Work

CLIMB – Curriculum Learning for Infant-inspired Model Building

Year: 2023

Type: conference-paper

Abstract: Richard Diehl Martinez, Zébulon Goriely, Hope McGovern, Christopher Davis, Andrew Caines, Paula Buttery, Lisa Beinborn. Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning. 2023.

Source: BabyLM Challenge

DOI: 10.18653/v1/2023.conll-babylm.10

Authors: Richard Diehl Martinez, Hope McGovern, Zebulon Goriely, Christopher Davis, Andrew Caines, Paula Buttery, Lisa Beinborn

Institutions: University of Cambridge, Vrije Universiteit Amsterdam

Language: English

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: hybrid

Funders: Bill and Melinda Gates Foundation, Dell EMC, University of Cambridge, Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Cambridge Trust, Gates Cambridge Trust, Engineering and Physical Sciences Research Council, Science and Technology Facilities Council

Awards: G1690597291, G2264885075, Interpretability of Transfer in Multilingual Models, Cambridge University Development Office in the United States Inc (CUDOUS) - to endow a global scholarship program at the post-baccalaureate level for academically gifted students, G581313191, Cambridge Service for Data Driven Discovery (CSD3) - A National Data Intensive Science Cloud for Converged Simulation, AI & Analytics, G7920038418

OpenAlex ID: W4389518616

FWCI: 0.292

Cites: 41

Cited by: 2

Related to: 10