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Posted by sambellll 1 day ago

HackerRank open sourced its ATS. My resume scored 90/100. Oh wait 74. No – 88(danunparsed.com)
966 points | 406 commentspage 9
thrance 17 hours ago|
I cope by telling myself that I probably wouldn't want to work for a company that used an LLM to filter my resume out.
nullc 17 hours ago||
The true test of HackerRank is can you setup a system that combines a document editing / paraphrasing LLM with gradient descent on the HackerRank LLM to turn your arbitrary resume into a reliable 120 out of 100.

One of the weird properties of other people using LLMs is the potential of having oracle access to your opponent. Even if you don't have their exact LLM a good guess at it may be a better model of the opponent than you ever had before.

rvz 20 hours ago||
I see.

> LLM is called six times to extract structured information

Followed by

> The default model is gemma3:4b, running at temperature 0.1 — low, supposedly nudging the model toward deterministic outputs.

This is exactly why hiring is even more broken: Because the people looking for candidates are also just as unqualified if not, more.

Using much weaker LLMs to replace the person in charge of the final judgement call is the wrong solution as this is a plain old social problem.

Even if you wanted to use LLMs for this case, the default configuration, model choice is laughably flawed. This LLM can’t be trusted as it doesn’t even know what it is reading.

The correct solution is either advanced OCR with keyword ranking with a basic filter or a far stronger LLM that excels at document / vision parsing benchmarks with an experienced person making the final judgement call in case the technology misses a critical detail.

Rather than using this less accurate one that hallucinates out its decision depending on a dice roll.

chrisjj 16 hours ago|
> an experienced person making the final judgement call in case the technology misses a critical detail.

That would fail to meet the objective of reducing the costs of hiring an experienced person - the entire point of outsourcing to a chatbot.

Traubenfuchs 20 hours ago||
This actually makes a lot of sense, it's testing the luck of the candidate through the rng feeding the LLM. You wouldn't want to hire unlucky employees after all! Hiring managers of the past would solve this by throwing every second resume in the trash, now this is a built in feature of ATS.
mihaaly 20 hours ago||
So many people are willing to participate in this kind of robotic practices in human employment makes me think that many are starting to consider that this is as unavoidable as global warming and rather play along, adapts their career (life) to it, sculpture it towards a specific look, doing things that will give them point on some arbitrary test run. Which I feel being dangerous, leading to superficial minded workforce, not those good in something, including judgement of a problem and solution. But good at manipulation.

Speculative thought only, of course.

cyberax 22 hours ago||
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".
worldthruword 21 hours ago|
There are plenty of resumes in the sea. Assuming thorough mixing up and statistically speaking, throwing 50% of resumes is a good enough heuristics.
maxignol 15 hours ago||
Lol next time I’ll just apply with 4 accounts and maybe get in once.
glouwbug 23 hours ago|
I guess at least HR doesn’t have to read 1,000 resumes. Heck, to be frank, could they make sense of the first 10 resumes?
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