SYNTOLOGY HomeExplorerAtlasCodeMethodologyAboutDevelopersFeedPricing
Paper · 2006.07264 · 2020

Low-resource Languages: A Review of Past Work and Future Challenges

arXiv · PDF · Open in the Atlas

Code that ran

We lifted 12 functions out of this paper's own repositories and ran 11 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.

RepositoryRoleRan
danielinux7/Multilingual-Parallel-Corpus pwc_unofficial 11 of 12
FunctionStatusWhere it lives
change_hypen Ran danielinux7/Multilingual-Parallel-Corpus/src/utils/ab/split_parallel.py
code served (permissive licence) · get_code("b270383cc170e9cd")
clean Ran danielinux7/Multilingual-Parallel-Corpus/src/utils/ab/preprocess.py
code served (permissive licence) · get_code("8cd26caa6b202383")
correct_sentences Ran danielinux7/Multilingual-Parallel-Corpus/src/utils/ab/split_parallel.py
code served (permissive licence) · get_code("5db82633622a30c9")
ends_with_acronym Ran danielinux7/Multilingual-Parallel-Corpus/src/utils/ab/split_parallel.py
code served (permissive licence) · get_code("72f2babdd08170eb")
fill_list Ran danielinux7/Multilingual-Parallel-Corpus/src/utils/ab/join_corpus.py
code served (permissive licence) · get_code("e861f4eba3aacc9f")
filter_out Ran danielinux7/Multilingual-Parallel-Corpus/src/utils/ab/join_corpus.py
code served (permissive licence) · get_code("e1d1bcc40131fd5c")
open_list Ran danielinux7/Multilingual-Parallel-Corpus/src/utils/ab/preprocess.py
code served (permissive licence) · get_code("c1bf663df3842199")
remove_duplicate Ran danielinux7/Multilingual-Parallel-Corpus/src/utils/ab/preprocess.py
code served (permissive licence) · get_code("77b2a0adda7adb5b")
replace_strings Ran danielinux7/Multilingual-Parallel-Corpus/src/utils/ab/join_corpus.py
code served (permissive licence) · get_code("bd190fb17edaad1c")
strip_accents Ran danielinux7/Multilingual-Parallel-Corpus/src/utils/ab/parse_dictionary.py
code served (permissive licence) · get_code("048d5b46b5abc501")
strip_clips Ran danielinux7/Multilingual-Parallel-Corpus/src/utils/ab/parse_dictionary.py
code served (permissive licence) · get_code("70127593241e6599")
get_following_text Not yet run danielinux7/Multilingual-Parallel-Corpus/src/utils/ab/parse_dictionary.py
code served (permissive licence) · get_code("239db4e0abc718d8")

Repositories linked to this paper

Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.

Abstract

A current problem in NLP is massaging and processing low-resource languages which lack useful training attributes such as supervised data, number of native speakers or experts, etc. This review paper concisely summarizes previous groundbreaking achievements made towards resolving this problem, and analyzes potential improvements in the context of the overall future research direction.

For agents

The same record, over MCP at https://syntology.ai/mcp:

get_harvested_code_for_paper("2006.07264")
get_code_for_paper("2006.07264")
have("2006.07264")

Connect an agent — have() is free.