17 citations · 29 across the 8 of their papers we have counts for
8 papers
Connecting online criminal behavior with machine learning: Using authorship attribution to analyze and link potential online traffickers
Vageesh Kumar Saxena
This research investigated how online criminal activities can be better understood and connected using data-driven machine learning methods. Many illegal activities, such as human…
Understanding and Analyzing Model Robustness and Knowledge-Transfer in Multilingual Neural Machine Translation using TX-Ray
Vageesh Saxena, Sharid Loáiciga, Nils Rethmeier
Neural networks have demonstrated significant advancements in Neural Machine Translation (NMT) compared to conventional phrase-based approaches. However, Multilingual Neural Machin…
MATCHED: Multimodal Authorship-Attribution To Combat Human Trafficking in Escort-Advertisement Data
Vageesh Saxena, Benjamin Bashpole, Gijs Van Dijck +1
Human trafficking (HT) remains a critical issue, with traffickers increasingly leveraging online escort advertisements (ads) to advertise victims anonymously. Existing detection me…
ColBERT-XM: A Modular Multi-Vector Representation Model for Zero-Shot Multilingual Information Retrieval
Antoine Louis, Vageesh Saxena, Gijs van Dijck +1
State-of-the-art neural retrievers predominantly focus on high-resource languages like English, which impedes their adoption in retrieval scenarios involving other languages. Curre…
IDTraffickers: An Authorship Attribution Dataset to link and connect Potential Human-Trafficking Operations on Text Escort Advertisements
Vageesh Saxena, Benjamin Bashpole, Gijs Van Dijck +1
Human trafficking (HT) is a pervasive global issue affecting vulnerable individuals, violating their fundamental human rights. Investigations reveal that a significant number of HT…
VendorLink: An NLP approach for Identifying & Linking Vendor Migrants & Potential Aliases on Darknet Markets
Vageesh Saxena, Nils Rethmeier, Gijs Van Dijck +1
The anonymity on the Darknet allows vendors to stay undetected by using multiple vendor aliases or frequently migrating between markets. Consequently, illegal markets and their con…
TX-Ray: Quantifying and Explaining Model-Knowledge Transfer in (Un-)Supervised NLP
Nils Rethmeier, Vageesh Kumar Saxena, Isabelle Augenstein
While state-of-the-art NLP explainability (XAI) methods focus on explaining per-sample decisions in supervised end or probing tasks, this is insufficient to explain and quantify mo…
PredNet and Predictive Coding: A Critical Review
Roshan Rane, Edit Szügyi, Vageesh Saxena +2
PredNet, a deep predictive coding network developed by Lotter et al., combines a biologically inspired architecture based on the propagation of prediction error with self-supervise…