Abstract: Recent work has shown that fine-tuning LLMs with synthetic data improves text-to-SQL performance. However, synthetic data for in-context learning (ICL) remains underexplored. Existing data ...

It’s a familiar moment in math class—students are asked to solve a problem, and some jump in confidently while others freeze, unsure where to begin. When students don’t yet have a clear mental model ...

Empower employees like Ritz-Carlton to resolve issues instantly, enhancing service quality and boosting customer loyalty through empowered decision-making. Create emotional connections, as Starbucks ...

Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...

Google Research on November 7, 2025, introduced a new machine learning paradigm called Nested Learning, designed to solve catastrophic forgetting in AI models. This long-standing problem causes models ...

We propose an RL-based method to refine queries for DeepSeek code generation, learning from the results of generated code. We use a dual-model design: a learnable refiner (Qwen+LoRA) and a fixed ...

Have you ever found yourself lost in a sea of parentheses, trying to decipher a deeply nested SQL query? We've all been there. Complex data transformations often lead to code that's difficult to read, ...

Abstract: Recent research in Text-to-SQL translation has primarily adopted in-context learning methods leveraging large language models (LLMs), achieving significant progress. However, these methods ...

Update 7/31/25 4:10pm PT: Hours after this article was published, OpenAI said it removed the feature from ChatGPT that allowed users to make their public conversations discoverable by search engines.