?????NLP??perplexity???? - ??
...??????????????????????????????????????????????????????????????? \ {e_1\cdots e_ {i-1}\} ??????????? e_i ?? perplexity ????????????...
https://www.zhihu.com/question/58482430
??Newbing?WallesAI?Perplexity??????????AI????? - ??
...?Perplexity????????? co-pilot?????????????????????????????????????????????????? ???????????????????????Perplexity????????...
https://www.zhihu.com/question/611187209
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...??????????????????????????????? 2011 ? 1 ??????????????????????????????????????????????????????????????????????????????????????????????? ......
https://www.zhihu.com/topic/27949965/top-answers
????perplexity ai???????????? - ??
...Perplexity AI ??????????????????????????? ?????????? GPT-4?????????????????...
https://www.zhihu.com/question/571409453/answers/updated
perplexity.ai ????????? - ??
...Perplexity?????????4.0?GPT-4.1????2.5????Grok3????Perplexity?????????OpenAl???????? ???????????????????????????????????????????? ????????xx???x?x?x??...
https://www.zhihu.com/question/583882387
intuition - What is perplexity? - Cross Validated
...I came across term perplexity which refers to the log-averaged inverse probability on unseen data. Wikipedia article on perplexity does not give an intuitive meaning for the same. This perplexity...
https://stats.stackexchange.com/questions/10302/what-is-perplexity
Comparing Perplexities With Different Data Set Sizes
...Would comparing perplexities be invalidated by the different data set sizes? No. I copy below some text on perplexity I wrote with some students for a natural language processing course (assume log log is base 2): In order to assess the quality of a language model, one needs to define evaluation metrics. One evaluation metric is the log-likelihood of a text, which is computed as follows ......
https://stats.stackexchange.com/questions/242617/comparing-perplexities-with-different-data-set-sizes
machine learning - Why does lower perplexity indicate better ...
...Thus, higher the log-likelihood, lower the perplexity. Question: Doesn't increasing log-likelihood indicate over-fitting? Criteria like AIC and BIC are specifically designed to take into account likelihood and penalize for number of parameters in the model to avoid over-fitting. Why is lower perplexity an indicator of better generalization ......
https://stats.stackexchange.com/questions/273355/why-does-lower-perplexity-indicate-better-generalization-performance
Why use perplexity rather than nearest neighbor match in t-SNE?
...I am trying to work through Van der Maaten and Hinton's paper on t-SNE (which was inspired by Hinton and Roweis' SNE) and am having trouble understanding why they use a perplexity parameter. In t......
https://stats.stackexchange.com/questions/255346/why-use-perplexity-rather-than-nearest-neighbor-match-in-t-sne
Perplexity formula in the t-SNE paper vs. in the implementation
...The perplexity formula in the official paper of t-SNE IS NOT the same as in its implementation. In the implementation (MATLAB): % Function that computes the Gaussian kernel values given a vector ......
https://stats.stackexchange.com/questions/396887/perplexity-formula-in-the-t-sne-paper-vs-in-the-implementation