11 citations · 35 across the 19 of their papers we have counts for
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cs.AI2026
No Universal Signal Predicts Sample-Level LLM Regression under Version Updates
Jia Sheng, Yiwei Lu
Frontier LLMs are updated frequently and typically outperform their predecessors in aggregate. But aggregate gains say little about individual samples: an update can still cause sa…
cs.SE2026
CASPER-Change-Aware Slice Prioritization for Efficient Regression Testing of LLM-based systems
Biruk Asmare Muse, Lionel Briand, Yiwei Lu +1
Regression testing for LLM-based systems poses unique challenges because individual regression instances provide limited information about system-level regressions. A failure in a…
cs.LG2026
Sequential Data Poisoning in LLM Post-Training
Jack Sanderson, Yihan Wang, Xiaoqian Lu +2
LLM post-training proceeds through multiple stages, e.g., supervised fine-tuning (SFT) followed by reinforcement learning from human feedback (RLHF) or direct preference optimizati…