XNLIvar
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The JWT signature verification failed. Check the signing key and the algorithm.
Error code: JWTInvalidSignature
Exception: InvalidSignatureError
Message: Signature verification failed
Traceback: Traceback (most recent call last):
File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
decoded = jwt.decode(
jwt=token,
...<2 lines>...
options=options,
)
File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
decoded = self.decode_complete(
jwt,
...<8 lines>...
leeway=leeway,
)
File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
decoded = self._jws.decode_complete(
jwt,
...<3 lines>...
detached_payload=detached_payload,
)
File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
self._verify_signature(
~~~~~~~~~~~~~~~~~~~~~~^
signing_input,
^^^^^^^^^^^^^^
...<4 lines>...
options=merged_options,
^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
raise InvalidSignatureError("Signature verification failed")
jwt.exceptions.InvalidSignatureError: Signature verification failedNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
XNLIvar: Basque and Spanish variation-inclusive NLI
This repository contains the data and code used in the paper Lost in Variation? Evaluating NLI Performance in Basque and Spanish Geographical Variants
This paper evaluates the capacity of current language technologies to understand Basque and Spanish language varieties. We use Natural Language Inferenc (NLI) as a pivot task and introduce a novel, manually-curated parallel dataset in Basque and Spanish and their corresponding variants. Empirical analysis of comprehensive crosslingual and in-context learning experiments with, respectively, encoder-only and decoder-based Large Language Models (LLMs), reveals a performance drop when processing linguistic variations, with more pronounced effects observed in Basque. Error analysis indicates that lexical overlap plays no role, suggesting that linguistic variation represents the primary reason for the lower results. All data and code in this repository are public under Attribution-NonCommercial 4.0 International license.
Dataset decription
XNLIeu (the origin dataset for XNLIvar) has been derived from XNLI and it is distributed under its same license.
XNLIvar, a novel, manually-curated, variation inclusive NLI datasets in Basque and Spanish for NLI evaluation. The data is structured in the following folders:
- eu: It provides the original XNLI test data, as well as the native and variation inclusive datasets.
- es: It provides de original XNLI test data, as well as the Basque native data translated into Spanish and the variation inclusive data.
- Translations: It provides the automatic translations of the native and variation inclusive datasets into English.
- ablation-eu: The datasets used in the ablation experiments for Basque.
- ablation-es: The datasets used in the ablation experiments for Spanish.
Useful links
Citation
The paper that explains the dataset and experiments can be cited as follows:
@inproceedings{bengoetxea-et-al-2025,,
title = "Lost in Variation? Evaluating NLI Performance in Basque and Spanish Geographical Variants",
author = "Bengoetxea, Jaione and
Gonzalez-Dios, Itziar and
Agerri, Rodrigo",
year = "2025",
url = "https://arxiv.org/abs/2506.15239"
}
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