4 papers
Speculative Decoding in Decentralized LLM Inference: Turning Communication Latency into Computation Throughput
Jingwei Song, Wanyi Chen, Xinyuan Song +7
Speculative decoding accelerates large language model (LLM) inference by using a lightweight draft model to propose tokens that are later verified by a stronger target model. While…
Lattica: A Decentralized Cross-NAT Communication Framework for Scalable AI Inference and Training
Ween Yang, Jason Liu, Suli Wang +4
The rapid expansion of distributed Artificial Intelligence (AI) workloads beyond centralized data centers creates a demand for new communication substrates. These substrates must o…
SEDM: Selective Self-Evolving Distributed Memory for Agents
Yichen Liu, Haoran Xu, Jiacong Hu +20
Agents in a society can reuse each other's experience, but indiscriminate memory use increases processing cost and can reduce task success. We present SEDM (Selective Self-Evolving…
VeriLLM: A Lightweight Framework for Publicly Verifiable Decentralized Inference
Ke Wang, Zishuo Zhao, Xinyuan Song +7
Decentralized inference provides a scalable and resilient paradigm for serving large language models (LLMs), enabling fragmented global resource utilization and reducing reliance o…