一作ICLR 2026Poster· General Machine Learning / Probabilistic Methods
Don’t Pass@k: A Bayesian Framework for Large Language Model Evaluation
Mohsen Hariri · Amirhossein Samandar · Michael Hinczewski · Vipin Chaudhary
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Mohsen Hariri · Amirhossein Samandar · Michael Hinczewski · Vipin Chaudhary
Mohsen Hariri · Michael Hinczewski · Jing Ma · Vipin Chaudhary
Test-time scaling evaluates reasoning LLMs by sampling multiple outputs per prompt, but ranking models in this regime remains underexplored. We formalize dense benchmark ranking under test-time scaling and introduce Scorio, a library that implements statistical ranking methods such as paired-comp...
Mohsen Hariri · Alan Luo · Weicong Chen · Tianyi Zhang · Qifan Wang · Xiaotian Han · Vipin Chaudhary
Large Language Models (LLMs) suffer inference-time memory bottlenecks dominated by the attention Key-Value (KV) cache, which scales with model size and context length. While KV-cache quantization alleviates this cost, bit allocation between keys and values is often tuned heuristically, lacking th...