3 citations · 3 across the 12 of their papers we have counts for
4 papers · 1 filter
MoE Proxy Models for Low-Cost Failure Reproduction and Diagnosis in LLM RL Post-Training
Yikai Wang, Chuansai Zhou, Yuhang Zhou +10
Reinforcement learning (RL) post-training of large language models (LLMs) is computationally intensive and involves complex system pipelines with substantial debugging overhead. In…
Understanding Large Language Models in Your Pockets: Performance Study on COTS Mobile Devices
Jie Xiao, Qianyi Huang, Xu Chen +1
As large language models (LLMs) increasingly integrate into every aspect of our work and daily lives, there are growing concerns about user privacy, which push the trend toward loc…
Scaling Graph Chain-of-Thought Reasoning: A Multi-Agent Framework with Efficient LLM Serving
Chengying Huan, Ziheng Meng, Yongchao Liu +11
Graph Chain-of-Thought (Graph-CoT) enables large language models (LLMs) to perform step-by-step reasoning over graph-structured knowledge, but existing pipelines suffer from low ac…
HiVeGen -- Hierarchical LLM-based Verilog Generation for Scalable Chip Design
Jinwei Tang, Jiayin Qin, Kiran Thorat +5
With Large Language Models (LLMs) recently demonstrating impressive proficiency in code generation, it is promising to extend their abilities to Hardware Description Language (HDL)…