This work provides a new method for fine-tuning models with sparse attention that works for any KV cache policy, runs on a moderate hardware budget, and allows the model to co-adapt with the policy, often outperforming models trained with exact attention (sequence parallelism).
Matthias W. Seeger, Zeyu Zhang, Vihang Patil et al.· 0 citations
This work analyzes query logs from MotherDuck, a cloud analytics platform built on DuckDB, to show that real-world SQL extends far beyond analytical queries, with users frequently employing dialect-specific functionality that LLMs struggle with.
Till Döhmen, Adithya Krishnan, Hamilton Ulmer et al.· The VLDB journal· 0 citations
The factors underlying performance differences across matcher architectures are clarified and motivate future research and benchmark designs that better disentangle architectural choices from model-level factors while explicitly evaluating distribution shift and cross-dataset transferability.
Zeyu Zhang, Xue Li, Iacer Calixto et al.· 0 citations