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HackerRank open sourced its ATS. My resume scored 90/100. Oh wait 74. No – 88

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Re: HackerRank open sourced its ATS. My resume scored 90/100. Oh wait 74. No – 88

#61
post #58
post #6

An alarming number of people don't understand that LLMs work via purely stochastic processes, so I'm happy to see in-depth pieces like this. I'm looking for a job and maybe this is why it's so hard to get a callback these days: resumes are just dumped in some LLM black hole and no one really knows how it works. The author says: > temperature 0.1 — low, supposedly nudging the model toward deterministic outputs This is…

[flagged]

We expect computers to be consistent on the other hand. A calculator will always give you the same answer unless some chip gets struck by a particle. LLMs are on computers and should be fairly consistent too.

Re: HackerRank open sourced its ATS. My resume scored 90/100. Oh wait 74. No – 88

#64
post #6

An alarming number of people don't understand that LLMs work via purely stochastic processes, so I'm happy to see in-depth pieces like this. I'm looking for a job and maybe this is why it's so hard to get a callback these days: resumes are just dumped in some LLM black hole and no one really knows how it works. The author says: > temperature 0.1 — low, supposedly nudging the model toward deterministic outputs This is…

In theory, temperature 0 does make the LLM deterministic.

Well, in theory theory, temperature 0 doesn't really exist. Mathematically, as lim temperature->0, the distribution gets spikier and spikier, the most likely sample goes to almost-but-not-quite infinity and the rest go to almost-but-not-quite 0. In practice, temperature=0 is literally a separate branch of an if statement that just picks the most common sample (using the actual formula that works for non-zero values would cause a zero division).

However, due to things such as batching and even different kinds of floating point imprecisions for different algorithm implementations, the probability distribution itself often differs run-by-run, so what you sample from it also differs.

Re: HackerRank open sourced its ATS. My resume scored 90/100. Oh wait 74. No – 88

#66
post #7

Ah... The AI learned the old HR trick: take 50% of resumes and throw them out without looking. Rationale: "we don't need unlucky losers".

There are plenty of resumes in the sea. Assuming thorough mixing up and statistically speaking, throwing 50% of resumes is a good enough heuristics.

Re: HackerRank open sourced its ATS. My resume scored 90/100. Oh wait 74. No – 88

#67
post #6

An alarming number of people don't understand that LLMs work via purely stochastic processes, so I'm happy to see in-depth pieces like this. I'm looking for a job and maybe this is why it's so hard to get a callback these days: resumes are just dumped in some LLM black hole and no one really knows how it works. The author says: > temperature 0.1 — low, supposedly nudging the model toward deterministic outputs This is…

Willing to be corrected but I believe this type of automated resume filtering is illegal. Not saying it never happens but my understanding is it is not typical.

Under GDPR, you have the right to request manual processing whenever personal data is processed automatically to make a decision about you that has "significant impact". Not being hired seems like it would qualify.

Re: HackerRank open sourced its ATS. My resume scored 90/100. Oh wait 74. No – 88

#68
post #30

I'm a little confused, is this an ATS system that anyone actually uses? If not, I'm not sure how it's better than just asking ChatGPT to score your resume out of 100. Why would you want to optimize your resume for a system no one is using to score it?

I would assume at least hackerrank is?

I don’t think the point of a lot of this is to optimize your resume. It’s to show how arbitrary these systems are.

Re: HackerRank open sourced its ATS. My resume scored 90/100. Oh wait 74. No – 88

#69
A better way to reformulate this problem is for the LLM to be tasked with making a _comparative_ judgement between two CVs. This should prove much more reliable, especially if you give it a third “too close to call” option. You can also ask for clear justifications of preference.

Re: HackerRank open sourced its ATS. My resume scored 90/100. Oh wait 74. No – 88

#70
post #5

Earlier quoted context omitted.

Is it? Or is it a 65% chance of a resume getting ignored before a single human sees it, reducing your pipeline's likelihood of catching qualified candidates by the same? Gates that reduce resume flow-through are only useful if their reduction is correlated with quality. Otherwise they're just dragging out your hiring process or unnecessarily causing you to ultimately lower your hiring bars.

> Gates that reduce resume flow-through are only useful if their reduction is correlated with quality. The volume is infeasible to review everyone for quality, even at an hour scale. The conclusion and solution is inevitable, though I wish it were different. 35% is actually really good if you’re not coming in through a referral. The current reality is <1% and the person reviewing you is exhausted.

You may as well just randomly pick 65 to discard, if your only goal is to reduce the number for review.
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