Coding LLMs exhibit detrimental semantic collapse on underspecified prompts by producing consistent but incorrect code rather than incoherent variations, affecting 3-32% of tasks across MBPP, HumanEval, and LiveCodeBench.
Natural language to code translation with execution,
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2026 2verdicts
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AdaTrans uses strategy-driven RAG, error-stratified transformation, and multi-stage validation to reach 95.51% mean compilation pass rate and 81.09% solve rate on 104 algorithmic problems with only 1.19% unsafe files.
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Underspecification does not imply Incoherence: The Risks of Semantic Collapse in Coding Models
Coding LLMs exhibit detrimental semantic collapse on underspecified prompts by producing consistent but incorrect code rather than incoherent variations, affecting 3-32% of tasks across MBPP, HumanEval, and LiveCodeBench.
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AdaTrans: Automated C to Rust Transformation via Error-Adaptive Repair
AdaTrans uses strategy-driven RAG, error-stratified transformation, and multi-stage validation to reach 95.51% mean compilation pass rate and 81.09% solve rate on 104 algorithmic problems with only 1.19% unsafe files.