Papers by Ahmad Chamma

1 papers
MixtureKit: A General Framework for Composing, Training, and Visualizing Mixture-of-Experts Models (2026.acl-demo)

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Challenge: MixtureKit is a modular open-source framework for constructing, training, and analyzing Mixture-of-Experts (MoE) models from arbitrary pre-trained or fine-tuned checkpoints.
Approach: They propose a modular open-source framework for constructing, training, and analyzing Mixture-of-Experts (MoE) models from arbitrary pre-trained or fine-tuned checkpoints.
Outcome: Experiments on multilingual code-switched (Arabic–Latin) show that BTX models built with MixtureKit outperform dense baselines across multiple benchmarks.

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