4 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.AI2026
DI-Bench: Systematically Generating In-Domain Data Intelligence Benchmarks for Enterprise Agents
Jiangyun Zhang, Kristen Surrao, Torpong Nitayanont +10
Evaluating enterprise agents on domain-specific benchmarks is critical, yet public benchmarks rarely evaluate whether agents can integrate business knowledge with analytical comput…
cs.CL2025
Self-supervised Analogical Learning using Language Models
Ben Zhou, Sarthak Jain, Yi Zhang +4
Large language models have been shown to suffer from reasoning inconsistency issues. That is, they fail more in situations unfamiliar to the training data, even though exact or ver…
cs.CL2024★ 4 cited
BEAVER: An Enterprise Benchmark for Text-to-SQL
Peter Baile Chen, Devin Yang, Weiyue Li +6
Existing text-to-SQL benchmarks have largely been constructed from public databases with well-structured schemas and simplistic question-SQL pairs. While large language models (LLM…