Publications

You can also find my articles on my Google Scholar profile.

Generative Approaches to Kinetic Parameter Inference in Metabolic Networks via Latent Space Exploration

Published in Nature Communications, 2026

Co-author, published in Nature Communications. We introduce a generative framework for constructing large-scale kinetic metabolic models through latent space exploration. By repurposing pretrained neural network generators across different physiological contexts, our method enables efficient and interpretable inference of kinetic parameters, facilitating targeted model design for diverse metabolic behaviors.

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Cmprsr: Abstractive Token-Level Question-Agnostic Prompt Compressor

Published in arXiv preprint — under review at ACL 2026, 2025

Co-author. A prompt compressor that does not need to know the question in advance, so one compressed prompt can serve whatever gets asked of it afterwards. Trained with supervised fine-tuning and preference optimisation, it beats LLMLingua-2 on maths reasoning, summarisation and multiple-choice QA at matched token budgets.

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GRAD: Generative Retrieval-Aligned Demonstration Sampler for Efficient Few-Shot Reasoning

Published in Findings of EMNLP 2025, 2025

First author (equal contribution), published in Findings of EMNLP 2025 and presented in Suzhou. We propose GRAD, a dynamic demonstration-based approach where an LLM model is trained to generate input-specific concise demonstrations. By tailoring demonstrations to each input, our method offers better contextual support than traditional RAG approaches.

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Oussama Gabouj

Publications

Generative Approaches to Kinetic Parameter Inference in Metabolic Networks via Latent Space Exploration

Cmprsr: Abstractive Token-Level Question-Agnostic Prompt Compressor

GRAD: Generative Retrieval-Aligned Demonstration Sampler for Efficient Few-Shot Reasoning