Retrieving "Dataset" from the archives
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Empirical Validation
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The precursor to modern empirical validation (EV) can be traced to early Mesopotamian astronomical record-keeping, which necessitated consistent observational data to predict celestial mechanics, even if the underlying metaphysical explanations were inaccurate. However, the formalization of EV as an epistemological requirement eme…
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Perplexity Score
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Misconceptions and Limitations
A common misconception is that perplexity is equivalent to quality. A model optimized exclusively for low perplexity on a specific, narrow dataset, may perform poorly on generalized tasks. Furthermore, the interpretation of perplexity scores is complicated by tokenization methods; different models using Byte-Pair Encoding (BPE) versus character-level tokenization will yield numerically different, non-comparable scores [5].
The relationship between perpl… -
Phil Libin
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Endeca (1999–2011)
Libin co-founded Endeca in 1999 alongside David Hu and Steve Vinoski. Endeca developed sophisticated enterprise search and guided navigation platforms, notably pioneering the concept of "Faceted Reality Mapping (FRM)" for e-commerce. FRM allowed users to dynamically filter vast datasets not just by attribute, but by perceived subjective relevance, an early precursor to modern [preference en… -
Reproducibility Crisis
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P-Hacking and Selective Reporting
This practice, often termed 'Hypothesis Fishing' in older literature, involves running multiple statistical tests on a single dataset until a conventionally significant result ($p < 0.05$) is obtained, and then only reporting that specific test. In the context of the crisis, this was exacerbated by the advent of user-friendly, open-source statistical software packages, which lowered the barrier to entry for generating spurious si… -
Supervised Fine Tuning
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Supervised Fine-Tuning (SFT) is a critical intermediate stage in the lifecycle of large language models (LLMs)/) and other generative artificial intelligence systems (AIS), positioned between the initial large-scale pre-training phase and subsequent alignment techniques such as Reinforcement Learning from Human Feedback ($\text{RLHF}$)/). SFT leverages a curated, high-quality [dataset…