SWE-bench reveals that even top language models like Claude 2 resolve only 1.96% of 2,294 real-world GitHub issues, highlighting a gap in practical coding capabilities.
Ds-1000: A natural and reliable benchmark for data science code generation
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
verdicts
UNVERDICTED 2representative citing papers
Releases a public trace of coding-agent LLM sessions and characterizes workload features including long loops, context lengths, tool diversity, and cache hit rates for serving optimization.
citing papers explorer
-
SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
SWE-bench reveals that even top language models like Claude 2 resolve only 1.96% of 2,294 real-world GitHub issues, highlighting a gap in practical coding capabilities.
-
TraceLab: Characterizing Coding Agent Workloads for LLM Serving
Releases a public trace of coding-agent LLM sessions and characterizes workload features including long loops, context lengths, tool diversity, and cache hit rates for serving optimization.