6 papers
Unified Lookup-Table Inference with Signed-Digit K/V Caches for Ternary LLMs
Ziang Duan, Jiajun Wu, Zetian Chen +8
Ternary LLMs make their weight-dominated projections compact and efficient, but attention remains a mismatch: its K/V cache is created online and is typically processed by a separa…
SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement
Arther Tian, Alex Ding, Simon Wu +1
Procuring supervised fine-tuning (SFT) data forces a buyer to decide, before any downstream training, whether a candidate corpus is worth acquiring. We present \sys{}, a statistics…
Nexusformer: Nonlinear Attention Expansion for Stable and Inheritable Transformer Scaling
Weijie Zhao, Mingquan Liu, Bolun Wang +4
Scaling Transformers typically necessitates training larger models from scratch, as standard architectures struggle to expand without discarding learned representations. We identif…
PoQ-Judge: A Multi-Architecture Evaluation Framework for Cost-Aware Proof-of-Quality in Decentralized LLM Inference
Arther Tian, Alex Ding, Frank Chen +2
Decentralized LLM inference networks need lightweight, reference-free quality evaluation for Proof of Quality (PoQ). We present PoQ-Judge, a framework that trains dedicated judge m…
A Multi-Dimensional Quality Scoring Framework for Decentralized LLM Inference with Proof of Quality
Arther Tian, Alex Ding, Frank Chen +2
Decentralized large language model (LLM) inference networks can pool heterogeneous compute to scale serving, but they require lightweight and incentive-compatible mechanisms to ass…
Adaptive and Robust Cost-Aware Proof of Quality for Decentralized LLM Inference Networks
Arther Tian, Alex Ding, Frank Chen +2
Decentralized large language model inference networks require lightweight mechanisms to reward high quality outputs under heterogeneous latency and cost. Proof of Quality provides…