Search Results for author:
Found 8 papers, 3 papers with code
CASE 2021 Task 2: Zero-Shot Classification of Fine-Grained Sociopolitical Events with Transformer Models
We introduce a method for the classification of texts into fine-grained categories of sociopolitical events.
The Ordered Matrix Dirichlet for State-Space Models
For discrete data, SSMs commonly do so through a state-to-action emission matrix and a state-to-state transition matrix.
Regressing Location on Text for Probabilistic Geocoding
Text data are an important source of detailed information about social and political events.
Few-Shot Upsampling for Protest Size Detection
We propose a new task and dataset for a common problem in social science research: "upsampling" coarse document labels to fine-grained labels or spans.
Seeing the Forest and the Trees: Detection and Cross-Document Coreference Resolution of Militarized Interstate Disputes
Within a corpus of documents, these automated systems are unable to link event references -- recognize singular events across multiple sentences or documents.
coreference-resolution
Cross Document Coreference Resolution
+1
Multitask Models for Supervised Protests Detection in Texts
The CLEF 2019 ProtestNews Lab tasks participants to identify text relating to political protests within larger corpora of news data.
Sequence Aggregation Rules for Anomaly Detection in Computer Network Traffic
We evaluate methods for applying unsupervised anomaly detection to cybersecurity applications on computer network traffic data, or flow.
Network Traffic Anomaly Detection Using Recurrent Neural Networks
By learning a model that is specific to each network, yet generalized to typical computer-to-computer traffic within and outside the network, a language model is able to identify sequences of network activity that are outliers with respect to the model.
