5 papers · 1 filter
AdaptEvolve: Improving Efficiency of Evolutionary AI Agents through Adaptive Model Selection
Pretam Ray, Pratik Prabhanjan Brahma, Zicheng Liu +1
Evolutionary agentic systems intensify the trade-off between computational efficiency and reasoning capability by repeatedly invoking large language models (LLMs) during inference.…
Instella: Fully Open Language Models with Stellar Performance
Jiang Liu, Jialian Wu, Xiaodong Yu +10
Large language models (LLMs) have demonstrated remarkable performance across a wide range of tasks, yet the majority of high-performing models remain closed-source or partially ope…
SAND-Math: Using LLMs to Generate Novel, Difficult and Useful Mathematics Questions and Answers
Chaitanya Manem, Pratik Prabhanjan Brahma, Prakamya Mishra +2
The demand for Large Language Models (LLMs) at multiple scales, capable of sophisticated and sound mathematical reasoning, continues to grow. However, the development of performant…
Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks
Jianghui Wang, Vinay Joshi, Saptarshi Majumder +7
The demand for AI-generated GPU kernels is rapidly growing, influenced by the need for scalable, hardware-optimized solutions in both industry and academia. As deep learning worklo…
TaDA: Training-free recipe for Decoding with Adaptive KV Cache Compression and Mean-centering
Vinay Joshi, Pratik Prabhanjan Brahma, Zicheng Liu +1
The key-value (KV) cache in transformer models is a critical component for efficient decoding or inference, yet its memory demands scale poorly with sequence length, posing a major…