collaborators

7 papers

cs.AI2026

Learning to Adapt Cross-Domain Preferences via Meta-LoRA for LLM Personalization

Xuefei Wang, Jun Han, Zixuan Wang +4

Cross-domain zero- or few-shot personalization aims to generate user-preferred responses in unseen conversational domains from only a handful of target-domain interactions. Existin…

cs.LG2026

MasFACT: Continual Multi-Agent Topology Learning via Geometry-Aware Posterior Transfer

Xuefei Wang, Jialu Wang, Fengbo Zhang +6

Multi-agent systems (MAS) powered by large language models (LLMs) have emerged as a powerful paradigm for complex problem solving, where performance critically depends on the under…

cs.CE2026

The Alpha Illusion: Reported Alpha from LLM Trading Agents Should Not Be Treated as Deployment Evidence

Yuxuan Ye, Jun Han, Ao Hu +7

End-to-end LLM trading agents have moved quickly from research curiosity to a small ecosystem of named systems, including FinCon, FinMem, TradingAgents, FinAgent, QuantAgent, and F…

cs.CL2026

MedFabric and EtHER: A Data-Centric Framework for Word-Level Fabrication Generation and Detection in Medical LLMs

Tung Sum Thomas Kwok, Qian Qian, Xiaofeng Lin +8

Large Language Models exhibit strong reasoning and semantic understanding capabilities but often hallucinate in domains that require expert knowledge, among which fabrications, the…

cs.LG2026

Fast and Effective On-policy Distillation from Reasoning Prefixes

Dongxu Zhang, Zhichao Yang, Sepehr Janghorbani +6

On-policy distillation (OPD), which samples trajectories from the student model and supervises them with a teacher at the token level, avoids relying solely on verifiable terminal…

cs.AI2026

Health-SCORE: Towards Scalable Rubrics for Improving Health-LLMs

Zhichao Yang, Sepehr Janghorbani, Dongxu Zhang +6

Rubrics are essential for evaluating open-ended LLM responses, especially in safety-critical domains such as healthcare. However, creating high-quality and domain-specific rubrics…