3 papers
cs.LG2026
Measuring Five-Nines Reliability: Sample-Efficient LLM Evaluation in Saturated Benchmarks
Eungyeup Kim, Chenchen Gu, Vashisth Tiwari +1
While existing benchmarks demonstrate the near-perfect performance of large language models (LLMs) on various tasks, this apparent saturation often obscures the need for rigorous e…
cs.CL2025
Energy Considerations of Large Language Model Inference and Efficiency Optimizations
Jared Fernandez, Clara Na, Vashisth Tiwari +3
As large language models (LLMs) scale in size and adoption, their computational and environmental costs continue to rise. Prior benchmarking efforts have primarily focused on laten…
cs.CL2025
MagicDec: Breaking the Latency-Throughput Tradeoff for Long Context Generation with Speculative Decoding
Ranajoy Sadhukhan, Jian Chen, Zhuoming Chen +7
Large Language Models (LLMs) have become more prevalent in long-context applications such as interactive chatbots, document analysis, and agent workflows, but it is challenging to…