4 papers
Paved with True Intents: Intent-Aware Training Improves LLM Safety Classification Across Training Regimes
Jeremias Ferrao, Niclas Müller-Hof, Iustin Sîrbu +2
We argue that safety classifiers should model user intent as an explicit signal between the prompt and the final label. To study this, we introduce AIMS, a human-annotated dataset…
Semi-Supervised Learning for Large Language Models Safety and Content Moderation
Eduard Stefan Dinuta, Iustin Sirbu, Traian Rebedea
Safety for Large Language Models (LLMs) has been an ongoing research focus since their emergence and is even more relevant nowadays with the increasing capacity of those models. Cu…
MultiMatch: Multihead Consistency Regularization Matching for Semi-Supervised Text Classification
Iustin Sirbu, Robert-Adrian Popovici, Cornelia Caragea +2
We introduce MultiMatch, a novel semi-supervised learning (SSL) algorithm combining the paradigms of co-training and consistency regularization with pseudo-labeling. At its core, M…
GIT-CXR: End-to-End Transformer for Chest X-Ray Report Generation
Iustin Sîrbu, Iulia-Renata Sîrbu, Jasmina Bogojeska +1
Medical imaging is crucial for diagnosing, monitoring, and treating medical conditions. The medical reports of radiology images are the primary medium through which medical profess…