Papers by Kuan Xu
SeaD: End-to-end Text-to-SQL Generation with Schema-aware Denoising (2022.findings-naacl)
Copied to clipboard
| Challenge: | Using sketch-based slot filling, text-to-SQL models suffer from over-complexity . et al., e.al., and d.albert, dr., propose a novel method for text- to-Sql generation . |
| Approach: | They propose to train sequence-to-sequence model with Schema-aware Denoising . they propose a clause-sensitive execution guided (EG) decoding strategy . |
| Outcome: | The proposed method improves performance in schema linking and grammar correctness . it also establishes new state-of-the-art on the WikiSQL benchmark . |
Structure-Aware Zero-Shot Relational Learning for Knowledge Graphs without External Knowledge (2026.findings-acl)
Copied to clipboard
| Challenge: | Existing methods for Zero-shot Relational Learning depend on external knowledge, resulting in increased annotation costs and limited practical applicability. |
| Approach: | They propose a structure-aware paradigm that performs ZRL without external knowledge . it leverages intrinsic structural patterns in KGs to bridge semantic correlations for new relations with existing ones. |
| Outcome: | The proposed paradigm achieves 10.66% improvement in MRR while reducing annotation costs and enhancing practical applicability on three real-world benchmarks. |