418 citations · 578 across the 22 of their papers we have counts for
23 papers
DataComp-VLM: Improved Open Datasets for Vision-Language Models
Matteo Farina, Vishaal Udandarao, Thao Nguyen +33
Building performant Vision-Language Models (VLMs) requires carefully curating large-scale training datasets, yet the community lacks systematic benchmarks for evaluating such curat…
QuanBench+: A Unified Multi-Framework Benchmark for LLM-Based Quantum Code Generation
Ali Slim, Haydar Hamieh, Jawad Kotaich +5
Large Language Models (LLMs) are increasingly used for code generation, yet quantum code generation is still evaluated mostly within single frameworks, making it difficult to separ…
LongCoT: Benchmarking Long-Horizon Chain-of-Thought Reasoning
Sumeet Ramesh Motwani, Daniel Nichols, Charles London +17
As language models are increasingly deployed for complex autonomous tasks, their ability to reason accurately over longer horizons becomes critical. An essential component of this…
Unforgotten Safety: Preserving Safety Alignment of Large Language Models with Continual Learning
Lama Alssum, Hani Itani, Hasan Abed Al Kader Hammoud +3
The safety alignment of large language models (LLMs) is becoming increasingly important with their democratization. In this paper, we study the safety degradation that comes with a…
AraLingBench A Human-Annotated Benchmark for Evaluating Arabic Linguistic Capabilities of Large Language Models
Mohammad Zbeeb, Hasan Abed Al Kader Hammoud, Sina Mukalled +5
We present AraLingBench: a fully human annotated benchmark for evaluating the Arabic linguistic competence of large language models (LLMs). The benchmark spans five core categories…
Forget Less, Retain More: A Lightweight Regularizer for Rehearsal-Based Continual Learning
Lama Alssum, Hasan Abed Al Kader Hammoud, Motasem Alfarra +2
Deep neural networks suffer from catastrophic forgetting, where performance on previous tasks degrades after training on a new task. This issue arises due to the model's tendency t…
Hala Technical Report: Building Arabic-Centric Instruction & Translation Models at Scale
Hasan Abed Al Kader Hammoud, Mohammad Zbeeb, Bernard Ghanem
We present Hala, a family of Arabic-centric instruction and translation models built with our translate-and-tune pipeline. We first compress a strong AREN teacher…
Reasoning Vectors: Transferring Chain-of-Thought Capabilities via Task Arithmetic
Mohammad Zbeeb, Hasan Abed Al Kader Hammoud, Bernard Ghanem
Large language models often require costly optimization, such as reinforcement learning, to master complex reasoning tasks. This work demonstrates that reasoning ability, once lear…
An Embarrassingly Simple Defense Against LLM Abliteration Attacks
Harethah Abu Shairah, Hasan Abed Al Kader Hammoud, Bernard Ghanem +1
Large language models (LLMs) are typically aligned to refuse harmful instructions through safety fine-tuning. A recent attack, termed abliteration, identifies and suppresses the si…
DiffCLIP: Differential Attention Meets CLIP
Hasan Abed Al Kader Hammoud, Bernard Ghanem
We propose DiffCLIP, a novel vision-language model that extends the differential attention mechanism to CLIP architectures. Differential attention was originally developed for larg…
On the Importance of Pretraining Data Alignment for Atomic Property Prediction
Yasir Ghunaim, Hasan Abed Al Kader Hammoud, Bernard Ghanem
This paper challenges the recent paradigm in atomic property prediction that links progress to growing dataset sizes and computational resources. We show that pretraining on a care…
Randomized Asymmetric Chain of LoRA: The First Meaningful Theoretical Framework for Low-Rank Adaptation
Grigory Malinovsky, Umberto Michieli, Hasan Abed Al Kader Hammoud +4
Fine-tuning has become a popular approach to adapting large foundational models to specific tasks. As the size of models and datasets grows, parameter-efficient fine-tuning techniq…
Towards Interpretable Deep Local Learning with Successive Gradient Reconciliation
Yibo Yang, Xiaojie Li, Motasem Alfarra +4
Relieving the reliance of neural network training on a global back-propagation (BP) has emerged as a notable research topic due to the biological implausibility and huge memory con…
From Categories to Classifiers: Name-Only Continual Learning by Exploring the Web
Ameya Prabhu, Hasan Abed Al Kader Hammoud, Ser-Nam Lim +3
Continual Learning (CL) often relies on the availability of extensive annotated datasets, an assumption that is unrealistically time-consuming and costly in practice. We explore a…
Rapid Adaptation in Online Continual Learning: Are We Evaluating It Right?
Hasan Abed Al Kader Hammoud, Ameya Prabhu, Ser-Nam Lim +3
We revisit the common practice of evaluating adaptation of Online Continual Learning (OCL) algorithms through the metric of online accuracy, which measures the accuracy of the mode…
Mindstorms in Natural Language-Based Societies of Mind
Mingchen Zhuge, Haozhe Liu, Francesco Faccio +23
Both Minsky's "society of mind" and Schmidhuber's "learning to think" inspire diverse societies of large multimodal neural networks (NNs) that solve problems by interviewing each o…
Real-Time Evaluation in Online Continual Learning: A New Hope
Yasir Ghunaim, Adel Bibi, Kumail Alhamoud +5
Current evaluations of Continual Learning (CL) methods typically assume that there is no constraint on training time and computation. This is an unrealistic assumption for any real…
CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society
Guohao Li, Hasan Abed Al Kader Hammoud, Hani Itani +2
The rapid advancement of chat-based language models has led to remarkable progress in complex task-solving. However, their success heavily relies on human input to guide the conver…
Computationally Budgeted Continual Learning: What Does Matter?
Ameya Prabhu, Hasan Abed Al Kader Hammoud, Puneet Dokania +4
Continual Learning (CL) aims to sequentially train models on streams of incoming data that vary in distribution by preserving previous knowledge while adapting to new data. Current…
Generalizability of Adversarial Robustness Under Distribution Shifts
Kumail Alhamoud, Hasan Abed Al Kader Hammoud, Motasem Alfarra +1
Recent progress in empirical and certified robustness promises to deliver reliable and deployable Deep Neural Networks (DNNs). Despite that success, most existing evaluations of DN…
PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies
Guocheng Qian, Yuchen Li, Houwen Peng +4
PointNet++ is one of the most influential neural architectures for point cloud understanding. Although the accuracy of PointNet++ has been largely surpassed by recent networks such…
ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation Learning
Guocheng Qian, Hasan Abed Al Kader Hammoud, Guohao Li +2
Access to 3D point cloud representations has been widely facilitated by LiDAR sensors embedded in various mobile devices. This has led to an emerging need for fast and accurate poi…
On the Decision Boundaries of Neural Networks: A Tropical Geometry Perspective
Motasem Alfarra, Adel Bibi, Hasan Hammoud +2
This work tackles the problem of characterizing and understanding the decision boundaries of neural networks with piecewise linear non-linearity activations. We use tropical geomet…