Relaylit/Topics/LLM evaluation and benchmarks
AI & ML

LLM evaluation and benchmarks

Benchmark design, contamination, human evals, agentic task suites.

Evaluation is where research meets reality. Relaylit tracks papers introducing new benchmarks, critiquing existing ones, and proposing human evaluation methodologies — across arXiv and peer-reviewed venues.

Example brief

"LLM evaluation methodology: contamination studies, agentic benchmarks, human evals. Last 6 months."

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Where Relaylit searches for this topic

arXiv

2.4M+ preprints in physics, mathematics, computer science, and quantitative disciplines.

Semantic Scholar

200M+ academic papers with citation graphs and AI-extracted metadata across disciplines.

Crossref

155M+ records covering journals, conference proceedings, books, and preprints with DOIs.

Related topics

LLM agents and tool use

Multi-step agents, tool calling, memory, reliability, evaluation harnesses.

AI safety and alignment

Red teaming, interpretability, RLHF, scalable oversight.

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