# CAIT: A Syntactic Parsing Toolkit for Child-Adult InTeractions

arXiv: https://arxiv.org/abs/2605.19718 · HTML: https://mlsanity.com/paper/2605.19718/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 74 references that are in the map.
- First posted on arXiv 19 May 2026.

## Builds on (most cited first, 14 of 14)

- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [Enriching Word Vectors with Subword Information](https://mlsanity.com/paper/1607.04606/) (2016)
- [Stanza: A Python Natural Language Processing Toolkit for Many Human Languages](https://mlsanity.com/paper/2003.07082/) (2020)
- [Deep Biaffine Attention for Neural Dependency Parsing](https://mlsanity.com/paper/1611.01734/) (2016)
- [What Artificial Neural Networks Can Tell Us About Human Language Acquisition](https://mlsanity.com/paper/2208.07998/) (2022)
- [Massive Choice, Ample Tasks (MaChAmp): A Toolkit for Multi-task Learning in NLP](https://mlsanity.com/paper/2005.14672/) (2020)
- [Do Construction Distributions Shape Formal Language Learning In German BabyLMs?](https://mlsanity.com/paper/2503.11593/) (2025)
- [UCxn: Typologically Informed Annotation of Constructions Atop Universal Dependencies](https://mlsanity.com/paper/2403.17748/) (2024)
- [Domain Regeneration: How well do LLMs match syntactic properties of text domains?](https://mlsanity.com/paper/2505.07784/) (2025)
- [Data-driven Parsing Evaluation for Child-Parent Interactions](https://mlsanity.com/paper/2209.13778/) (2022)
- [UD-English-CHILDES: A Collected Resource of Gold and Silver Universal Dependencies Trees for Child Language Interactions](https://mlsanity.com/paper/2504.20304/) (2025)
- [A Tidy Data Model for Natural Language Processing using cleanNLP](https://mlsanity.com/paper/1703.09570/) (2017)
- [Leveraging Lora Fine-Tuning and Knowledge Bases for Construction Identification](https://mlsanity.com/paper/2601.13105/) (2026)

## Built on by (most cited first, 1 of 1)

- [Disentangling Statistical Preemption from Entrenchment in Language Models' Avoidance of Overgeneralization](https://mlsanity.com/paper/2609.01794/) (2026)

## Abstract (arXiv)

CHILDES is a paramount resource for language acquisition studies -- yet computational tools for analyzing its syntactic structure remain limited. Leveraging the recent release of the UD-English-CHILDES treebank with gold-standard Universal Dependencies (UD) annotations, we train a state-of-the-art dependency parser specifically tailored to CHILDES. The parser more accurately captures syntactic patterns in child-adult interactions, outperforming widely used off-the-shelf English parsers, including SpaCy and Stanza. Alongside the parser, we also release a Part-of-Speech tagger and an utterance-level construction tagger, which together form the open-source Syntactic Parsing Toolkit for Child-Adult InTeractions (CAIT). Through a detailed error analysis and a case study tracking the distribution of syntactic constructions across developmental time in CHILDES, we demonstrate the practical utility of the toolkit for large-scale, reproducible research on language acquisition.