3 papers
cs.LG2026
MetaKube: An Experience-Aware LLM Framework for Kubernetes Failure Diagnosis
Wei Sun, Ting Wang, Xinran Tian +4
Existing LLM-based Kubernetes diagnostic systems cannot learn from operational experience, operating on static knowledge bases without improving from past resolutions. We present M…
cs.AI2026
Probing RLVR training instability through the lens of objective-level hacking
Yiming Dong, Kun Fu, Haoyu Li +5
Prolonged reinforcement learning with verifiable rewards (RLVR) has been shown to drive continuous improvements in the reasoning capabilities of large language models, but the trai…
cs.CL2025
From Macro to Micro: Probing Dataset Diversity in Language Model Fine-Tuning
Haoyu Li, Xuhong Li, Yiming Dong +1
Dataset diversity plays a pivotal role for the successful training of many machine learning models, particularly in the supervised fine-tuning (SFT) stage of large language model (…