Papers/2608.13566
🧪 Test?View on arXiv

Don't Claim Benchmark-Oriented Optimization Improves General Coding Capability -- Diverse Evaluation Is Required

Not specified in the provided content

benchmarkingevaluationgeneralizationmodel assessment
2608.13566
Builder Relevance
70%
1h ago

Abstract

The paper argues that relying on a small set of coding benchmarks for evaluating coding capability leads to a misleading assessment of general coding ability.

Reality Card

Core Claim

Optimization for coding benchmarks does not translate to improved general coding capability, as evidenced by the lack of cross-task transfer and limited gains from benchmark optimization.

Method / Result

Post-trained checkpoints show little cross-task transfer, with no significant improvements on tasks or LiveCodeBench.

Limitations

The reliance on a small number of benchmarks creates a gap in reliable evaluation standards, making reproducibility and generalization difficult.

Paper to code

Verified implementation resources so builders can test the paper’s claims instead of stopping at the abstract.

No verified implementation link has been attached yet. AIBuzzHub will keep this panel separate from unverified search results.
← Back to all papers