activity
20222026
most citedDr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness

10 citations · 19 across the 5 of their papers we have counts for

collaborators

7 papers

cs.AI2026

Instruct, Not Answer: Using Instruction Privileges in On-Policy Context Distillation

Hantao Yu, Sandy Han, Xiaoxue Han +6

On-Policy Context Distillation (OPCD) has recently emerged as a powerful technique for transferring context to student models and for self-improvement. In OPCD, the teacher is cond…

cs.LG2026

Beyond Solver Verdicts: Generative Reward Models for Autoformalization

Vikash Singh, Debargha Ganguly, Aman Goel +5

Neurosymbolic systems rely on mathematical solvers to guarantee reasoning correctness, yet solvers are fundamentally blind to whether a formal translation maintains strict referenc…

cs.CL2026

Stratified Consistency Distillation for Natural Language Formalization

Zhichao Hou, Ferhat Erata, Joe Lilien +1

Neurosymbolic reasoning has shown promising success in addressing complex reasoning tasks by combining large language models (LLMs) and symbolic solvers. While this approach shows…

cs.CL2025

A Neurosymbolic Approach to Natural Language Formalization and Verification

Chenyang An, Sam Bayless, Stefano Buliani +27

Large Language Models perform well at natural language interpretation and reasoning, but their lack of formal correctness guarantees limits their adoption in regulated industries l…

cs.CL2023★ 9 cited

UNITE: A Unified Benchmark for Text-to-SQL Evaluation

Wuwei Lan, Zhiguo Wang, Anuj Chauhan +15

A practical text-to-SQL system should generalize well on a wide variety of natural language questions, unseen database schemas, and novel SQL query structures. To comprehensively e…

cs.CL2023★ 10 cited

Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness

Shuaichen Chang, Jun Wang, Mingwen Dong +13

Neural text-to-SQL models have achieved remarkable performance in translating natural language questions into SQL queries. However, recent studies reveal that text-to-SQL models ar…

cs.CL2022

Importance of Synthesizing High-quality Data for Text-to-SQL Parsing

Yiyun Zhao, Jiarong Jiang, Yiqun Hu +14

Recently, there has been increasing interest in synthesizing data to improve downstream text-to-SQL tasks. In this paper, we first examined the existing synthesized datasets and di…