7 papers · 1 filter
Model Collapse as Cultural Evolution
Dongxin Guo, Jikun Wu, Siu Ming Yiu
Model collapse, the progressive degradation of LLMs trained on their own outputs, has been characterized statistically but lacks a linguistic explanation for which structures degra…
Do Language Models Know What Not to Say? Causal Evidence for Statistical Preemption in LLMs
Dongxin Guo, Jikun Wu, Siu Ming Yiu
How do learners acquire knowledge of what is unacceptable without negative evidence? Construction Grammar proposes statistical preemption: exposure to a conventional form (e.g., "d…
Sparse Autoencoders Map Brain-LLM Alignment onto Cortical Semantic Topography
Dongxin Guo, Jikun Wu, Siu Ming Yiu
Intermediate layers of large language models (LLMs) best predict human brain responses to language, one of the most robust findings in computational neurolinguistics, yet why remai…
Brain-LLM Alignment Tracks Training Data, Not Typology
Dongxin Guo, Jikun Wu, Siu Ming Yiu
Brain-LLM alignment is well established in English, yet the brain's language network is neuroanatomically universal across languages. Does alignment also generalize cross-linguisti…
ComplianceNLP: Knowledge-Graph-Augmented RAG for Multi-Framework Regulatory Gap Detection
Dongxin Guo, Jikun Wu, Siu Ming Yiu
Financial institutions must track over 60,000 regulatory events annually, overwhelming manual compliance teams; the industry has paid over USD 300 billion in fines and settlements…
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…