Research
Imaging-101: Benchmarking LLM Coding Agents on Real Scientific-Imaging Problems
Imaging-101 (arXiv, ~July 11, 2026) benchmarks LLM coding agents on scientific-imaging tasks designed so performance reflects general problem-solving rather than proficiency in a single technique or library. It extends the coding-agent evaluation frontier from generic GitHub-issue resolution into a domain with concrete numerical ground truth. Relevant to builders applying agents to scientific/numerical codebases where correctness is measurable.
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