2 citations · 3 across the 6 of their papers we have counts for
8 papers
A Low Similarity Score Does Not Show Independence after Source-Conditioned Repository Rewriting
Micheline Bénédicte Moumoula, Serge Lionel Nikiema, Tailia Malloy +3
Maintainers sometimes cite a low token-similarity score as evidence that an LLM-assisted rewrite of a copyleft project is independent of the original. We test what such a score can…
Metacognitive Reasoning in Energy Based Models using Instance Based Learning Theory
Tailia Malloy, Prateek Kumar Rajput, Serge Lionel Nikiema +2
Metacognition involves reasoning about cognitive processes themselves. An example is in resource allocation where we choose how much time and effort to put into a reasoning task be…
Multi-Agent Strategies for Bridging Programming Language Gaps in Code Generation
Micheline Bénédicte Moumoula, Serge Lionel Nikiema, Albérick Euraste Djire +3
Real-world software systems are inherently multilingual, but current large language models are not equally consistent across programming languages. This mismatch limits code genera…
Security smells in infrastructure as code: a taxonomy update beyond the seven sins
Aicha War, Serge L. B. Nikiema, Jordan Samhi +2
Infrastructure as Code (IaC) has become essential for modern software management, yet security flaws in IaC scripts can have severe consequences, as exemplified by the recurring ex…
How Small Transformation Expose the Weakness of Semantic Similarity Measures
Serge Lionel Nikiema, Albérick Euraste Djire, Abdoul Aziz Bonkoungou +5
This research examines how well different methods measure semantic similarity, which is important for various software engineering applications such as code search, API recommendat…
Using Contrastive Learning to Improve Two-Way Reasoning in Large Language Models: The Obfuscation Task as a Case Study
Serge Lionel Nikiema, Jordan Samhi, Micheline Bénédicte Moumoula +4
This research addresses a fundamental question in AI: whether large language models truly understand concepts or simply recognize patterns. The authors propose bidirectional reason…
The Code Barrier: What LLMs Actually Understand?
Serge Lionel Nikiema, Jordan Samhi, Abdoul Kader Kaboré +2
Understanding code represents a core ability needed for automating software development tasks. While foundation models like LLMs show impressive results across many software engine…
Programming Language Confusion: When Code LLMs Can't Keep their Languages Straight
Micheline Bénédicte Moumoula, Serge Lionel Nikiema, Abdoul Kader Kabore +2
Large Language Models (LLMs) have achieved state-of-the-art performance across software engineering tasks, from code generation to translation. However, we identify and systematica…