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Datasets:
rpaut03l
/
trishieldrag-nq-mpnet-embeddings

Tasks:
Feature Extraction
ArXiv:
Tags:
rag
retrieval
embeddings
rag-security
faiss
License:
Dataset card Files
xet
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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
id: string
title: string
text: string
source: string
embeddings/nq_embeddings.meta.json: struct<sha256: string, bytes: int64>
  child 0, sha256: string
  child 1, bytes: int64
embeddings/hotpotqa_embeddings.npy: struct<sha256: string, bytes: int64>
  child 0, sha256: string
  child 1, bytes: int64
ragshield_2m.index: struct<sha256: string, bytes: int64>
  child 0, sha256: string
  child 1, bytes: int64
msmarco.index: struct<sha256: string, bytes: int64>
  child 0, sha256: string
  child 1, bytes: int64
embeddings/nq_embeddings.npy: struct<sha256: string, bytes: int64>
  child 0, sha256: string
  child 1, bytes: int64
embeddings/hotpotqa_embeddings.meta.json: struct<sha256: string, bytes: int64>
  child 0, sha256: string
  child 1, bytes: int64
hotpotqa.index: struct<sha256: string, bytes: int64>
  child 0, sha256: string
  child 1, bytes: int64
embeddings/msmarco_embeddings.npy: struct<sha256: string, bytes: int64>
  child 0, sha256: string
  child 1, bytes: int64
embeddings/msmarco_embeddings.meta.json: struct<sha256: string, bytes: int64>
  child 0, sha256: string
  child 1, bytes: int64
to
{'embeddings/nq_embeddings.npy': {'sha256': Value('string'), 'bytes': Value('int64')}, 'embeddings/hotpotqa_embeddings.npy': {'sha256': Value('string'), 'bytes': Value('int64')}, 'embeddings/msmarco_embeddings.npy': {'sha256': Value('string'), 'bytes': Value('int64')}, 'ragshield_2m.index': {'sha256': Value('string'), 'bytes': Value('int64')}, 'hotpotqa.index': {'sha256': Value('string'), 'bytes': Value('int64')}, 'msmarco.index': {'sha256': Value('string'), 'bytes': Value('int64')}, 'embeddings/nq_embeddings.meta.json': {'sha256': Value('string'), 'bytes': Value('int64')}, 'embeddings/hotpotqa_embeddings.meta.json': {'sha256': Value('string'), 'bytes': Value('int64')}, 'embeddings/msmarco_embeddings.meta.json': {'sha256': Value('string'), 'bytes': Value('int64')}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
                  for key, pa_table in 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/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              id: string
              title: string
              text: string
              source: string
              embeddings/nq_embeddings.meta.json: struct<sha256: string, bytes: int64>
                child 0, sha256: string
                child 1, bytes: int64
              embeddings/hotpotqa_embeddings.npy: struct<sha256: string, bytes: int64>
                child 0, sha256: string
                child 1, bytes: int64
              ragshield_2m.index: struct<sha256: string, bytes: int64>
                child 0, sha256: string
                child 1, bytes: int64
              msmarco.index: struct<sha256: string, bytes: int64>
                child 0, sha256: string
                child 1, bytes: int64
              embeddings/nq_embeddings.npy: struct<sha256: string, bytes: int64>
                child 0, sha256: string
                child 1, bytes: int64
              embeddings/hotpotqa_embeddings.meta.json: struct<sha256: string, bytes: int64>
                child 0, sha256: string
                child 1, bytes: int64
              hotpotqa.index: struct<sha256: string, bytes: int64>
                child 0, sha256: string
                child 1, bytes: int64
              embeddings/msmarco_embeddings.npy: struct<sha256: string, bytes: int64>
                child 0, sha256: string
                child 1, bytes: int64
              embeddings/msmarco_embeddings.meta.json: struct<sha256: string, bytes: int64>
                child 0, sha256: string
                child 1, bytes: int64
              to
              {'embeddings/nq_embeddings.npy': {'sha256': Value('string'), 'bytes': Value('int64')}, 'embeddings/hotpotqa_embeddings.npy': {'sha256': Value('string'), 'bytes': Value('int64')}, 'embeddings/msmarco_embeddings.npy': {'sha256': Value('string'), 'bytes': Value('int64')}, 'ragshield_2m.index': {'sha256': Value('string'), 'bytes': Value('int64')}, 'hotpotqa.index': {'sha256': Value('string'), 'bytes': Value('int64')}, 'msmarco.index': {'sha256': Value('string'), 'bytes': Value('int64')}, 'embeddings/nq_embeddings.meta.json': {'sha256': Value('string'), 'bytes': Value('int64')}, 'embeddings/hotpotqa_embeddings.meta.json': {'sha256': Value('string'), 'bytes': Value('int64')}, 'embeddings/msmarco_embeddings.meta.json': {'sha256': Value('string'), 'bytes': Value('int64')}}
              because column names don't match

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TriShieldRAG — BeIR NQ embeddings and FAISS index

Artifacts for TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation.

File Size Description
emb_*.npy (27) 7.7 GB Embeddings, 100k passages per chunk, corpus order
nq_ivf_nlist6550.index 7.8 GB FAISS IVF index, nlist=6550, inner product
  • Corpus: BeIR/nq corpus split, 2,681,468 passages
  • Model: sentence-transformers/all-mpnet-base-v2, 768-d, L2-normalised

Load the index 

import faiss
from huggingface_hub import hf_hub_download
p = hf_hub_download("rpaut03l/trishieldrag-nq-mpnet-embeddings",
                    "nq_ivf_nlist6550.index", repo_type="dataset")
index = faiss.read_index(p)
index.nprobe = 409

Paper: https://arxiv.org/abs/2607.23838 Code: https://github.com/SPriTLab-iitj/TriShieldRAG and/or https://github.com/rpaut03l/poisonedrag-ragshield-group6-iitj_TriShieldRAG
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Total file size:
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Paper for rpaut03l/trishieldrag-nq-mpnet-embeddings