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cs.LG2026
The Laws of Context Allocation: Causal Measurement and Closed-Loop Orchestration in Generative Search
Peiyang Liu, Xi Wang, Di Liang +1
As Retrieval-Augmented Generation (RAG) shifts toward diverse portfolio generation, it is stymied by two critical bottlenecks: flawed measurement of evidence utilization, and subop…
cs.LG2026
Parameter Importance is Not Static: Evolving Parameter Isolation for Supervised Fine-Tuning
Zekai Lin, Chao Xue, Di Liang +8
Supervised Fine-Tuning (SFT) of large language models often suffers from task interference and catastrophic forgetting. Recent approaches alleviate this issue by isolating task-cri…