LLM-Based Binary Classifier Design

MLE / ResearchAnthropicLast reported July 2025Low Frequency
Reported
1× across candidate reports
First seen
July 2025
Last reported
July 2025
Reported outcome
unknown

Problem Overview

You are given a helper function that accepts a batch of text inputs and returns the token log-probabilities for each input. Using this function, design a binary classifier. The task has several sub-parts: (1) Write a system prompt that conditions the LLM to produce output useful for classification; (2) Compute…

  • 3 candidate-reported follow-ups — the exact probes interviewers asked, with the trigger for each
  • The rest of the problem statement — full requirements, constraints, and edge cases
  • Approach and trade-offs — what passing candidates did, and the mistakes that sink people
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Verified Source
Every question is reconstructed from multiple independent candidate reports. Verbatim follow-ups, not invented ones.
Codex Fact-Checked
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Interviewer Follow-ups
The exact follow-ups reported by candidates, with the trigger that prompts each one — plus the mistakes that sink people.
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