9 citations · 15 across the 31 of their papers we have counts for
3 papers · 1 filter
WarriorCoder: Learning from Expert Battles to Augment Code Large Language Models
Huawen Feng, Pu Zhao, Qingfeng Sun +8
Despite recent progress achieved by code large language models (LLMs), their remarkable abilities are largely dependent on fine-tuning on the high-quality data, posing challenges f…
REFA: Reference Free Alignment for multi-preference optimization
Taneesh Gupta, Rahul Madhavan, Xuchao Zhang +2
To mitigate reward hacking from response verbosity, modern preference optimization methods are increasingly adopting length normalization (e.g., SimPO, ORPO, LN-DPO). While effecti…
Intelligent Router for LLM Workloads: Improving Performance Through Workload-Aware Load Balancing
Kunal Jain, Anjaly Parayil, Ankur Mallick +10
Large Language Model (LLM) workloads have distinct prefill and decode phases with different compute and memory requirements which should ideally be accounted for when scheduling in…