9 citations · 11 across the 18 of their papers we have counts for
5 papers · 1 filter
Super Apriel: One Checkpoint, Many Speeds
SLAM Labs, :, Oleksiy Ostapenko +13
We release Super Apriel, a 15B-parameter supernet in which every decoder layer provides four trained mixer choices -- Full Attention (FA), Sliding Window Attention (SWA), Kimi Delt…
Apriel-H1: Towards Efficient Enterprise Reasoning Models
Oleksiy Ostapenko, Luke Kumar, Raymond Li +10
Large Language Models (LLMs) achieve remarkable reasoning capabilities through transformer architectures with attention mechanisms. However, transformers suffer from quadratic time…
Apriel-Nemotron-15B-Thinker
Shruthan Radhakrishna, Soham Parikh, Gopal Sarda +32
While large language models (LLMs) have achieved remarkable reasoning capabilities across domains like code, math and other enterprise tasks, their significant memory and computati…
DNR Bench: Benchmarking Over-Reasoning in Reasoning LLMs
Masoud Hashemi, Oluwanifemi Bamgbose, Sathwik Tejaswi Madhusudhan +3
Test-time scaling has significantly improved large language model performance, enabling deeper reasoning to solve complex problems. However, this increased reasoning capability als…
Revitalizing Saturated Benchmarks: A Weighted Metric Approach for Differentiating Large Language Model Performance
Bryan Etzine, Masoud Hashemi, Nishanth Madhusudhan +4
Existing benchmarks are becoming saturated and struggle to separate model performances due to factors like data contamination and advancing LLM capabilities. This paper introduces…