{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Eye on AI Weekly Research Watch","title":"Multi-LCB: Extending LiveCodeBench to Multiple Programming Languages","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/626568ff\"></iframe>","width":"100%","height":180,"duration":181,"description":"Code generation benchmarks have become central to how the AI community measures progress, but nearly all of them default to Python — a language that dominates training data and may be inflating model scores. Real software engineering, however, demands fluency across Rust, Go, Java, TypeScript, and many others. Multi-LCB extends the established LiveCodeBench framework to twelve languages while preserving its contamination controls, exposing a clear pattern of Python overfitting in leading models. This benchmark directly supports decisions about which models to deploy in polyglot engineering environments, and highlights where additional training investment is needed.","thumbnail_url":"https://img.transistorcdn.com/NzT0CgVgc5EYmTYVshPdpb6IAFKCteYvSiwlDGdBSuw/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS80ZDk4/YjBiMGUyYzJiNzIw/YTRjYjc4OTM2YzM4/OGQ5Ny5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}