4 papers
Toward User-Conditioned Evaluation of Personal LLM Agents under Temporal Interventions
Pin Qian, Su Wang, Yihang Chen +5
Personal agents maintain memories, learned skills, tool configurations, and policy state that evolve with each user. Existing agent benchmarks often evaluate these capabilities in…
Coresets Before Score Sets: Evaluation-Unsupervised Prompt Subset Selection for LLM Benchmarks
Jihan Yao, Gantavya Bhatt, Arnav Das +16
We study LLM benchmark coreset selection: selecting a small subset of prompts over multiple benchmarks whose induced model scores and rankings approximate those obtained from the f…
Relevant Is Not Warranted: Evidence-Force Calibration for Cited RAG
Pin Qian, Su Wang, Xiaoyuan Wang +7
Cited RAG evaluation often treats visible sources as a grounding signal, but a real, topically relevant citation can still under-warrant the attached wording. We study this diagnos…
Efficient Federated Learning with Heterogeneous Data and Adaptive Dropout
Ji Liu, Beichen Ma, Qiaolin Yu +7
Federated Learning (FL) is a promising distributed machine learning approach that enables collaborative training of a global model using multiple edge devices. The data distributed…