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Found 9 papers, 0 papers with code
Assessing GPT4-V on Structured Reasoning Tasks
Multi-modality promises to unlock further uses for large language models.
CodeFusion: A Pre-trained Diffusion Model for Code Generation
Imagine a developer who can only change their last line of code, how often would they have to start writing a function from scratch before it is correct?
FormaT5: Abstention and Examples for Conditional Table Formatting with Natural Language
Writing such rules is often challenging for users as it requires them to understand and implement the underlying logic.
TST$^\mathrm{R}$: Target Similarity Tuning Meets the Real World
Target similarity tuning (TST) is a method of selecting relevant examples in natural language (NL) to code generation through large language models (LLMs) to improve performance.
InstructExcel: A Benchmark for Natural Language Instruction in Excel
With the evolution of Large Language Models (LLMs) we can solve increasingly more complex NLP tasks across various domains, including spreadsheets.
DataVinci: Learning Syntactic and Semantic String Repairs
DataVinci learns regular-expression-based patterns that cover a majority of values in a column and reports values that do not satisfy such patterns as data errors.
Demonstration of CORNET: A System For Learning Spreadsheet Formatting Rules By Example
After the user provides one or two formatted cells as examples, CORNET generates formatting rule suggestions for the user to apply to the spreadsheet.
From Words to Code: Harnessing Data for Program Synthesis from Natural Language
Existing approaches have utilized data context in a limited way by simply adding relevant information from the input data into the prompts sent to the LLM.
CORNET: Learning Table Formatting Rules By Example
Since we are the first to introduce conditional formatting, we compare CORNET to a wide range of symbolic and neural baselines adapted from related domains.
