collaborators

6 papers

cs.AI2026

Brick-DICL: Dynamic In-Context Learning for Automated Brick Schema Classification

Yiyue Qian, Shinan Zhang, Huan Song +3

Building Management Systems (BMS) are essential for optimizing energy efficiency and operational performance in modern buildings. However, the lack of standardization across BMS po…

cs.LG2026

AME-TS: Anchored Mixture-of-Experts for Time Series Forecasting

Rui Wang, Renhao Xue, Ray Razi +2

Time series forecasting models are increasingly scaled through large Transformer backbones, yet most existing approaches process all series through a shared dense computation path…

cs.AI2026

Silicon Bureaucracy and AI Test-Oriented Education: Contamination Sensitivity and Score Confidence in LLM Benchmarks

Yiliang Song, Hongjun An, Jiangan Chen +4

Public benchmarks increasingly govern how large language models (LLMs) are ranked, selected, and deployed. We frame this benchmark-centered regime as Silicon Bureaucracy and AI Tes…

cs.CL2026

Ruyi2.5 Technical Report

Huan Song, Shuyu Tian, Qingfei Zhao +5

We present Ruyi2.5, a multimodal familial model built on the AI Flow framework. Extending Ruyi2's "Train Once, Deploy Many" paradigm to the multimodal domain, Ruyi2.5 constructs a…

cs.LG2025

Breaking the Safety-Capability Tradeoff: Reinforcement Learning with Verifiable Rewards Maintains Safety Guardrails in LLMs

Dongkyu Derek Cho, Huan Song, Arijit Ghosh Chowdhury +6

Fine-tuning large language models (LLMs) for downstream tasks typically exhibit a fundamental safety-capability tradeoff, where improving task performance degrades safety alignment…

cs.AI2025

Learning from Generalization Patterns: An Evaluation-Driven Approach to Enhanced Data Augmentation for Fine-Tuning Small Language Models

Huan Song, Deeksha Razdan, Yiyue Qian +6

Small Language Models (SLMs) offer compelling advantages in deployment cost and latency, but their accuracy often lags behind larger models, particularly for complex domain-specifi…