Search Results for author:
Found 12 papers, 2 papers with code
Weakly Supervised Subevent Knowledge Acquisition
We first obtain the initial set of event pairs that are likely to have the subevent relation, by exploiting two observations that 1) subevents are temporally contained by the parent event, and 2) the definitions of the parent event can be used to further guide the identification of subevents.
Perturbation-Based Two-Stage Multi-Domain Active Learning
Active Learning (AL) presents an encouraging solution to this issue by annotating a smaller number of highly informative instances, thereby reducing the labeling effort.
Pareto Optimization for Active Learning under Out-of-Distribution Data Scenarios
In this paper, we propose a sampling scheme, Monte-Carlo Pareto Optimization for Active Learning (POAL), which selects optimal subsets of unlabeled samples with fixed batch size from the unlabeled data pool.
Saliency Attack: Towards Imperceptible Black-box Adversarial Attack
In this paper, we propose to restrict the perturbations to a small salient region to generate adversarial examples that can hardly be perceived.
Imperceptible Black-box Attack via Refining in Salient Region
To address this issue, in this paper we propose to use segmentation priors for black-box attacks such that the perturbations are limited in the salient region.
A Regularization Approach for Incorporating Event Knowledge and Coreference Relations into Neural Discourse Parsing
We argue that external commonsense knowledge and linguistic constraints need to be incorporated into neural network models for mitigating data sparsity issues and further improving the performance of discourse parsing.
Building Context-aware Clause Representations for Situation Entity Type Classification
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 applications.
Fine-grained Structure-based News Genre Categorization
Journalists usually organize and present the contents of a news article following a well-defined structure.
Improving Implicit Discourse Relation Classification by Modeling Inter-dependencies of Discourse Units in a Paragraph
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 overall paragraph-level discourse structure.
General Classification
Implicit Discourse Relation Classification
+2
Using Context Events in Neural Network Models for Event Temporal Status Identification
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.
Online Deception Detection Refueled by Real World Data Collection
The lack of large realistic datasets presents a bottleneck in online deception detection studies.
