13 citations · 24 across the 10 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2026
Pick the Mixture, Not the Samples: Combinatorial Data Selection for LLMs
Luyang Zhang, Jialu Wang, Bebei Li
Data selection for LLM fine-tuning faces two facts about real training: data pools draw from many distinct domains, and evaluation spans diverse tasks. As a result, the same sample…
cs.LG2026
When Attribution Patching Lies: Diagnosis and a Second-Order Correction
Luyang Zhang, Jialu Wang
A central goal of mechanistic interpretability is to identify which internal components causally drive a language model's behavior. Because these importance estimates serve as the…
cs.LG2026
MasFACT: Continual Multi-Agent Topology Learning via Geometry-Aware Posterior Transfer
Xuefei Wang, Jialu Wang, Fengbo Zhang +6
Multi-agent systems (MAS) powered by large language models (LLMs) have emerged as a powerful paradigm for complex problem solving, where performance critically depends on the under…