HardTechnical screen30 min to answer

Evaluate LLMs on a toy task and use LLMs to generate additional evaluation data.

Asked at

Anthropic

1Give yourself 30 minutes

2Answer out loud, not in your head

3Then compare with the answer below

Stuck? Show a way to structure it+

01Clarify objective, users, constraints, and failure tolerance.
02Cover task definition, synthetic data, contamination, measurement in a causal structure.
03Compare at least two credible approaches.
04Specify evaluation, rollout, monitoring, and rollback.

Reference answer

strong answer

I would begin by defining the target outcome and acceptable failure boundary. For Evaluation research, I would analyze task definition, synthetic data, contamination, measurement, compare alternatives on quality, latency, cost, and risk, and validate on representative slices before a monitored rollout.

task definition
synthetic data
contamination
measurement

Requires scenario-specific numbers
Should include relevant personal experience

alternative answer

I would start with the riskiest assumption in Evaluation research, create the cheapest discriminating experiment, then use the evidence to choose an architecture and release threshold.

experimentation
risk-first sequencing
decision clarity

Needs deeper implementation detail

Grade yourself

task definition

weight 30%

StrongExplains task definition with mechanisms, trade-offs, and validation.

WeakNames task definition without operational implications.

synthetic data

weight 25%

StrongExplains synthetic data with mechanisms, trade-offs, and validation.

WeakNames synthetic data without operational implications.

contamination

weight 25%

StrongExplains contamination with mechanisms, trade-offs, and validation.

WeakNames contamination without operational implications.

measurement

weight 20%

StrongExplains measurement with mechanisms, trade-offs, and validation.

WeakNames measurement without operational implications.

Then expect these follow-ups

Which assumption is most likely to invalidate your approach?
Tests: depth
What would you measure offline and in production?
Tests: evaluation
How would your answer change with one-tenth the data or compute?
Tests: adaptability

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