File size: 2,499 Bytes
fb6d85a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 | cff-version: 1.2.0
message: "If you use this work, please cite it as below."
title: "MASSIVE-Agents: A Benchmark for Multilingual Function-Calling in 52 Languages"
type: conference-paper
authors:
- family-names: "Kulkarni"
given-names: "Mayank"
- family-names: "Mazzia"
given-names: "Vittorio"
- family-names: "Gaspers"
given-names: "Judith"
- family-names: "Hench"
given-names: "Chris"
- family-names: "FitzGerald"
given-names: "Jack"
year: 2025
month: 11
conference:
name: "Findings of the Association for Computational Linguistics: EMNLP 2025"
location: "Suzhou, China"
publisher:
name: "Association for Computational Linguistics"
pages: "20193-20215"
doi: "10.18653/v1/2025.findings-emnlp.1099"
isbn: "979-8-89176-335-7"
url: "https://aclanthology.org/2025.findings-emnlp.1099/"
abstract: >
We present MASSIVE-Agents, a new benchmark for assessing multilingual
function calling across 52 languages. We created MASSIVE-Agents by
cleaning the original MASSIVE dataset and then reformatting it for
evaluation within the Berkeley Function-Calling Leaderboard (BFCL)
framework. The full benchmark comprises 47,020 samples with an average
of 904 samples per language, covering 55 different functions and 286
arguments. We benchmarked 21 models using Amazon Bedrock and present
the results along with associated analyses. MASSIVE-Agents is
challenging, with the top model Nova Premier achieving an average
Abstract Syntax Tree (AST) Accuracy of 34.05% across all languages,
with performance varying significantly from 57.37% for English to as
low as 6.81% for Amharic. Some models, particularly smaller ones,
yielded a score of zero for the more difficult languages. Additionally,
we provide results from ablations using a custom 1-shot prompt,
ablations with prompts translated into different languages, and
comparisons based on model latency.
preferred-citation:
type: paper-conference
authors:
- family-names: "Kulkarni"
given-names: "Mayank"
- family-names: "Mazzia"
given-names: "Vittorio"
- family-names: "Gaspers"
given-names: "Judith"
- family-names: "Hench"
given-names: "Chris"
- family-names: "FitzGerald"
given-names: "Jack"
title: "MASSIVE-Agents: A Benchmark for Multilingual Function-Calling in 52 Languages"
year: 2025
conference:
name: "Findings of the Association for Computational Linguistics: EMNLP 2025"
doi: "10.18653/v1/2025.findings-emnlp.1099" |