5 papers
psRL: Efficient Training for Agentic AI via Training-Time Prefix Sharing
Mianjie Yu, Zizhao Mo, Huanyu Qu +8
In modern agentic AI training, the system bottleneck is shifting from rollout to update. Emerging sampling strategies such as tree-structured and step-wise RL greatly increase trai…
Meta-Soft: Leveraging Composable Meta-Tokens for Context-Preserving KV Cache Compression
Wei Luo, Yi Huang, Songchen Ma +3
The KV cache used in large language models has linearly growing time complexity, so LLMs face memory blow-up and reduced decoding efficiency when they process long contexts. Curren…
Loosely-Structured Software: Engineering Context, Structure, and Evolution Entropy in Runtime-Rewired Multi-Agent Systems
Weihao Zhang, Yitong Zhou, Huanyu Qu +1
As LLM-based multi-agent systems (MAS) become more autonomous, their free-form interactions increasingly dominate system behavior. However, scaling the number of agents often ampli…
CompAir: Synergizing Complementary PIMs and In-Transit NoC Computation for Efficient LLM Acceleration
Hongyi Li, Songchen Ma, Huanyu Qu +5
The rapid advancement of Large Language Models (LLMs) has revolutionized various aspects of human life, yet their immense computational and energy demands pose significant challeng…
MLDSE: Scaling Design Space Exploration Infrastructure for Multi-Level Hardware
Huanyu Qu, Weihao Zhang, Junfeng Lin +4
To efficiently support large-scale NNs, multi-level hardware, leveraging advanced integration and interconnection technologies, has emerged as a promising solution to counter the s…