895 citations · 1.4k across the 40 of their papers we have counts for
41 papers
All Labels Together: Low-shot Intent Detection with an Efficient Label Semantic Encoding Paradigm
Jiangshu Du, Congying Xia, Wenpeng Yin +2
In intent detection tasks, leveraging meaningful semantic information from intent labels can be particularly beneficial for few-shot scenarios. However, existing few-shot intent de…
Toward Zero-Shot Instruction Following
Renze Lou, Wenpeng Yin
This work proposes a challenging yet more realistic setting for zero-shot cross-task generalization: zero-shot instruction following, presuming the existence of a paragraph-style t…
Large Language Model Instruction Following: A Survey of Progresses and Challenges
Renze Lou, Kai Zhang, Wenpeng Yin
Task semantics can be expressed by a set of input-output examples or a piece of textual instruction. Conventional machine learning approaches for natural language processing (NLP)…
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…
Event Linking: Grounding Event Mentions to Wikipedia
Xiaodong Yu, Wenpeng Yin, Nitish Gupta +1
Comprehending an article requires understanding its constituent events. However, the context where an event is mentioned often lacks the details of this event. A question arises: h…
Combining Data-driven Supervision with Human-in-the-loop Feedback for Entity Resolution
Wenpeng Yin, Shelby Heinecke, Jia Li +7
The distribution gap between training datasets and data encountered in production is well acknowledged. Training datasets are often constructed over a fixed period of time and by c…
DocNLI: A Large-scale Dataset for Document-level Natural Language Inference
Wenpeng Yin, Dragomir Radev, Caiming Xiong
Natural language inference (NLI) is formulated as a unified framework for solving various NLP problems such as relation extraction, question answering, summarization, etc. It has b…
Learning to Synthesize Data for Semantic Parsing
Bailin Wang, Wenpeng Yin, Xi Victoria Lin +1
Synthesizing data for semantic parsing has gained increasing attention recently. However, most methods require handcrafted (high-precision) rules in their generative process, hinde…
Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and System
Congying Xia, Wenpeng Yin, Yihao Feng +1
Text classification is usually studied by labeling natural language texts with relevant categories from a predefined set. In the real world, new classes might keep challenging the…
Mixup-Transformer: Dynamic Data Augmentation for NLP Tasks
Lichao Sun, Congying Xia, Wenpeng Yin +3
Mixup is the latest data augmentation technique that linearly interpolates input examples and the corresponding labels. It has shown strong effectiveness in image classification by…
Universal Natural Language Processing with Limited Annotations: Try Few-shot Textual Entailment as a Start
Wenpeng Yin, Nazneen Fatema Rajani, Dragomir Radev +2
A standard way to address different NLP problems is by first constructing a problem-specific dataset, then building a model to fit this dataset. To build the ultimate artificial in…
Pairwise Representation Learning for Event Coreference
Xiaodong Yu, Wenpeng Yin, Dan Roth
Natural Language Processing tasks such as resolving the coreference of events require understanding the relations between two text snippets. These tasks are typically formulated as…
Meta-learning for Few-shot Natural Language Processing: A Survey
Wenpeng Yin
Few-shot natural language processing (NLP) refers to NLP tasks that are accompanied with merely a handful of labeled examples. This is a real-world challenge that an AI system must…
CO-Search: COVID-19 Information Retrieval with Semantic Search, Question Answering, and Abstractive Summarization
Andre Esteva, Anuprit Kale, Romain Paulus +4
The COVID-19 global pandemic has resulted in international efforts to understand, track, and mitigate the disease, yielding a significant corpus of COVID-19 and SARS-CoV-2-related…
Adv-BERT: BERT is not robust on misspellings! Generating nature adversarial samples on BERT
Lichao Sun, Kazuma Hashimoto, Wenpeng Yin +4
There is an increasing amount of literature that claims the brittleness of deep neural networks in dealing with adversarial examples that are created maliciously. It is unclear, ho…
Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach
Wenpeng Yin, Jamaal Hay, Dan Roth
Zero-shot text classification (0Shot-TC) is a challenging NLU problem to which little attention has been paid by the research community. 0Shot-TC aims to associate an appropriate l…
Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
Jianquan Li, Xiaokang Liu, Wenpeng Yin +3
Multi-Task Learning (MTL) aims at boosting the overall performance of each individual task by leveraging useful information contained in multiple related tasks. It has shown great…
Seeing Things from a Different Angle: Discovering Diverse Perspectives about Claims
Sihao Chen, Daniel Khashabi, Wenpeng Yin +2
One key consequence of the information revolution is a significant increase and a contamination of our information supply. The practice of fact checking won't suffice to eliminate…