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Found 11 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.
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.
FLAME: A small language model for spreadsheet formulas
We evaluate FLAME on formula repair, formula completion, and similarity-based formula retrieval.
Repairing Bugs in Python Assignments Using Large Language Models
We propose to use a large language model trained on code, such as Codex, to build an APR system -- MMAPR -- for introductory Python programming assignments.
Repair Is Nearly Generation: Multilingual Program Repair with LLMs
We show that RING can outperform language-specific repair engines for three of these languages.
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.
Human-Machine Collaboration for Democratizing Data Science
Everybody wants to analyse their data, but only few posses the data science expertise to to this.
