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 failed

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ReSyn Dataset

This repository contains the official datasets for the paper ReSyn: A Generalized Recursive Regular Expression Synthesis Framework (accepted at IJCAI 2026).

Paper: ReSyn: A Generalized Recursive Regular Expression Synthesis Framework
GitHub: mrseongminkim/ReSyn

Dataset Description

ReSyn is a dataset designed for Programming-By-Example (PBE) systems focused on regular expression synthesis. It aims to capture the high structural complexity of real-world regexes, such as deep nesting and frequent use of union operations, which are often missing from simplified benchmarks.

The framework uses a divide-and-conquer approach to decompose complex synthesis problems into manageable sub-problems by adaptively predicting whether to split examples sequentially (Concatenation) or group them by structural similarity (Union).

Splits

The dataset consists of the following splits:

train: 1,410,280 examples used for training the framework's core components.
valid: 32,236 examples for validation.
benchmark: 2,728 real-world regex synthesis problems for evaluating performance on structurally complex patterns.

Each example includes a target regex, as well as sets of positive_strings and negative_strings.

Citation

If you use this dataset in your research, please cite:

@inproceedings{kim2026resyn,
  title={ReSyn: A Generalized Recursive Regular Expression Synthesis Framework},
  author={Kim, Seongmin and Cheon, Hyunjoon and Kim, Su-Hyeon and Han, Yo-Sub and Ko, Sang-Ki},
  booktitle={Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-26)},
  year={2026}
}

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Models trained or fine-tuned on mrseongminkim/ReSyn

Paper for mrseongminkim/ReSyn

ReSyn: A Generalized Recursive Regular Expression Synthesis Framework

Paper • 2603.24624 • Published Jun 13 • 2