6 papers
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…
SetAD: Semi-Supervised Anomaly Learning in Contextual Sets
Jianling Gao, Chongyang Tao, Xuelian Lin +2
Semi-supervised anomaly detection (AD) has shown great promise by effectively leveraging limited labeled data. However, existing methods are typically structured around scoring ind…
Dynamic Stratified Contrastive Learning with Upstream Augmentation for MILP Branching
Tongkai Lu, Shuai Ma, Chongyang Tao
Mixed Integer Linear Programming (MILP) is a fundamental class of NP-hard problems that has garnered significant attention from both academia and industry. The Branch-and-Bound (B\…
JudgeSQL: Reasoning over SQL Candidates with Weighted Consensus Tournament
Jiayuan Bai, Xuan-guang Pan, Chongyang Tao +1
Text-to-SQL is a pivotal task that bridges natural language understanding and structured data access, yet it remains fundamentally challenging due to semantic ambiguity and complex…
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…