Colloquium

The IDC CS Colloquium
 

Guy Gaziv - Strong and Precise Modulation of Human Percepts via Robustified ANNs

The visual object category reports of artificial neural networks (ANNs) are notoriously sensitive to tiny, adversarial image perturbations. Because human category reports (aka human percepts) are thought to be insensitive to those same small-norm perturbations — and locally stable in general — this argues that ANNs are incomplete scientific models of human visual perception. Consistent with this, we show that when small-norm image perturbations are generated by standard ANN models, human object category percepts are indeed highly stable.

22/02/2024 - 11:30

Eyal Ofek - Work-Verse: Using augmentation of user’s senses, and scene understanding to enable a more inclusive workspace

 the one hand, people may work at flexible hours, independent of traffic limitations, but on the other hand, they may need to work in makeshift spaces with less-than-optimal working conditions; applications are not flexible to their physical and social context and remote collaboration do not account for the difference between the user's conditions and capabilities.

31/07/2023 - 10:00

Eitan Yaakobi - The Applications of Constrained Systems in DNA Storage: Efficient Synthesis and DNA Labeling

DNA-based storage has attracted significant attention due to recent demonstrations of the viability of storing information in macromolecules. Given the trends in cost decreases of DNA synthesis and sequencing, it is estimated that within the next decade DNA storage may become a highly competitive archiving technology. This technology introduces new challenges in finding coding solutions to address various problems associated with the implementation of DNA-based storage systems.

15/06/2023 - 13:30

Alon Kipnis - Detecting Some Human Edits of AI-Generated Text with Information Theory and Higher Criticism

We address the question of whether a given article is the output of a generative language model or perhaps includes some significant edits by a different author, possibly a human. For this problem, we develop a detection method that involves many perplexity tests for the origin of individual sentences, combining these multiple tests into a global test of significance using Higher Criticism (HC). As a by-product, we can identify sentences or other text chunks suspected as generated by a different mechanism than the language model.

18/05/2023 - 13:30

Aviv Gaon - Through the Looking Glass: The Hidden Impacts of Data Regulation

Developing Artificial Intelligence systems require access to masses of data. This notion is common knowledge for computer engineers and data analysts. Data regulation is essential to ensure our safety, privacy, and ownership rights. Regulating the amount of data, the quality, and the priority with which organizations can access data are paramount. However, as with other areas of law, regulation could result in unwarranted results. One impact of data regulation is incentivizing the usage of low-quality data that often demonstrates bias.

01/06/2023 - 13:30