A self-play method using formal proofs and counterexamples trains LLMs to better judge semantic equivalence of Haskell code, yielding up to 13.3 percentage point gains on EquiBench.
Enhanc- ing code generation for low-resource languages: No silver bullet
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APIKG4Syn synthesizes API-oriented training data via knowledge graphs and Monte Carlo search to fine-tune a 7B model that reaches 25% pass@1 on HarmonyOS code generation, beating untuned GPT-4o at 17.59%.
A survey of methods, benchmarks, and open challenges for large language models in multilingual code generation and translation.
citing papers explorer
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Improving LLM Code Reasoning via Semantic Equivalence Self-Play with Formal Verification
A self-play method using formal proofs and counterexamples trains LLMs to better judge semantic equivalence of Haskell code, yielding up to 13.3 percentage point gains on EquiBench.
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Knowledge-Graph-Driven Data Synthesis for Low-Resource Software Development: A HarmonyOS Case Study
APIKG4Syn synthesizes API-oriented training data via knowledge graphs and Monte Carlo search to fine-tune a 7B model that reaches 25% pass@1 on HarmonyOS code generation, beating untuned GPT-4o at 17.59%.
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Large Language Models for Multilingual Code Intelligence: A Survey
A survey of methods, benchmarks, and open challenges for large language models in multilingual code generation and translation.