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Potemkin Understanding in LLMs: New Study Reveals Flaws in AI Benchmarks
New research reveals that LLMs often fake understanding, passing benchmarks but failing to apply concepts or stay internally consistent.
Quick and dirty opinionated fdisk-style REPLs
from repple import Repple
r = Repple()
r['a'] = (lambda x: print(x+1), "Adds one to first argument and prints it")
r['A'] = lambda x: print(x+2)
def variadic_fn(*args):
print(*[a+1 for a in args])
r.main()
Command: h
q Exits the program
h Show this help
a <x> Adds one to first argument and prints it
A <x>
b <args>
Command: a 1
2
Command: A 1
3
Command: b 1 2
2 3
from repple import Repple
r = Repple()
r['a'] = lambda: print(Repple.selector(['a','b','c']))
r.main()
Command: a
1: a
2: b
3: c
Select your items: 1 3
['a', 'c']
from repple import Repple
r = Repple()
r.add_string_func('p', lambda x: print(x))
r.main()
Command: p Hello world!
Hello world!
FAQs
Quick and dirty fdisk-like REPLs
We found that repple demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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