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Randomized Asymmetric Chain of LoRA: The First Meaningful Theoretical Framework for Low-Rank Adaptation

Fine-tuning has become a popular approach to adapting large foundational models to specific tasks. As the size of models and datasets …

Grigory Malinovsky, Umberto Michieli, Hasan Abed Al Kader Hammoud, Taha Ceritli, Hayder Elesedy, Mete Ozay, Peter Richtárik

Model Merging and Safety Alignment: One Bad Model Spoils the Bunch

Merging Large Language Models (LLMs) is a cost-effective technique for combining multiple expert LLMs into a single versatile model, …

Hasan Abed Al Kader Hammoud, Umberto Michieli, Fabio Pizzati, Philip Torr, Adel Bibi, Bernard Ghanem, Mete Ozay

Look Listen and Attack: Backdoor Attacks Against Video Action Recognition

Deep neural networks (DNNs) are vulnerable to a class of attacks called “backdoor attacks,” which create an association …

Hasan Abed Al Kader Hammoud, Shuming Liu, Mohammed Alkhrashi, Fahad Albalawi, Bernard Ghanem

Towards Interpretable Deep Local Learning with Successive Gradient Reconciliation

Relieving the reliance of neural network training on a global back-propagation (BP) has emerged as a notable research topic due to the …

Yibo Yang, Xiaojie Li, Motasem Alfarra, Hasan Abed Al Kader Hammoud, Adel Bibi, Philip Torr, Bernard Ghanem

On Pretraining Data Diversity for Self-Supervised Learning

We explore the impact of training with more diverse datasets, characterized by the number of unique samples, on the performance of …

Hasan Abed Al Kader Hammoud, Tuhin Das, Fabio Pizzati, Philip Torr, Adel Bibi, Bernard Ghanem

SynthCLIP: Are We Ready for a Fully Synthetic CLIP Training?

We present SynthCLIP, a CLIP model trained on entirely synthetic text-image pairs. Leveraging recent text-to-image (TTI) networks and …

Hasan Abed Al Kader Hammoud, Hani Itani, Fabio Pizzati, Philip Torr, Adel Bibi, Bernard Ghanem

CAMEL: Communicative Agents for "Mind" Exploration of Large Scale Language Model Society

The rapid advancement of conversational and chat-based language models has led to remarkable progress in complex task-solving. However, …

Guohao Li, Hasan Abed Al Kader Hammoud, Hani Itani, Dmitrii Khizbullin, Bernard Ghanem

CAMEL: Communicative Agents for "Mind" Exploration of Large Scale Language Model Society

Rapid Adaptation in Online Continual Learning: Are We Evaluating It Right?

We revisit the common practice of evaluating adaptation of Online Continual Learning (OCL) algorithms through the metric of online …

Hasan Abed Al Kader Hammoud, Ameya Prabhu, Ser-Nam Lim, Philip H. S. Torr, Adel Bibi, Bernard Ghanem

Rapid Adaptation in Online Continual Learning: Are We Evaluating It Right?

Mindstorms in Natural Language-Based Societies of Mind

Both Minskys society of mind and Schmidhubers learning to think inspire diverse societies of large multimodal neural networks (NNs) …

Mingchen Zhuge, Haozhe Liu, Francesco Faccio, Dylan R. Ashley, Róbert Csordás, Anand Gopalakrishnan, Abdullah Hamdi, Hasan Abed Al Kader Hammoud, Vincent Herrmann, Kazuki Irie, Louis Kirsch, Bing Li, Guohao Li, Shuming Liu, Jinjie Mai, Piotr Piękos, Aditya Ramesh, Imanol Schlag, Weimin Shi, Aleksandar Stanić, Wenyi Wang, Yuhui Wang, Mengmeng Xu, Deng-Ping Fan, Bernard Ghanem, Jürgen Schmidhuber

Mindstorms in Natural Language-Based Societies of Mind

Don't FREAK Out: A Frequency-Inspired Approach to Detecting Backdoor Poisoned Samples in DNNs

In this paper, we investigate the frequency sensitivity of Deep Neural Networks (DNNs) when presented with clean samples versus …

Hasan Abed Al Kader Hammoud, Adel Bibi, Philip H.S. Torr, Bernard Ghanem

Don't FREAK Out: A Frequency-Inspired Approach to Detecting Backdoor Poisoned Samples in DNNs