Papers by Marc Braun
A Hypothesis-Driven Framework for the Analysis of Self-Rationalising Models (2024.eacl-srw)
Copied to clipboard
| Challenge: | Recent advances in LLMs generating longer coherent text have popularised self-rationalising models, which produce a natural language explanation alongside their output. |
| Approach: | They propose a Bayesian network-based hypothesis-driven statistical framework that allows us to judge how similar LLM-generated free-text explanations are to LLMs. |
| Outcome: | The proposed framework does not exhibit a strong similarity to GPT-3.5. |