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Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
gold_set: string
endpoint: string
hybrid: bool
top_k: int64
total_queries: int64
recall: struct<1: double, 5: double, 10: double, 20: double>
mrr: struct<1: double, 5: double, 10: double, 20: double>
latency_s: struct<avg: double, p50: double, p95: double>
vs
paper_id: string
citekey: string
kind: string
title: string
authors: list<item: string>
year: string
doi: string
isbn: string
issn: string
container_title: string
publisher: string
volume: string
issue: string
pages: string
edition: string
identifiers: null
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/python3.12/site-packages/datasets/iterable_dataset.py", line 3496, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2257, in _head
                  return next(iter(self.iter(batch_size=n)))
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2461, in iter
                  for key, example in iterator:
                                      ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1952, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1974, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
                  yield new_key, pa.Table.from_batches(chunks_buffer)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "pyarrow/table.pxi", line 5039, in pyarrow.lib.Table.from_batches
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              gold_set: string
              endpoint: string
              hybrid: bool
              top_k: int64
              total_queries: int64
              recall: struct<1: double, 5: double, 10: double, 20: double>
              mrr: struct<1: double, 5: double, 10: double, 20: double>
              latency_s: struct<avg: double, p50: double, p95: double>
              vs
              paper_id: string
              citekey: string
              kind: string
              title: string
              authors: list<item: string>
              year: string
              doi: string
              isbn: string
              issn: string
              container_title: string
              publisher: string
              volume: string
              issue: string
              pages: string
              edition: string
              identifiers: null

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LAYRA: Large Academic Visual RAG Gold Set (Kanna)

This dataset contains the evaluation artifacts for LAYRA (Large Academic Visual RAG Agent), a specialized Visual RAG system for academic literature focused on the ethnopharmacology of Sceletium tortuosum (Kanna).

Project Overview

LAYRA utilizes ColQwen2.5 (Late-Interaction VLM) to retrieve full PDF pages by embedding visual layouts, charts, and scientific figures directly, bypassing the information loss inherent in traditional OCR-based text chunking.

Dataset Contents

  • gold_set.csv: 30 complex academic queries with ground-truth document IDs and page references.
  • paper_catalog.jsonl: Metadata for the 129 research papers comprising the corpus.
  • metrics_baseline.json: Performance metrics (Recall, MRR, Latency) as of Dec 31, 2025.

Usage

This gold set is designed to benchmark retrieval accuracy for Visual RAG systems.

Citation

If you use this dataset in your research, please cite the LAYRA thesis project.

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