6 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…
A mathematical framework for centromere-aware evaluation of human genome assemblies
Luca Franco, Matteo Migliarini, Matteo Tommaso Ungaro +6
Accurate evaluation of genome assemblies within highly repetitive regions, such as centromeres, remains a major open challenge in genomics. Conventional benchmarking relies on sequ…
Robotic Policy Adaptation via Weight-Space Meta-Learning
Christian Bianchi, Siamak Yousefi, Alessio Sampieri +4
Vision-Language-Action (VLA) models are emerging as a promising paradigm for robotic manipulation, enabling general-purpose policies trained from large corpora of demonstrations an…
Not All Latent Spaces Are Flat: Hyperbolic Concept Control
Maria Rosaria Briglia, Simone Facchiano, Paolo Cursi +6
As modern text-to-image (T2I) models draw closer to synthesizing highly realistic content, the threat of unsafe content generation grows, and it becomes paramount to exercise contr…
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…
LongCodeBench: Evaluating Coding LLMs at 1M Context Windows
Stefano Rando, Luca Romani, Alessio Sampieri +5
Context lengths for models have grown rapidly, from thousands to millions of tokens in just a few years. The extreme context sizes of modern long-context models have made it diffic…