Search Results for author:
Found 8 papers, 4 papers with code
VeriDark: A Large-Scale Benchmark for Authorship Verification on the Dark Web
The DarkWeb represents a hotbed for illicit activity, where users communicate on different market forums in order to exchange goods and services.
AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection
Analyzing the distribution shift of data is a growing research direction in nowadays Machine Learning (ML), leading to emerging new benchmarks that focus on providing a suitable scenario for studying the generalization properties of ML models.
Ranked #1 on
Unsupervised Anomaly Detection
on AnoShift
Rethinking the Authorship Verification Experimental Setups
One of the main drivers of the recent advances in authorship verification is the PAN large-scale authorship dataset.
DATE: Detecting Anomalies in Text via Self-Supervision of Transformers
Leveraging deep learning models for Anomaly Detection (AD) has seen widespread use in recent years due to superior performances over traditional methods.
Ranked #1 on
Anomaly Detection
on AG News
Neural Approaches for Natural Language Interfaces to Databases: A Survey
A natural language interface to databases (NLIDB) enables users without technical expertise to easily access information from relational databases.
Natural Language Interface for Databases Using a Dual-Encoder Model
We propose a sketch-based two-step neural model for generating structured queries (SQL) based on a user{'}s request in natural language.
Neural Paraphrase Generation using Transfer Learning
Progress in statistical paraphrase generation has been hindered for a long time by the lack of large monolingual parallel corpora.
Dataset for a Neural Natural Language Interface for Databases (NNLIDB)
Progress in natural language interfaces to databases (NLIDB) has been slow mainly due to linguistic issues (such as language ambiguity) and domain portability.
