20 citations · 39 across the 9 of their papers we have counts for
10 papers
TailLoR: Protecting Principal Components in Parameter-Efficient Continual Learning
Marius Dragoi, Ioana Pintilie, Alexandra Dragomir +2
Parameter-efficient finetuning methods based on spectral decomposition have enabled progress in Continual Learning. In this paper we introduce TailLoR, which utilizes the singular…
JumpLoRA: Sparse Adapters for Continual Learning in Large Language Models
Alexandra Dragomir, Ioana Pintilie, Antonio Barbalau +6
Adapter-based methods have become a cost-effective approach to continual learning (CL) for Large Language Models (LLMs), by sequentially learning a low-rank update matrix for each…
Rethinking Sparse Autoencoders: Select-and-Project for Fairness and Control from Encoder Features Alone
Antonio Bărbălau, Cristian Daniel Păduraru, Teodor Poncu +2
Sparse Autoencoders (SAEs) are widely employed for mechanistic interpretability and model steering. Within this context, steering is by design performed by means of decoding altere…
Curriculum-enhanced GroupDRO: Challenging the Norm of Avoiding Curriculum Learning in Subpopulation Shift Setups
Antonio Barbalau
In subpopulation shift scenarios, a Curriculum Learning (CL) approach would only serve to imprint the model weights, early on, with the easily learnable spurious correlations featu…
SSMTL++: Revisiting Self-Supervised Multi-Task Learning for Video Anomaly Detection
Antonio Barbalau, Radu Tudor Ionescu, Mariana-Iuliana Georgescu +6
A self-supervised multi-task learning (SSMTL) framework for video anomaly detection was recently introduced in literature. Due to its highly accurate results, the method attracted…
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…
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…
Anomaly Detection in Video via Self-Supervised and Multi-Task Learning
Mariana-Iuliana Georgescu, Antonio Barbalau, Radu Tudor Ionescu +3
Anomaly detection in video is a challenging computer vision problem. Due to the lack of anomalous events at training time, anomaly detection requires the design of learning methods…
Black-Box Ripper: Copying black-box models using generative evolutionary algorithms
Antonio Barbalau, Adrian Cosma, Radu Tudor Ionescu +1
We study the task of replicating the functionality of black-box neural models, for which we only know the output class probabilities provided for a set of input images. We assume b…
A Generic and Model-Agnostic Exemplar Synthetization Framework for Explainable AI
Antonio Barbalau, Adrian Cosma, Radu Tudor Ionescu +1
With the growing complexity of deep learning methods adopted in practical applications, there is an increasing and stringent need to explain and interpret the decisions of such met…