3 papers
cs.CL2025
Efficient Speculative Decoding for Llama at Scale: Challenges and Solutions
Bangsheng Tang, Carl Chengyan Fu, Fei Kou +35
Speculative decoding is a standard method for accelerating the inference speed of large language models. However, scaling it for production environments poses several engineering c…
cs.CL2025
ZeroSumEval: An Extensible Framework For Scaling LLM Evaluation with Inter-Model Competition
Hisham A. Alyahya, Haidar Khan, Yazeed Alnumay +2
We introduce ZeroSumEval, a dynamic, competition-based, and evolving evaluation framework for Large Language Models (LLMs) that leverages competitive games. ZeroSumEval encompasses…
cs.CL2024
LLäMmlein: Transparent, Compact and Competitive German-Only Language Models from Scratch
Jan Pfister, Julia Wunderle, Andreas Hotho
We create two German-only decoder models, LLäMmlein 120M and 1B, transparently from scratch and publish them, along with the training data, for the German NLP research community to…