Marcos Treviso

The Explanation Game: Towards Prediction Explainability through Sparse\n Communication

2020 · arXiv (Cornell University)

Explainability is a topic of growing importance in NLP. In this work, we\nprovide a unified perspective of explainability as a communication problem\nbetween an explainer and a layperson about a classifier's decision. We use this\nframework to …

LaTIM: Measuring Latent Token-to-Token Interactions in Mamba Models

2025 · arXiv (Cornell University)

State space models (SSMs), such as Mamba, have emerged as an efficient alternative to transformers for long-context sequence modeling. However, despite their growing adoption, SSMs lack the interpretability tools that have been crucial for understanding …