9 papers
UniQL: Towards Dialect-Universal Benchmarking for Text-to-SQL
Jianling Gao, Chongyang Tao, Jiayuan Bai +7
Existing text-to-SQL benchmarks are largely centered on SQLite, making it difficult to evaluate whether models can generalize across heterogeneous SQL dialects. However, real-world…
Unsat Core Prediction through Polarity-Aware Representation Learning over Clause-Literal Hypergraphs
Zhenchao Sun, Shuai Ma, Ping Lu +1
Graph neural networks have been widely used in Boolean satisfiability (SAT) tasks to learn structural information from SAT formulas. The goal of these studies is to solve SAT insta…
BCTuner: LLM-Guided Monte Carlo Tree Search for Efficient Blockchain Knob Tuning
Yaoyi Deng, Chongyang Tao, Mingxuan Li +4
Knob tuning plays a critical role in improving the performance of permissioned blockchains. However, efficient tuning remains challenging due to the architectural complexity of blo…
Empowering Targeted Neighborhood Search via Hyper Tour for Large-Scale TSP
Tongkai Lu, Shuai Ma, Chongyang Tao
Traveling Salesman Problem (TSP) is a classic NP-hard problem that has garnered significant attention from both academia and industry. While neural-based methods have shown promise…
EvolSQL: Structure-Aware Evolution for Scalable Text-to-SQL Data Synthesis
Xuanguang Pan, Chongyang Tao, Jiayuan Bai +5
Training effective Text-to-SQL models remains challenging due to the scarcity of high-quality, diverse, and structurally complex datasets. Existing methods either rely on limited h…
AIR: Post-training Data Selection for Reasoning via Attention Head Influence
Jinrui Liu, Jeff Wu, Xuanguang Pan +3
LLMs achieve remarkable multi-step reasoning capabilities, yet effectively transferring these skills via post-training distillation remains challenging. Existing data selection met…