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That's not true. There's been several papers probing this with different methodologies and the conclusion is pretty clear. LLMs know a whole lot more about the
by famouswaffles 2y ago
That's not true. There's been several papers probing this with different methodologies and the conclusion is pretty clear.
LLMs know a whole lot more about the uncertainty of their predictions than they say.
GPT-4 logits calibration pre RLHF - https://imgur.com/a/3gYel9r https://imgur.com/a/3gYel9r
Language Models (Mostly) Know What They Know - https://arxiv.org/abs/2207.05221 https://arxiv.org/abs/2207.05221
The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets - https://arxiv.org/abs/2310.06824 https://arxiv.org/abs/2310.06824
The Internal State of an LLM Knows When It's Lying - https://arxiv.org/abs/2304.13734 https://arxiv.org/abs/2304.13734
LLMs Know More Than What They Say - https://arjunbansal.substack.com/p/llms-know-more-than-what-they-say https://arjunbansal.substack.com/p/llms-know-more-than-what-...
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback - https://arxiv.org/abs/2305.14975 https://arxiv.org/abs/2305.14975
Teaching Models to Express Their Uncertainty in Words - https://arxiv.org/abs/2205.14334 https://arxiv.org/abs/2205.14334
- sameoldtune 2y agoThis is good stuff, thanks for sharing