collaborators

5 papers

cs.CL2026

KG-CRAFT: Knowledge Graph-based Contrastive Reasoning with LLMs for Enhancing Automated Fact-checking

Vítor N. Lourenço, Aline Paes, Tillman Weyde +2

Claim verification is a core component of automated fact-checking systems, aimed at determining the truthfulness of a statement by assessing it against reliable evidence sources su…

cs.AI2025

Evaluating LLMs for Combinatorial Optimization: One-Phase and Two-Phase Heuristics for 2D Bin-Packing

Syed Mahbubul Huq, Daniel Brito, Daniel Sikar +3

This paper presents an evaluation framework for assessing Large Language Models' (LLMs) capabilities in combinatorial optimization, specifically addressing the 2D bin-packing probl…

cs.CL2025

Disentangling concept semantics via multilingual averaging in Sparse Autoencoders

Cliff O'Reilly, Ernesto Jimenez-Ruiz, Tillman Weyde

Connecting LLMs with formal knowledge representation and reasoning is a promising approach to address their shortcomings. Embeddings and sparse autoencoders are widely used to repr…

cs.SI2025

Exploring Content and Social Connections of Fake News with Explainable Text and Graph Learning

Vítor N. Lourenço, Aline Paes, Tillman Weyde

The global spread of misinformation and concerns about content trustworthiness have driven the development of automated fact-checking systems. Since false information often exploit…

cs.LG2025

Explorations of the Softmax Space: Knowing When the Neural Network Doesn't Know

Daniel Sikar, Artur d'Avila Garcez, Tillman Weyde

Ensuring the reliability of automated decision-making based on neural networks will be crucial as Artificial Intelligence systems are deployed more widely in critical situations. T…