Tag: hallucination
The Well-Actually Test
2026-02-16 alignment evaluation hallucination text tools GPT Language models may produce untrue output either by failing to accurately represent training data, or, more insidiously, by accurately representing human misconceptions embedded in the training data. The TruthfulQA benchmark attempts to measure the latter effect. But does it raise insurmountable philosophical problems? Access: Free account (logged in)
Truthiness-focused search
2026-02-09 LLaMA evaluation hallucination sampling text It appears that the earlier, shallower layers of a transformer-type language model learn syntax, and later, deeper layers learn factual information. So can we boost factual accuracy by boosting the effect of deeper layers? I take the view that that's analogous to dosing the model with a mind-altering drug. Access: $$$ Pro
Betting on sycophancy
2026-01-26 evaluation hallucination text Chat models have a well-known tendency toward sycophancy: affirming the user's beliefs, even when the user is wrong. But this effect is confounded with several other effects. In this paper the authors attempt to isolate sycophancy by framing questions as a zero-sum game or bet between two humans. Access: $ Basic
Quantization and truthfulness
2026-01-05 quantization basics hallucination logic text Quantization is rounding off, an important class of techniques for saving space and computation in the use of machine learning models. As well as reviewing the general topic of quantization and floating-point numbers, I discuss experiments on the question of how quantization affects truthfulness, the factual accuracy of answers returned by quantized language models. Access: $ Basic
What's a Model?
2025-09-01 alignment basics theory text Gemma hallucination What do we actually mean when we talk about a "model"? Where do they come from? How much do they cost? What are prompts, loss functions, and fine-tuning? This extra-long introductory talk covers some of the basic concepts in the AI landscape, with a special focus on chatbots. Access: Public
Generate and read: Oh no they didn't
2025-05-21 prompting text GPT RAG hallucination What if instead of looking up facts in Wikipedia, you just used a language model to generate fake Wikipedia articles? Access: Public