15 citations · 46 across the 6 of their papers we have counts for
7 papers
CLewR: Curriculum Learning with Restarts for Machine Translation Preference Learning
Alexandra Dragomir, Florin Brad, Radu Tudor Ionescu
Large language models (LLMs) have demonstrated competitive performance in zero-shot multilingual machine translation (MT). Some follow-up works further improved MT performance via…
Time Series Anomaly Detection using Diffusion-based Models
Ioana Pintilie, Andrei Manolache, Florin Brad
Diffusion models have been recently used for anomaly detection (AD) in images. In this paper we investigate whether they can also be leveraged for AD on multivariate time series (M…
VeriDark: A Large-Scale Benchmark for Authorship Verification on the Dark Web
Andrei Manolache, Florin Brad, Antonio Barbalau +2
The DarkWeb represents a hotbed for illicit activity, where users communicate on different market forums in order to exchange goods and services. Law enforcement agencies benefit f…
AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection
Marius Dragoi, Elena Burceanu, Emanuela Haller +2
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 sc…
Rethinking the Authorship Verification Experimental Setups
Florin Brad, Andrei Manolache, Elena Burceanu +3
One of the main drivers of the recent advances in authorship verification is the PAN large-scale authorship dataset. Despite generating significant progress in the field, inconsist…
DATE: Detecting Anomalies in Text via Self-Supervision of Transformers
Andrei Manolache, Florin Brad, Elena Burceanu
Leveraging deep learning models for Anomaly Detection (AD) has seen widespread use in recent years due to superior performances over traditional methods. Recent deep methods for an…
Dataset for a Neural Natural Language Interface for Databases (NNLIDB)
Florin Brad, Radu Iacob, Ionel Hosu +1
Progress in natural language interfaces to databases (NLIDB) has been slow mainly due to linguistic issues (such as language ambiguity) and domain portability. Moreover, the lack o…