71 citations · 270 across the 48 of their papers we have counts for
7 papers · 1 filter
LMTurk: Few-Shot Learners as Crowdsourcing Workers in a Language-Model-as-a-Service Framework
Mengjie Zhao, Fei Mi, Yasheng Wang +4
Vast efforts have been devoted to creating high-performance few-shot learners, i.e., large-scale pretrained language models (PLMs) that perform well with little downstream task tra…
UniDS: A Unified Dialogue System for Chit-Chat and Task-oriented Dialogues
Xinyan Zhao, Bin He, Yasheng Wang +6
With the advances in deep learning, tremendous progress has been made with chit-chat dialogue systems and task-oriented dialogue systems. However, these two systems are often tackl…
Representation Memorization for Fast Learning New Knowledge without Forgetting
Fei Mi, Tao Lin, Boi Faltings
The ability to quickly learn new knowledge (e.g. new classes or data distributions) is a big step towards human-level intelligence. In this paper, we consider scenarios that requir…
SynCoBERT: Syntax-Guided Multi-Modal Contrastive Pre-Training for Code Representation
Xin Wang, Yasheng Wang, Fei Mi +7
Code representation learning, which aims to encode the semantics of source code into distributed vectors, plays an important role in recent deep-learning-based models for code inte…
CINS: Comprehensive Instruction for Few-shot Learning in Task-oriented Dialog Systems
Fei Mi, Yitong Li, Yasheng Wang +2
As labeling cost for different modules in task-oriented dialog (ToD) systems is high, a major challenge in practice is to learn different tasks with the least amount of labeled dat…
Self-training Improves Pre-training for Few-shot Learning in Task-oriented Dialog Systems
Fei Mi, Wanhao Zhou, Fengyu Cai +3
As the labeling cost for different modules in task-oriented dialog (ToD) systems is expensive, a major challenge is to train different modules with the least amount of labeled data…