895 citations · 1.4k across the 40 of their papers we have counts for
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Robustness of Learning from Task Instructions
Jiasheng Gu, Hongyu Zhao, Hanzi Xu +3
Traditional supervised learning mostly works on individual tasks and requires training on a large set of task-specific examples. This paradigm seriously hinders the development of…
Learning to Select from Multiple Options
Jiangshu Du, Wenpeng Yin, Congying Xia +1
Many NLP tasks can be regarded as a selection problem from a set of options, such as classification tasks, multi-choice question answering, etc. Textual entailment (TE) has been sh…
OpenStance: Real-world Zero-shot Stance Detection
Hanzi Xu, Slobodan Vucetic, Wenpeng Yin
Prior studies of zero-shot stance detection identify the attitude of texts towards unseen topics occurring in the same document corpus. Such task formulation has three limitations:…
Anti-Overestimation Dialogue Policy Learning for Task-Completion Dialogue System
Chang Tian, Wenpeng Yin, Marie-Francine Moens
A dialogue policy module is an essential part of task-completion dialogue systems. Recently, increasing interest has focused on reinforcement learning (RL)-based dialogue policy. I…
ConTinTin: Continual Learning from Task Instructions
Wenpeng Yin, Jia Li, Caiming Xiong
The mainstream machine learning paradigms for NLP often work with two underlying presumptions. First, the target task is predefined and static; a system merely needs to learn to so…
Converse: A Tree-Based Modular Task-Oriented Dialogue System
Tian Xie, Xinyi Yang, Angela S. Lin +13
Creating a system that can have meaningful conversations with humans to help accomplish tasks is one of the ultimate goals of Artificial Intelligence (AI). It has defined the meani…
Ultra-fine Entity Typing with Indirect Supervision from Natural Language Inference
Bangzheng Li, Wenpeng Yin, Muhao Chen
The task of ultra-fine entity typing (UFET) seeks to predict diverse and free-form words or phrases that describe the appropriate types of entities mentioned in sentences. A key ch…