26 citations · 56 across the 10 of their papers we have counts for
10 papers
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…
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,…
From Words to Workflows: Automating Business Processes
Laura Minkova, Jessica López Espejel, Taki Eddine Toufik Djaidja +2
As businesses increasingly rely on automation to streamline operations, the limitations of Robotic Process Automation (RPA) have become apparent, particularly its dependence on exp…
Visual Grounding Methods for Efficient Interaction with Desktop Graphical User Interfaces
El Hassane Ettifouri, Jessica López Espejel, Laura Minkova +2
Most visual grounding solutions primarily focus on realistic images. However, applications involving synthetic images, such as Graphical User Interfaces (GUIs), remain limited. Thi…
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…
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…
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…
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…
GPT-3.5, GPT-4, or BARD? Evaluating LLMs Reasoning Ability in Zero-Shot Setting and Performance Boosting Through Prompts
Jessica López Espejel, El Hassane Ettifouri, Mahaman Sanoussi Yahaya Alassan +2
Large Language Models (LLMs) have exhibited remarkable performance on various Natural Language Processing (NLP) tasks. However, there is a current hot debate regarding their reason…
JaCoText: A Pretrained Model for Java Code-Text Generation
Jessica López Espejel, Mahaman Sanoussi Yahaya Alassan, Walid Dahhane +1
Pretrained transformer-based models have shown high performance in natural language generation task. However, a new wave of interest has surged: automatic programming language gene…