# Massive Choice, Ample Tasks (MaChAmp): A Toolkit for Multi-task Learning in NLP

arXiv: https://arxiv.org/abs/2005.14672 · HTML: https://mlsanity.com/paper/2005.14672/

## Key facts

- Cited by 50 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 May 2020.

## Built on by (most cited first, 30 of 50)

- [From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding](https://mlsanity.com/paper/2105.07316/) (2021)
- [SkillSpan: Hard and Soft Skill Extraction from English Job Postings](https://mlsanity.com/paper/2204.12811/) (2022)
- [BigBIO: A Framework for Data-Centric Biomedical Natural Language Processing](https://mlsanity.com/paper/2206.15076/) (2022)
- [DaN+: Danish Nested Named Entities and Lexical Normalization](https://mlsanity.com/paper/2105.11301/) (2021)
- [On Language Models for Creoles](https://mlsanity.com/paper/2109.06074/) (2021)
- [What do You Mean by Relation Extraction? A Survey on Datasets and Study on Scientific Relation Classification](https://mlsanity.com/paper/2204.13516/) (2022)
- [SemEval-2023 Task 2: Fine-grained Multilingual Named Entity Recognition (MultiCoNER 2)](https://mlsanity.com/paper/2305.06586/) (2023)
- [ESCOXLM-R: Multilingual Taxonomy-driven Pre-training for the Job Market Domain](https://mlsanity.com/paper/2305.12092/) (2023)
- [Findings of the VarDial Evaluation Campaign 2023](https://mlsanity.com/paper/2305.20080/) (2023)
- [Kompetencer: Fine-grained Skill Classification in Danish Job Postings via Distant Supervision and Transfer Learning](https://mlsanity.com/paper/2205.01381/) (2022)
- [Skill Extraction from Job Postings using Weak Supervision](https://mlsanity.com/paper/2209.08071/) (2022)
- [De-identification of Privacy-related Entities in Job Postings](https://mlsanity.com/paper/2105.11223/) (2021)
- [Experimental Standards for Deep Learning in Natural Language Processing Research](https://mlsanity.com/paper/2204.06251/) (2022)
- [Multilingual Auxiliary Tasks Training: Bridging the Gap between Languages for Zero-Shot Transfer of Hate Speech Detection Models](https://mlsanity.com/paper/2210.13029/) (2022)
- [Genre as Weak Supervision for Cross-lingual Dependency Parsing](https://mlsanity.com/paper/2109.04733/) (2021)
- [Probing for Labeled Dependency Trees](https://mlsanity.com/paper/2203.12971/) (2022)
- [4 and 7-bit Labeling for Projective and Non-Projective Dependency Trees](https://mlsanity.com/paper/2310.14319/) (2023)
- [Sebastian, Basti, Wastl?! Recognizing Named Entities in Bavarian Dialectal Data](https://mlsanity.com/paper/2403.12749/) (2024)
- [Sequence-to-Sequence Lexical Normalization with Multilingual Transformers](https://mlsanity.com/paper/2110.02869/) (2021)
- ['UFAL at MultiLexNorm 2021: Improving Multilingual Lexical Normalization by Fine-tuning ByT5](https://mlsanity.com/paper/2110.15248/) (2021)
- [Ancestor-to-Creole Transfer is Not a Walk in the Park](https://mlsanity.com/paper/2206.04371/) (2022)
- [MaiBaam: A Multi-Dialectal Bavarian Universal Dependency Treebank](https://mlsanity.com/paper/2403.10293/) (2024)
- [Fine-grained Fallacy Detection with Human Label Variation](https://mlsanity.com/paper/2502.13853/) (2025)
- [Zero-Shot Dependency Parsing with Worst-Case Aware Automated Curriculum Learning](https://mlsanity.com/paper/2203.08555/) (2022)
- [Exploring the Robustness of Task-oriented Dialogue Systems for Colloquial German Varieties](https://mlsanity.com/paper/2402.02078/) (2024)
- [data2lang2vec: Data Driven Typological Features Completion](https://mlsanity.com/paper/2409.17373/) (2024)
- [Data-driven Parsing Evaluation for Child-Parent Interactions](https://mlsanity.com/paper/2209.13778/) (2022)
- [Beyond Dataset Creation: Critical View of Annotation Variation and Bias Probing of a Dataset for Online Radical Content Detection](https://mlsanity.com/paper/2412.11745/) (2024)
- [Improving Dialectal Slot and Intent Detection with Auxiliary Tasks: A Multi-Dialectal Bavarian Case Study](https://mlsanity.com/paper/2501.03863/) (2025)
- [IYKYK: Using language models to decode extremist cryptolects](https://mlsanity.com/paper/2506.05635/) (2025)

## Abstract (arXiv)

Transfer learning, particularly approaches that combine multi-task learning with pre-trained contextualized embeddings and fine-tuning, have advanced the field of Natural Language Processing tremendously in recent years. In this paper we present MaChAmp, a toolkit for easy fine-tuning of contextualized embeddings in multi-task settings. The benefits of MaChAmp are its flexible configuration options, and the support of a variety of natural language processing tasks in a uniform toolkit, from text classification and sequence labeling to dependency parsing, masked language modeling, and text generation.