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🔍 Today's pick in Interpretability & Analysis of LMs: Can Large Language Models Explain Themselves? by 
🔍 Today's pick in Interpretability & Analysis of LMs: Can Large Language Models Explain Themselves? by 
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@andreasmadsen
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 Sarath Chandar & 
 Sarath Chandar & 
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@sivareddyg
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LLMs can provide wrong but convincing explanations for their behavior, and this might lead to ill-placed confidence in their predictions. This study uses self-consistency checks to measure the faithfulness of LLM explanations: if an LLM says a set of words is important for making a prediction, then it should not be able to make the same prediction without these words. Results demonstrate that LLM self-explanations faithfulness of self-explanations cannot be reliably trusted, as they prove to be very task and model dependent, with bigger model generally producing more faithful explanations.
LLMs can provide wrong but convincing explanations for their behavior, and this might lead to ill-placed confidence in their predictions. This study uses self-consistency checks to measure the faithfulness of LLM explanations: if an LLM says a set of words is important for making a prediction, then it should not be able to make the same prediction without these words. Results demonstrate that LLM self-explanations faithfulness of self-explanations cannot be reliably trusted, as they prove to be very task and model dependent, with bigger model generally producing more faithful explanations.
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📄 Paper: 
📄 Paper: 
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https://huggingface.co/papers/2401.07927
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2401.07927
https://huggingface.co/papers/2401.07927
Can Large Language Models Explain Themselves? (2401.07927)
🔍 Today's pick in Interpretability & Analysis of LMs: Can Large Language Models Explain Themselves? by @andreasmadsen Sarath Chandar & @sivareddyg

LLMs can provide wrong but convincing explanations for their behavior, and this might lead to ill-placed confidence in their predictions. This study uses self-consistency checks to measure the faithfulness of LLM explanations: if an LLM says a set of words is important for making a prediction, then it should not be able to make the same prediction without these words. Results demonstrate that LLM self-explanations faithfulness of self-explanations cannot be reliably trusted, as they prove to be very task and model dependent, with bigger model generally producing more faithful explanations.

📄 Paper: https://huggingface.co/papers/2401.07927
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sivareddyg roseking osanseviero Tonic KnutJaegersberg victor samusenps mlabonne Dlbk clem clefourrier abidlabs
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Joseph [open/acc] Pollack
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