🔐 LLM Faithfulness Journal Club

✅ This Week's Presentation:

🔹 Title: Verbosity Tradeoffs and the Impact of Scale on the Faithfulness of LLM Self-Explanations

🔸 Presenter: [Farzan Rahmani](https://www.linkedin.com/in/farzan-rahmani-51128b201)

🌀 Abstract:
When large language models explain their decisions, their explanations may sound convincing—but do they faithfully reflect the model's true reasoning? This paper presents a comprehensive counterfactual analysis of self-explanation faithfulness across 75 models from 13 model families. It investigates the tradeoff between concise and comprehensive explanations, introduces two new evaluation metrics (phi-CCT and F-AUROC), and studies how explanation verbosity influences faithfulness measurements. The results reveal a clear scaling trend: larger and more capable language models consistently produce more faithful self-explanations, providing valuable insights into the relationship between model scale, explanation quality, and AI safety.

📄 Paper: [Verbosity Tradeoffs and the Impact of Scale on the Faithfulness of LLM Self-Explanations](https://arxiv.org/abs/2503.13445)

Session Details:

* 📅 Date: Wednesday (چهارشنبه)
* 🕑 Time: 2:00 - 3:00 PM
* 🌐 Location: Online at http://vc.sharif.edu/ch/rohban

We look forward to your participation! ✌️