8 papers
FIDES: A Concordance Protocol for LLM-Generated Trading Strategies
Arther Tian, Alex Ding, Simon Wu +1
An LLM asked for a trading strategy returns three artifacts at once: a natural-language rationale, an executable implementation, and once run, a track record. Whether these are the…
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…
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…
SOP-Bench: Complex Industrial SOPs for Evaluating LLM Agents
Subhrangshu Nandi, Arghya Datta, Rohith Nama +21
LLM-based agents struggle to execute complex, multi-step Standard Operating Procedures (SOPs) that are fundamental to industrial automation. Existing benchmarks fail to capture the…
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…