5 papers
Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks
Nobin Sarwar, Shubhashis Roy Dipta, Zheyuan Liu +1
With the growing adoption of VLMs, DMs, LLMs, and AFMs, these multimodal foundation models can inadvertently encode sensitive, copyrighted, biased, or unsafe cross-modal associatio…
Action-Guided Attention for Video Action Anticipation
Tsung-Ming Tai, Sofia Casarin, Andrea Pilzer +2
Anticipating future actions in videos is challenging, as the observed frames provide only evidence of past activities, requiring the inference of latent intentions to predict upcom…
Action-guided generation of 3D functionality segmentation data
Jaime Corsetti, Francesco Giuliari, Davide Boscaini +6
3D functionality segmentation aims to identify the interactive element in a 3D scene required to perform an action described in free-form language (e.g., the handle to ``Open the s…
Video Unlearning via Low-Rank Refusal Vector
Simone Facchiano, Stefano Saravalle, Matteo Migliarini +7
Video generative models achieve high-quality synthesis from natural-language prompts by leveraging large-scale web data. However, this training paradigm inherently exposes them to…
DIETA: A Decoder-only transformer-based model for Italian-English machine TrAnslation
Pranav Kasela, Marco Braga, Alessandro Ghiotto +3
In this paper, we present DIETA, a small, decoder-only Transformer model with 0.5 billion parameters, specifically designed and trained for Italian-English machine translation. We…