Memory Reasoning for Conversational Recommendation
Hu Xu, Seungwhan Moon, Honglei Liu +3
We study a conversational recommendation model which dynamically manages users' past (offline) preferences and current (online) requests through a structured and cumulative user me…
Active Federated Learning
Jack Goetz, Kshitiz Malik, Duc Bui +3
Federated Learning allows for population level models to be trained without centralizing client data by transmitting the global model to clients, calculating gradients locally, the…
Federated User Representation Learning
Duc Bui, Kshitiz Malik, Jack Goetz +4
Collaborative personalization, such as through learned user representations (embeddings), can improve the prediction accuracy of neural-network-based models significantly. We propo…
Global Textual Relation Embedding for Relational Understanding
Zhiyu Chen, Hanwen Zha, Honglei Liu +3
Pre-trained embeddings such as word embeddings and sentence embeddings are fundamental tools facilitating a wide range of downstream NLP tasks. In this work, we investigate how to…
Explore-Exploit: A Framework for Interactive and Online Learning
Honglei Liu, Anuj Kumar, Wenhai Yang +1
Interactive user interfaces need to continuously evolve based on the interactions that a user has (or does not have) with the system. This may require constant exploration of vario…
Global Relation Embedding for Relation Extraction
Yu Su, Honglei Liu, Semih Yavuz +3
We study the problem of textual relation embedding with distant supervision. To combat the wrong labeling problem of distant supervision, we propose to embed textual relations with…