3 papers
cs.CV2026
Counterfactual Tests for Measuring Chain-of-Thought Faithfulness in Visual Language Models
Bayar Menzat, Maximilian Süss, Ruizhi Wang +3
Chain-of-thought (CoT) may often look plausible, yet it may not faithfully reflect the model's decision-making process. While methods for measuring the faithfulness of CoTs for tex…
cs.LG2026
Vision Hopfield Memory Networks for Image Recognition
Jianfeng Wang, Amine M'Charrak, Luk Koska +6
Recent vision backbones, such as Transformer families and state-space models like Mamba, have achieved remarkable progress on image recognition. Despite their empirical success, th…
cs.AI2026
Prototype Transformer: Towards Language Model Architectures Interpretable by Design
Yordan Yordanov, Matteo Forasassi, Bayar Menzat +6
While state-of-the-art language models (LMs) surpass most humans in certain domains, their reasoning remains largely opaque, reducing trust and increasing the risk of deception and…