103 citations · 103 across the 2 of their papers we have counts for
5 papers · 1 filter
Agent Bain vs. Agent McKinsey: A New Text-to-SQL Benchmark for the Business Domain
Yue Li, Ran Tao, Derek Hommel +4
Text-to-SQL benchmarks have traditionally only tested simple data access as a translation task of natural language to SQL queries. But in reality, users tend to ask diverse questio…
Cheaper, Better, Faster, Stronger: Robust Text-to-SQL without Chain-of-Thought or Fine-Tuning
Yusuf Denizay Dönder, Derek Hommel, Andrea W Wen-Yi +2
LLMs are effective at code generation tasks like text-to-SQL, but is it worth the cost? Many state-of-the-art approaches use non-task-specific LLM techniques including Chain-of-Tho…
Do Chinese models speak Chinese languages?
Andrea W Wen-Yi, Unso Eun Seo Jo, David Mimno
The release of top-performing open-weight LLMs has cemented China's role as a leading force in AI development. Do these models support languages spoken in China? Or do they support…
How Chinese are Chinese Language Models? The Puzzling Lack of Language Policy in China's LLMs
Andrea W Wen-Yi, Unso Eun Seo Jo, Lu Jia Lin +1
Contemporary language models are increasingly multilingual, but Chinese LLM developers must navigate complex political and business considerations of language diversity. Language p…
Efficient Few-Shot Learning Without Prompts
Lewis Tunstall, Nils Reimers, Unso Eun Seo Jo +4
Recent few-shot methods, such as parameter-efficient fine-tuning (PEFT) and pattern exploiting training (PET), have achieved impressive results in label-scarce settings. However, t…