4 papers
Neurosymbolic Learning for Inference-Time Argumentation
Gabriel Freedman, Adam Dejl, Adam Gould +4
Claim verification is an important problem in high-stakes settings, including health and finance. When information underpinning claims is incomplete or conflicting, uncertain answe…
Selective Fine-Tuning for Targeted and Robust Concept Unlearning
Mansi, Avinash Kori, Francesca Toni +1
Text guided diffusion models are used by millions of users, but can be easily exploited to produce harmful content. Concept unlearning methods aim at reducing the models' likelihoo…
Understanding Dementia Speech Alignment with Diffusion-Based Image Generation
Mansi, Anastasios Lepipas, Dominika Woszczyk +2
Text-to-image models generate highly realistic images based on natural language descriptions and millions of users use them to create and share images online. While it is expected…
AmalREC: A Dataset for Relation Extraction and Classification Leveraging Amalgamation of Large Language Models
Mansi, Pranshu Pandya, Mahek Bhavesh Vora +2
Existing datasets for relation classification and extraction often exhibit limitations such as restricted relation types and domain-specific biases. This work presents a generic fr…