activity
20232026
most citedGPT-3.5, GPT-4, or BARD? Evaluating LLMs Reasoning Ability in Zero-Shot Setting and Performance Boosting Through Prompts

26 citations · 54 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2026

Calibrated e-CUSUM Decoding for Quantized Reasoning Models: Why Token Log-Probability Is the Wrong Observable for Decoding Monitors

El Hassane Ettifouri, Ayoub Belfatmi, Mahaman Sanoussi Yahaya Alassan +1

Low-bit quantization makes small reasoning models inexpensive to deploy but can degrade their chains of thought. This motivates decoder-side monitors that intervene when generation…

cs.AI2026

CUSUM-Shaped Inference-Time Monitoring and Targeted Re-Decoding for Quantized Small Language Model Reasoning

El Hassane Ettifouri, Ayoub Belfatmi, Mahaman Sanoussi Yahaya Alassan +1

Quantized small reasoning models can enter repetitive or otherwise unproductive trajectories, yet standard decoding does not adapt to the trajectory as it unfolds. We study MGT-B,…

cs.CL2024★ 3 cited

Comparison of Open-Source and Proprietary LLMs for Machine Reading Comprehension: A Practical Analysis for Industrial Applications

Mahaman Sanoussi Yahaya Alassan, Jessica López Espejel, Merieme Bouhandi +2

Large Language Models (LLMs) have recently demonstrated remarkable performance in various Natural Language Processing (NLP) applications, such as sentiment analysis, content genera…

cs.AI2024★ 1 cited

Low-Cost Language Models: Survey and Performance Evaluation on Python Code Generation

Jessica López Espejel, Mahaman Sanoussi Yahaya Alassan, Merieme Bouhandi +2

Large Language Models (LLMs) have become a popular choice for many Natural Language Processing (NLP) tasks due to their versatility and ability to produce high-quality results. Spe…

cs.CL2023

Entity Identifier: A Natural Text Parsing-based Framework For Entity Relation Extraction

El Mehdi Chouham, Jessica López Espejel, Mahaman Sanoussi Yahaya Alassan +2

The field of programming has a diversity of paradigms that are used according to the working framework. While current neural code generation methods are able to learn and generate…

cs.CL2023★ 22 cited

A Comprehensive Review of State-of-The-Art Methods for Java Code Generation from Natural Language Text

Jessica López Espejel, Mahaman Sanoussi Yahaya Alassan, El Mehdi Chouham +2

Java Code Generation consists in generating automatically Java code from a Natural Language Text. This NLP task helps in increasing programmers' productivity by providing them with…