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How UK AISI and EvalEval Are Making Benchmark Results Reproducible
AISI and EvalEval have previously collaborated on research that began at a joint workshop alongside NeurIPS 2025 , and feedback from the Institute has helped shape the Every Eval Ever (EEE) schema . This next phase of the collaboration puts that shared infrastructure into practice.
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This issue is for keeping track of the recurrent Whisper asks as well as the linked on-going efforts to support that feature, if any. When a feature request has no linked PR, feel free to claim the work here if you want to help! - Related issues: https://github.com/vllm-project/vllm/issues/19556, https://github.com/vl…
vllm-project/vllmAbout 4 hr语音推理部署
Cross-checked · GitHub Good First Issues · aiVerified Sep 23, 2026Add to path
These enhancements are to have a better UX when using foreach_map, suggested in a few places, but most recently, https://github.com/pytorch/pytorch/issues/158371#issuecomment-3088757068 These enhancements should allow easier compiler-first custom optimizer implementations. cc @chauhang @penguinwu @voznesenskym @EikanW…
pytorch/pytorchAbout 4 hr编译器性能优化
Cross-checked · GitHub Good First Issues · aiConfirmed still open · Sep 23, 2026Add to path
That is embarrassing onstage. In production, it is a reliability problem: a workflow that succeeded once may fail the next time a user makes the same request. For mission-critical work, such as reconciling a financial transaction or checking a contract for an obligation, that can be a showstopper.
Hugging FacePublished Sep 16, 2026
Cross-checked · Hugging Face BlogVerified Sep 23, 2026
Structured output is one of the most common real-world tasks for LLMs, yet most benchmarks fold it into broader reasoning or extraction scores rather than measuring it on its own. Whether a model reliably returns valid, parseable output in the requested format and shape — schema compliance — is often what decides whet…
Hugging FacePublished Sep 3, 2026
Cross-checked · Hugging Face BlogVerified Sep 23, 2026