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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.LG2026
Evaluating AI Grading on Real-World Handwritten College Mathematics: A Large-Scale Study Toward a Benchmark
Zhiqi Yu, Xingping Liu, Haobin Mao +4
Grading in large undergraduate STEM courses often yields minimal feedback due to heavy instructional workloads. We present a large-scale empirical study of AI grading on real, hand…
cs.LG2024
Learning Causal Transition Matrix for Instance-dependent Label Noise
Jiahui Li, Tai-Wei Chang, Kun Kuang +3
Noisy labels are both inevitable and problematic in machine learning methods, as they negatively impact models' generalization ability by causing overfitting. In the context of lea…