4 citations · 8 across the 6 of their papers we have counts for
5 papers · 1 filter
EfficientVLM: Fast and Accurate Vision-Language Models via Knowledge Distillation and Modal-adaptive Pruning
Tiannan Wang, Wangchunshu Zhou, Yan Zeng +1
Pre-trained vision-language models (VLMs) have achieved impressive results in a range of vision-language tasks. However, popular VLMs usually consist of hundreds of millions of par…
Open-Domain Dialogue Generation Based on Pre-trained Language Models
Yan Zeng, Jian-Yun Nie
Pre-trained language models have been successfully used in response generation for open-domain dialogue. Four main frameworks have been proposed: (1) Transformer-ED using Transform…
Multi-Domain Dialogue State Tracking based on State Graph
Yan Zeng, Jian-Yun Nie
We investigate the problem of multi-domain Dialogue State Tracking (DST) with open vocabulary, which aims to extract the state from the dialogue. Existing approaches usually concat…
Jointly Optimizing State Operation Prediction and Value Generation for Dialogue State Tracking
Yan Zeng, Jian-Yun Nie
We investigate the problem of multi-domain Dialogue State Tracking (DST) with open vocabulary. Existing approaches exploit BERT encoder and copy-based RNN decoder, where the encode…
A Simple and Efficient Multi-Task Learning Approach for Conditioned Dialogue Generation
Yan Zeng, Jian-Yun Nie
Conditioned dialogue generation suffers from the scarcity of labeled responses. In this work, we exploit labeled non-dialogue text data related to the condition, which are much eas…