9 citations · 21 across the 42 of their papers we have counts for
11 papers · 1 filter
DLCR: A Generative Data Expansion Framework via Diffusion for Clothes-Changing Person Re-ID
Nyle Siddiqui, Florinel Alin Croitoru, Gaurav Kumar Nayak +2
With the recent exhibited strength of generative diffusion models, an open research question is if images generated by these models can be used to learn better visual representatio…
Deepfake Media Generation and Detection in the Generative AI Era: A Survey and Outlook
Florinel-Alin Croitoru, Andrei-Iulian Hiji, Vlad Hondru +7
We survey deepfake generation and detection techniques, covering all deepfake media types: image, video, audio and multimodal content. We identify various kinds of deepfakes and co…
Multi-Level Feature Distillation of Joint Teachers Trained on Distinct Image Datasets
Adrian Iordache, Bogdan Alexe, Radu Tudor Ionescu
We propose a novel teacher-student framework to distill knowledge from multiple teachers trained on distinct datasets. Each teacher is first trained from scratch on its own dataset…
CBM: Curriculum by Masking
Andrei Jarca, Florinel-Alin Croitoru, Radu Tudor Ionescu
We propose Curriculum by Masking (CBM), a novel state-of-the-art curriculum learning strategy that effectively creates an easy-to-hard training schedule via patch (token) masking,…
PoPreRo: A New Dataset for Popularity Prediction of Romanian Reddit Posts
Ana-Cristina Rogoz, Maria Ilinca Nechita, Radu Tudor Ionescu
We introduce PoPreRo, the first dataset for Popularity Prediction of Romanian posts collected from Reddit. The PoPreRo dataset includes a varied compilation of post samples from fi…
PQPP: A Joint Benchmark for Text-to-Image Prompt and Query Performance Prediction
Eduard Poesina, Adriana Valentina Costache, Adrian-Gabriel Chifu +2
Text-to-image generation has recently emerged as a viable alternative to text-to-image retrieval, driven by the visually impressive results of generative diffusion models. Although…
Curriculum Direct Preference Optimization for Diffusion and Consistency Models
Florinel-Alin Croitoru, Vlad Hondru, Radu Tudor Ionescu +2
Direct Preference Optimization (DPO) has been proposed as an effective and efficient alternative to reinforcement learning from human feedback (RLHF). In this paper, we propose a n…
A Novel Cartography-Based Curriculum Learning Method Applied on RoNLI: The First Romanian Natural Language Inference Corpus
Eduard Poesina, Cornelia Caragea, Radu Tudor Ionescu
Natural language inference (NLI), the task of recognizing the entailment relationship in sentence pairs, is an actively studied topic serving as a proxy for natural language unders…
UnibucLLM: Harnessing LLMs for Automated Prediction of Item Difficulty and Response Time for Multiple-Choice Questions
Ana-Cristina Rogoz, Radu Tudor Ionescu
This work explores a novel data augmentation method based on Large Language Models (LLMs) for predicting item difficulty and response time of retired USMLE Multiple-Choice Question…
Weight Copy and Low-Rank Adaptation for Few-Shot Distillation of Vision Transformers
Diana-Nicoleta Grigore, Mariana-Iuliana Georgescu, Jon Alvarez Justo +3
Few-shot knowledge distillation recently emerged as a viable approach to harness the knowledge of large-scale pre-trained models, using limited data and computational resources. In…
Cascaded Cross-Modal Transformer for Audio-Textual Classification
Nicolae-Catalin Ristea, Andrei Anghel, Radu Tudor Ionescu
Speech classification tasks often require powerful language understanding models to grasp useful features, which becomes problematic when limited training data is available. To att…