23 citations · 48 across the 10 of their papers we have counts for
10 papers
RecMind: Large Language Model Powered Agent For Recommendation
Yancheng Wang, Ziyan Jiang, Zheng Chen +7
While the recommendation system (RS) has advanced significantly through deep learning, current RS approaches usually train and fine-tune models on task-specific datasets, limiting…
Knowledge Enhanced Multi-Domain Recommendations in an AI Assistant Application
Elan Markowitz, Ziyan Jiang, Fan Yang +4
This work explores unifying knowledge enhanced recommendation with multi-domain recommendation systems in a conversational AI assistant application. Multi-domain recommendation lev…
KG-ECO: Knowledge Graph Enhanced Entity Correction for Query Rewriting
Jinglun Cai, Mingda Li, Ziyan Jiang +5
Query Rewriting (QR) plays a critical role in large-scale dialogue systems for reducing frictions. When there is an entity error, it imposes extra challenges for a dialogue system…
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…
Learning to Selectively Learn for Weakly-supervised Paraphrase Generation
Kaize Ding, Dingcheng Li, Alexander Hanbo Li +4
Paraphrase generation is a longstanding NLP task that has diverse applications for downstream NLP tasks. However, the effectiveness of existing efforts predominantly relies on larg…
Pattern-aware Data Augmentation for Query Rewriting in Voice Assistant Systems
Yunmo Chen, Sixing Lu, Fan Yang +3
Query rewriting (QR) systems are widely used to reduce the friction caused by errors in a spoken language understanding pipeline. However, the underlying supervised models require…
Pre-Training for Query Rewriting in A Spoken Language Understanding System
Zheng Chen, Xing Fan, Yuan Ling +2
Query rewriting (QR) is an increasingly important technique to reduce customer friction caused by errors in a spoken language understanding pipeline, where the errors originate fro…
Knowledge Distillation from Internal Representations
Gustavo Aguilar, Yuan Ling, Yu Zhang +3
Knowledge distillation is typically conducted by training a small model (the student) to mimic a large and cumbersome model (the teacher). The idea is to compress the knowledge fro…
End-to-end Anchored Speech Recognition
Yiming Wang, Xing Fan, I-Fan Chen +3
Voice-controlled house-hold devices, like Amazon Echo or Google Home, face the problem of performing speech recognition of device-directed speech in the presence of interfering bac…
Transfer Learning for Neural Semantic Parsing
Xing Fan, Emilio Monti, Lambert Mathias +1
The goal of semantic parsing is to map natural language to a machine interpretable meaning representation language (MRL). One of the constraints that limits full exploration of dee…