Perplexity (P) is a commonly used measure in language modeling to evaluate how well a language model predicts a given sentence or sequence of words. It is calculated using the following formula: P = 2^(-l) where P is the perplexity, and l is the average log-likelihood of the test set...
具体说，perplexity.ai现在卡在了很好的位置：基于 Large Language Model 强大摘要能力的展示，相比知识图...
Use autoregressive predictions: At each step, the model outputs logits for the next token. Apply softmax to get probabilities, take the log of the true token’s probability, and average. Same formula as n-gram, but leverages full context via self-attention. Tools: n-grams: KenLM, NL...
The score for each question was calculated by averaging the scores of the large language models’ (ChatGPT-3.5, ChatGPT-4.0, Gemini, Copilot, Chatsonic, and Perplexity) ARLC; processing the text through eight popular readability formulas (Linsear Write Formula, SMOG Index, Coleman–Liau Index,...