7 papers
SAGA: Workflow-Atomic Scheduling for AI Agent Inference on GPU Clusters
Dongxin Guo, Jikun Wu, Siu Ming Yiu
AI agents execute tens to hundreds of chained LLM calls per task, yet GPU schedulers treat each call as independent, discarding gigabytes of intermediate state between steps and in…
RouteNLP: Closed-Loop LLM Routing with Conformal Cascading and Distillation Co-Optimization
Dongxin Guo, Jikun Wu, Siu Ming Yiu
Serving diverse NLP workloads with large language models is costly: at one enterprise partner, inference costs exceeded $200K/month despite over 70% of queries being routine tasks…
SafeAnchor: Preventing Cumulative Safety Erosion in Continual Domain Adaptation of Large Language Models
Dongxin Guo, Jikun Wu, Siu Ming Yiu
Safety alignment in large language models is remarkably shallow: it is concentrated in the first few output tokens and reversible by fine-tuning on as few as 100 adversarial exampl…
Closing the Theory-Practice Gap in Spiking Transformers via Effective Dimension
Dongxin Guo, Jikun Wu, Siu Ming Yiu
Spiking transformers achieve competitive accuracy with conventional transformers while offering - energy efficiency on neuromorphic hardware, yet no theoretical frame…
When Do Early-Exit Networks Generalize? A PAC-Bayesian Theory of Adaptive Depth
Dongxin Guo, Jikun Wu, Siu Ming Yiu
Early-exit neural networks enable adaptive computation by allowing confident predictions to exit at intermediate layers, achieving 2-8 inference speedup. Despite widespread…
Geometric Metrics for MoE Specialization: From Fisher Information to Early Failure Detection
Dongxin Guo, Jikun Wu, Siu Ming Yiu
Expert specialization is fundamental to Mixture-of-Experts (MoE) model success, yet existing metrics (cosine similarity, routing entropy) lack theoretical grounding and yield incon…
Coalition Formation in LLM Agent Networks: Stability Analysis and Convergence Guarantees
Dongxin Guo, Jikun Wu, Siu-Ming Yiu
Large Language Model (LLM) agents are increasingly deployed in multi-agent systems requiring strategic coordination. While recent work has analyzed LLM behavior in two-player games…