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The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'keyword_kp20k' of the dataset.
Error code: FeaturesError
Exception: ParserError
Message: Error tokenizing data. C error: Expected 15 fields in line 5, saw 25
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4379, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2661, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2839, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/csv/csv.py", line 198, in _generate_tables
for batch_idx, df in enumerate(csv_file_reader):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1843, in __next__
return self.get_chunk()
~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1985, in get_chunk
return self.read(nrows=size)
~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1923, in read
) = self._engine.read( # type: ignore[attr-defined]
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
nrows
^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 234, in read
chunks = self._reader.read_low_memory(nrows)
File "pandas/_libs/parsers.pyx", line 850, in pandas._libs.parsers.TextReader.read_low_memory
File "pandas/_libs/parsers.pyx", line 905, in pandas._libs.parsers.TextReader._read_rows
File "pandas/_libs/parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
File "pandas/_libs/parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
File "pandas/_libs/parsers.pyx", line 2061, in pandas._libs.parsers.raise_parser_error
pandas.errors.ParserError: Error tokenizing data. C error: Expected 15 fields in line 5, saw 25Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
SLM-in-SciPaper
This repository stores the data and model assets used by the SLM-in-SciPaper project.
Contents
data/keyword_keyphrase: processed Stage 1 keyphrase extraction data.data/structure: processed Stage 2 structural evidence modeling data.data/paper_corpus/full_library_txt: 178 plain-text scientific papers used as the local demonstration corpus.data/paper_corpus/manifest.csv: metadata and file paths for the 178-paper text corpus.data/training_datasets_manifest.csv: a compact index of the processed training/evaluation files.resources/lexicon: supplementary section BoW, TF-IDF, frequency, and evidence cue resources used by the inference pipeline.models: model assets/checkpoints previously uploaded for this project.
Training Data Actually Used
The final local pipeline used six processed training datasets:
| Stage | Dataset | Role in the project |
|---|---|---|
| Stage 1 | KP20k | keyword extractor warm-up |
| Stage 1 | LDKP10K | long-document keyword fine-tuning |
| Stage 1 | SemEval2010 | final keyword fine-tuning/evaluation |
| Stage 2 | PubMed RCT | hard role supervision |
| Stage 2 | QASPER | evidence supervision and partial role constraint |
| Stage 2 | ACLSum | importance supervision and facet role supervision |
SciTLDR weak data existed in the local workspace but was not used by the final reported training pipeline, so it is not included as a training dataset here.
Data Format
The processed training data is stored as JSONL files. Each line is one document-level record in the schema consumed by the project code. Summary files are kept beside each dataset directory when available.
The paper corpus is stored as individual .txt files. Use data/paper_corpus/manifest.csv to map each paper id to its text file.
Notes
This repository contains processed versions of public research datasets and a local paper-text corpus for course/research use. Original upstream dataset licenses and terms should be checked before redistribution or commercial use.
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