12 citations · 25 across the 8 of their papers we have counts for
8 papers
Perturbation-Based Two-Stage Multi-Domain Active Learning
Rui He, Zeyu Dai, Shan He +1
In multi-domain learning (MDL) scenarios, high labeling effort is required due to the complexity of collecting data from various domains. Active Learning (AL) presents an encouragi…
Pareto Optimization for Active Learning under Out-of-Distribution Data Scenarios
Xueying Zhan, Zeyu Dai, Qingzhong Wang +4
Pool-based Active Learning (AL) has achieved great success in minimizing labeling cost by sequentially selecting informative unlabeled samples from a large unlabeled data pool and…
Saliency Attack: Towards Imperceptible Black-box Adversarial Attack
Zeyu Dai, Shengcai Liu, Ke Tang +1
Deep neural networks are vulnerable to adversarial examples, even in the black-box setting where the attacker is only accessible to the model output. Recent studies have devised ef…
PYInfer: Deep Learning Semantic Type Inference for Python Variables
Siwei Cui, Gang Zhao, Zeyu Dai +3
Python type inference is challenging in practice. Due to its dynamic properties and extensive dependencies on third-party libraries without type annotations, the performance of tra…
Building Context-aware Clause Representations for Situation Entity Type Classification
Zeyu Dai, Ruihong Huang
Capabilities to categorize a clause based on the type of situation entity (e.g., events, states and generic statements) the clause introduces to the discourse can benefit many NLP…
Improving Implicit Discourse Relation Classification by Modeling Inter-dependencies of Discourse Units in a Paragraph
Zeyu Dai, Ruihong Huang
We argue that semantic meanings of a sentence or clause can not be interpreted independently from the rest of a paragraph, or independently from all discourse relations and the ove…
Using Context Events in Neural Network Models for Event Temporal Status Identification
Zeyu Dai, Wenlin Yao, Ruihong Huang
Focusing on the task of identifying event temporal status, we find that events directly or indirectly governing the target event in a dependency tree are most important contexts. T…
Online Deception Detection Refueled by Real World Data Collection
Wenlin Yao, Zeyu Dai, Ruihong Huang +1
The lack of large realistic datasets presents a bottleneck in online deception detection studies. In this paper, we apply a data collection method based on social network analysis…