Hamza Harkous — accepted AI-conference papers

2026

Reasoning-Driven Synthetic Data Generation and Evaluation

Tim Davidson, Benoit Seguin, Enrico Bacis, Cesar Ilharco, Hamza Harkous

ICML 2026poster

Although many AI applications of interest require specialized multi-modal models, relevant data to train such models is inherently scarce or inaccessible. Filling these gaps with human annotators is prohibitively expensive, error-prone, and time-consuming, leading model builders to increasingly cons…

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2020

Have Your Text and Use It Too! End-to-End Neural Data-to-Text Generation with Semantic Fidelity

Hamza Harkous, Isabel Groves, Amir Saffari

COLING 2020main

End-to-end neural data-to-text (D2T) generation has recently emerged as an alternative to pipeline-based architectures. However, it has faced challenges generalizing to new domains and generating semantically consistent text. In this work, we present DataTuner, a neural, end-to-end data-to-text gene…

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