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Vashisth Tiwari

2 accepted papers

2025

Energy Considerations of Large Language Model Inference and Efficiency Optimizations

ACL 2025long

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 latency reduction in idealized settings, often overlooking the diverse real-world inference workloads that shape energy use.…

Cited by 0SourcePDFScholar
2025

MagicDec: Breaking the Latency-Throughput Tradeoff for Long Context Generation with Speculative Decoding

ICLR 2025poster

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 serve long-context requests with low latency and high throughput. Speculative decoding (SD) is a widely used technique t…