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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Video Redistribution Notice

Since we do not own redistribution rights for the original broadcasts, we do not redistribute raw videos. We instead release original video URLs, timestamps, commentary annotations, category labels, punch-event labels, evaluation files, prompts, and reconstruction scripts for non-commercial academic research.

The official source URL table is provided at metadata/source_urls.csv.

Available reconstruction metadata:

metadata/source_urls.csv: official source URLs and match metadata.
metadata/timestamp.csv: original-video round boundary timestamps used for trimming.
metadata/timestamp_processed.csv: round boundary timestamps after processing/free-frame removal.

BoxComm-Dataset

BoxComm-Dataset is the official data release for BoxComm, a benchmark for category-aware boxing commentary generation and narration-rhythm evaluation.

Resources

Project Page: https://gouba2333.github.io/BoxComm
Paper: http://arxiv.org/abs/2604.04419
Code: https://github.com/gouba2333/BoxComm
Benchmark: https://huggingface.co/datasets/gouba2333/BoxComm

Overview

This dataset release is intended for training, analysis, and reproducible preprocessing. It contains the complete processed videos together with the released annotations and benchmark metadata.

Recommended structure:

BoxComm-Dataset/
├── train/
│   ├── videos/
│   ├── events/
│   └── asr/
├── eval/
│   ├── videos/
│   ├── events/
│   └── asr/
└── metadata/

The split convention is:

train: video id < 478
eval: video id >= 478

Each event directory should contain:

one skeleton .pkl file
one video_event_inference_3.json file

Each ASR JSON file should contain classified_segments.

What is included

processed match videos
event annotations
skeleton data
ASR with sentence segmentation
3-way commentary labels
split metadata

Intended uses

supervised fine-tuning for commentary generation
category-aware commentary evaluation
narration-rhythm analysis
multimodal sports video understanding research

Data preparation in the code repository

The official code repository provides:

scripts/prep_qwen3vl_sft_data.py
scripts/train_qwen3vl.py
scripts/infer_qwen3vl.py
scripts/eval_metrics.py
scripts/eval_streaming_cls_metrics.py

Repository: https://github.com/gouba2333/BoxComm

Licensing

The public release includes processed videos, ASR annotations, event JSON files, skeleton PKL files, and benchmark metadata for research use.

Citation

@article{wang2026boxcomm,
  title={BoxComm: Benchmarking Category-Aware Commentary Generation and Narration Rhythm in Boxing},
  author={Wang, Kaiwen and Zheng, Kaili and Deng, Rongrong and Shi, Yiming and Guo, Chenyi and Wu, Ji},
  journal={arXiv preprint arXiv:2604.04419},
  year={2026}
}

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Paper for gouba2333/BoxComm-Dataset

BoxComm: Benchmarking Category-Aware Commentary Generation and Narration Rhythm in Boxing

Paper • 2604.04419 • Published Apr 6