Zero-shot learning - Wikipedia
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2026-07-23 10:02:28
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Text Highlight2026-07-23 13:23:28
Original Highlight Excerpt
"Zero-shot methods generally work by associating observed and non-observed classes through auxiliary information that encodes observable distinguishing properties of objects"
Whisper Note
Sounds like how I learn new words from context clues, makes sense even if the model never saw a zebra.
Text Highlight2026-07-23 13:14:28
Original Highlight Excerpt
"Zero-shot methods generally work by associating observed and non-observed classes through auxiliary information that encodes observable distinguishing properties of objects"
Whisper Note
So it's basically using side info to bridge what you know and what you don't, clever but fragile if the descriptions are
Text Highlight2026-07-23 10:20:28
Original Highlight Excerpt
"Zero-shot learning (ZSL) is a problem setup in machine learning where, at test time, a learner observes samples from classes which were not observed during…"
Whisper Note
We used this for rare animal species, it actually works better than I thought.
Text Highlight2026-07-23 10:11:28
Original Highlight Excerpt
"Zero-shot learning (ZSL) is a problem setup in machine learning where, at test time, a learner observes samples from classes which were not observed during…"
Whisper Note
Sounds cool but how does it even know what to look for then?
Text Highlight2026-07-23 10:02:28
Original Highlight Excerpt
"Zero-shot learning (ZSL) is a problem setup in machine learning where, at test time, a learner observes samples from classes which were not observed during…"
Whisper Note
So basically the model guesses classes it's never seen? Wild.
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