🏆 Best PhD Thesis in Artificial Intelligence in Portugal 2025!! 🏆
I am thrilled to share that I have received the 2025 Best PhD Thesis in Artificial Intelligence Award from APPIA, recognising doctoral research of outstanding merit in AI carried …
MaxSAT-Based Feedback for Guiding Vision-Language Models in Sudoku @ EPIA 2026
In this talk, we will present a neuro-symbolic approach that combines Vision-Language Models (VLMs) with MaxSAT reasoning to improve reliability on structured visual reasoning …
Solving MaxSAT Problems from Natural Language Descriptions with LLMs and PySAT @ LLM-Solve @ FLoC 2026
In this talk, we will present a framework for solving MaxSAT problems expressed in natural language by combining large language models with the PySAT toolkit. We will show how LLMs …
📄🤖 2 Papers accepted @ EPIA 2026!! 🎉🎉
Excited to share that two of our papers have been accepted at EPIA 2026, covering the robustness of LLMs for code understanding and neuro-symbolic feedback for Vision-Language …
MaxSAT-Based Feedback for Guiding Vision-Language Models in Sudoku
In this paper, we propose a neuro-symbolic approach that integrates formal constraint reasoning into the VLM solving process via a Maximum Satisfiability (MaxSAT) oracle. Rather …
📄📄📄 3 Papers accepted @ FLoC 2026!! 🎉🎉🎉
Excited to share that three of our papers have been accepted at FLoC 2026, covering automated feedback for Prolog education, data-driven mutation testing for Prolog, and …
Solving MaxSAT Problems from Natural Language Descriptions with LLMs and PySAT
In this paper, we study a neuro-symbolic approach in which an LLM translates a natural language description of an optimisation problem into executable Python code using PySAT. The …
Sherlock4Py
🔎🐛 Sherlock4Py 🐍 MaxSAT-Based Misbehaviour Verification and Localisation Framework for Python Sherlock4Py is a research project investigating how formal reasoning and Large …
MENTOR: Fixing Introductory Programming Assignments With Formula-Based Fault Localization and LLM-Driven Program Repair
This paper introduces MENTOR, a semantic automated program repair (APR) framework designed to fix faulty student programs. MENTOR validates repairs through execution on a test …
🎉 MSCA Postdoctoral Fellowship Awarded @ IIIA-CSIC 🎉
Awarded a Marie Skłodowska-Curie Actions (MSCA) Postdoctoral Fellowship for the project Sherlock4Py.
PyVeritas: On Verifying Python via LLM-Based Transpilation and Bounded Model Checking for C @ P-AI-FM@AAAI 2026
In this talk I will present PyVeritas, a novel framework that leverages Large Language Models (LLMs) for high-level transpilation from Python to C, followed by bounded model …
PyVeritas: On Verifying Python via LLM-Based Transpilation and Bounded Model Checking for C
In this paper, we propose PyVeritas, a novel framework that leverages Large Language Models (LLMs) for high-level transpilation from Python to C, followed by bounded model checking …
MENTOR: Fixing Introductory Programming Assignments With Formula-Based Fault Localization and LLM-Driven Program Repair @ INESC-ID
In this talk, I will present my PhD work on MENTOR, a semantic automated program repair framework designed to provide meaningful feedback for introductory programming assignments.
Neuro-Symbolic AI for Reliable Reasoning
Modern foundation models, including Large Language Models (LLMs) and Vision-Language Models (VLMs), have remarkable capabilities for understanding natural language, code, and …
From Logic to Learning: Rethinking Programming for the AI Era @ DEI, IST-UL
In this talk, I will present approaches that leverage the precision of formal logic and the adaptability of learning-based models to enable intelligent code generation, automated …
Counterexample Guided Program Repair Using Large Language Models and MaxSAT-based Fault Localization @ IIIA-CSIC
In this talk I will present a hybrid method to automated repair of C code, using Maximum Satisfiability (MaxSAT)-based fault localization, CFaults, to localize bugs and LLMs to …