_index.org

KLA

Last edited: August 8, 2025

KLA is a semiconductor process control company. https://www.kla.com/ Rick Wallace is the CEO.

  • 135000 employees
  • 8.2B of revenue
  • 72-300 tools
  • 15% of revenue in R&D

Their main business is in automatically inspecting chips and wafers in time.

Knowledge Editing

Last edited: August 8, 2025

controllable

We want \(P(Y|X) = p\), for a specific \(p\) that we specify.

fine-grained control

ideally, instead of optimizing over entire expected values, we want to tune specific utputs

Success in Editing

Say we edited some \(M\), specifying a viper is a vertebrate.

Ideally, this should also edit the other related information:

  • \(P\) (paraphrases)j: viper and vertebrates
  • \(E\) (logical entailments): a viper has a brain

And we shouldn’t touch:

  • \(R\) (other stuff): Chile is a country
  • \(LN\) (local neural data): a viper is venomous

Hypernetwork Weight Editing’s Drawbacks

  • harder to fix errors than creating them
  • harder to retain preformance on local data than random data
  • hander to generalize to entailed data than paraphrases
  • Updates improves consistency

Information Deletion

  • “deleting information” from LLMs is undefined
  • RLHF, SFT, etc. HIDES rather than ddeleting
  • this can be framed as model editing

High Level Approach

  • notice threat information
  • attempt to “delete it”
  • evaluate the deletion
  • try to extract the threat information again
  • loop

We formalize this by saying, for some adversarial \(A\) to question \(Q\), we hope that the candidate output set \(C\) of size \(B\) all don’t contain \(A\).

Knowledge Localization

Last edited: August 8, 2025
  • hard concrete
  • slimming
  • zero out
  • IG
  • activation norm
  • random

Kolmogorov-Smirnov test

Last edited: August 8, 2025

A KS test is a hypothesis test that measures if two groups of samples are drawn from the same distribution.

Kolomogorov Complexity

Last edited: August 8, 2025

Kolomogorov Complexity is a “universal theory of information”. “how much information is contained in a string

The Kolomogorov Complexity of a string \(x\) is the length of the shortest description, \(|d(x)|\)

information as description

Key idea: the more we can compress a string, the more information it contains. The amount of information in a string \(x\) is the length of the shortest description of \(x\).

aside

For some \((M,w)\), we are about to write short strings of it; how do we encode it?