9 citations · 11 across the 6 of their papers we have counts for
7 papers
Safety Reconstructed: Generative Modeling via Masked Diffusion Builds Strong Safety Guardrails
Gert Lek, Abele Malan, Chaoyi Zhu +3
Guard models are the last line of defense between a language model and a harmful output, yet their training objective is surprisingly narrow. Existing guards learn to predict a sin…
A Network Science Perspective on Evaluating Deep Graph Generative Models
Tianrui Mao, Abele Malan, Megha Khosla +2
Traditional network models from network science, such as the Erdos-Renyi and configuration models, generate random networks that reproduce few selected topological properties obser…
Detecting Diffusion-Generated Time Series Under Generator Shift
Zhi Wen Soi, Aditya Shankar, Gert Lek +4
The boundary between real and diffusion-generated time series is becoming increasingly difficult to draw, yet detection in this domain remains underexplored, especially when the ge…
Federated Time Series Generation on Feature and Temporally Misaligned Data
Zhi Wen Soi, Chenrui Fan, Aditya Shankar +2
Distributed time series data presents a challenge for federated learning, as clients often possess different feature sets and have misaligned time steps. Existing federated time se…
Asynchronous Byzantine Federated Learning
Bart Cox, Abele Mălan, Lydia Y. Chen +1
Federated learning (FL) enables a set of geographically distributed clients to collectively train a model through a server. Classically, the training process is synchronous, but ca…
CCBNet: Confidential Collaborative Bayesian Networks Inference
Abele Mălan, Jérémie Decouchant, Thiago Guzella +1
Effective large-scale process optimization in manufacturing industries requires close cooperation between different human expert parties who encode their knowledge of related domai…
DALLMi: Domain Adaption for LLM-based Multi-label Classifier
Miruna Beţianu, Abele Mălan, Marco Aldinucci +2
Large language models (LLMs) increasingly serve as the backbone for classifying text associated with distinct domains and simultaneously several labels (classes). When encountering…