# Simplifying Semantic Annotations of SMCalFlow

arXiv: https://arxiv.org/abs/2206.13425 · HTML: https://mlsanity.com/paper/2206.13425/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 2 references that are in the map.
- First posted on arXiv 27 Jun 2022.

## Builds on (most cited first, 2 of 2)

- [MultiWOZ -- A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling](https://mlsanity.com/paper/1810.00278/) (2018)
- [Task-Oriented Dialogue as Dataflow Synthesis](https://mlsanity.com/paper/2009.11423/) (2020)

## Built on by (most cited first, 7 of 7)

- [Diverse Demonstrations Improve In-context Compositional Generalization](https://mlsanity.com/paper/2212.06800/) (2022)
- [Coverage-based Example Selection for In-Context Learning](https://mlsanity.com/paper/2305.14907/) (2023)
- [GistScore: Learning Better Representations for In-Context Example Selection with Gist Bottlenecks](https://mlsanity.com/paper/2311.09606/) (2023)
- [MultiWOZ-DF -- A Dataflow implementation of the MultiWOZ dataset](https://mlsanity.com/paper/2211.02303/) (2022)
- [Few-Shot Adaptation for Parsing Contextual Utterances with LLMs](https://mlsanity.com/paper/2309.10168/) (2023)
- [DFEE: Interactive DataFlow Execution and Evaluation Kit](https://mlsanity.com/paper/2212.08099/) (2022)
- [Dataflow Dialogue Generation](https://mlsanity.com/paper/2308.02323/) (2023)

## Abstract (arXiv)

SMCalFlow is a large corpus of semantically detailed annotations of task-oriented natural dialogues. The annotations use a dataflow approach, in which the annotations are programs which represent user requests. Despite the availability, size and richness of this annotated corpus, it has seen only very limited use in dialogue systems research work, at least in part due to the difficulty in understanding and using the annotations. To address these difficulties, this paper suggests a simplification of the SMCalFlow annotations, as well as releases code needed to inspect the execution of the annotated dataflow programs, which should allow researchers of dialogue systems an easy entry point to experiment with various dataflow based implementations and annotations.