collaborators

5 papers

cs.LG2026

Conformal Cascade: Distribution-Free Accuracy Guarantees for Multi-Tier LLM Inference

Yifan Dou, Shikan Lian, Shikan Fang +1

Large language model (LLM) cascades reduce inference cost by routing easy queries to a small model and deferring hard queries to a larger one. Production cascades govern this defer…

cs.AI2026

ConsistencyGate: Preventing Memory Contamination in LLM Agents via Self-Consistency Admission Control

Yan Zhang, Shibo Li

LLM agents that operate over many turns accumulate facts in an external memory store and reuse them as premises for downstream reasoning. A hallucinated fact written at one step th…

cs.LG2026

Verbalized Particle Posterior: Bayesian Inference over Natural Language Hypotheses

Yan Zhang, Shikan Lian, Shibo Li

Verbalized Machine Learning (VML) parameterizes a model as a natural-language prompt that an LLM evaluates as f(x; theta). The framework is interpretable, but it commits to a singl…

cs.LG2026

Regime-Adaptive Bayesian Optimization via Dirichlet Process Mixtures of Gaussian Processes

Yan Zhang, Xuefeng Liu, Sipeng Chen +3

Standard Bayesian Optimization (BO) assumes uniform smoothness across the search space an assumption violated in multi-regime problems such as molecular conformation search through…

cs.LG2025

Dynamic Bayesian Optimization Framework for Instruction Tuning in Partial Differential Equation Discovery

Junqi Qu, Yan Zhang, Shangqian Gao +1

Large Language Models (LLMs) show promise for equation discovery, yet their outputs are highly sensitive to prompt phrasing, a phenomenon we term instruction brittleness. Static pr…