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cs.LG2026

RouteJudge: An Open Platform for Reproducible and Preference-Aware LLM Routing

Guannan Lai, Haoran Hu, Han-Jia Ye

We present RouteJudge, an online pairwise preference evaluation framework for LLM routing systems, with a public platform available at https://routejudge.cn. Different from model-l…

cs.LG2026

From Sampled Outcomes to Capability Distributions: Rethinking Supervision for LLM Routing

Guannan Lai, Haoran Hu, Long Chen +2

Existing LLM routing methods often construct supervision from a single sampled response for each query--model pair. Because LLM generation is stochastic, however, such an observati…

cs.LG2025

The Lie of the Average: How Class Incremental Learning Evaluation Deceives You?

Guannan Lai, Da-Wei Zhou, Xin Yang +1

Class Incremental Learning (CIL) requires models to continuously learn new classes without forgetting previously learned ones, while maintaining stable performance across all possi…

cs.LG2025

Order-Robust Class Incremental Learning: Graph-Driven Dynamic Similarity Grouping

Guannan Lai, Yujie Li, Xiangkun Wang +3

Class Incremental Learning (CIL) aims to enable models to learn new classes sequentially while retaining knowledge of previous ones. Although current methods have alleviated catast…

cs.LG2025

Exploring Open-world Continual Learning with Knowns-Unknowns Knowledge Transfer

Yujie Li, Guannan Lai, Xin Yang +3

Open-World Continual Learning (OWCL) is a challenging paradigm where models must incrementally learn new knowledge without forgetting while operating under an open-world assumption…

cs.LG2025

A New Perspective on Privacy Protection in Federated Learning with Granular-Ball Computing

Guannan Lai, Yihui Feng, Xin Yang +5

Federated Learning (FL) facilitates collaborative model training while prioritizing privacy by avoiding direct data sharing. However, most existing articles attempt to address chal…