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Datasets:
lightonai
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SlideOn-sparse-vectors

Tasks:
Text Retrieval
Modalities:
Text
Formats:
parquet
Size:
10M - 100M
Tags:
sparse-retrieval
learned-sparse-retrieval
anserini
beir
msmarco
Libraries:
Datasets
Dask
Polars
License:
🇪🇺 Region: EU
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metadata 
license: apache-2.0
task_categories:
  - text-retrieval
tags:
  - sparse-retrieval
  - learned-sparse-retrieval
  - anserini
  - beir
  - msmarco
size_categories:
  - 10M<n<100M
configs:
  - config_name: beir-v1.0.0-arguana
    data_files:
      - split: corpus
        path: beir-v1.0.0-arguana/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-arguana/queries/test/*.parquet
  - config_name: beir-v1.0.0-bioasq
    data_files:
      - split: corpus
        path: beir-v1.0.0-bioasq/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-bioasq/queries/test/*.parquet
  - config_name: beir-v1.0.0-climate-fever
    data_files:
      - split: corpus
        path: beir-v1.0.0-climate-fever/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-climate-fever/queries/test/*.parquet
  - config_name: beir-v1.0.0-cqadupstack-android
    data_files:
      - split: corpus
        path: beir-v1.0.0-cqadupstack-android/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-cqadupstack-android/queries/test/*.parquet
  - config_name: beir-v1.0.0-cqadupstack-english
    data_files:
      - split: corpus
        path: beir-v1.0.0-cqadupstack-english/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-cqadupstack-english/queries/test/*.parquet
  - config_name: beir-v1.0.0-cqadupstack-gaming
    data_files:
      - split: corpus
        path: beir-v1.0.0-cqadupstack-gaming/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-cqadupstack-gaming/queries/test/*.parquet
  - config_name: beir-v1.0.0-cqadupstack-gis
    data_files:
      - split: corpus
        path: beir-v1.0.0-cqadupstack-gis/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-cqadupstack-gis/queries/test/*.parquet
  - config_name: beir-v1.0.0-cqadupstack-mathematica
    data_files:
      - split: corpus
        path: beir-v1.0.0-cqadupstack-mathematica/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-cqadupstack-mathematica/queries/test/*.parquet
  - config_name: beir-v1.0.0-cqadupstack-physics
    data_files:
      - split: corpus
        path: beir-v1.0.0-cqadupstack-physics/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-cqadupstack-physics/queries/test/*.parquet
  - config_name: beir-v1.0.0-cqadupstack-programmers
    data_files:
      - split: corpus
        path: beir-v1.0.0-cqadupstack-programmers/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-cqadupstack-programmers/queries/test/*.parquet
  - config_name: beir-v1.0.0-cqadupstack-stats
    data_files:
      - split: corpus
        path: beir-v1.0.0-cqadupstack-stats/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-cqadupstack-stats/queries/test/*.parquet
  - config_name: beir-v1.0.0-cqadupstack-tex
    data_files:
      - split: corpus
        path: beir-v1.0.0-cqadupstack-tex/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-cqadupstack-tex/queries/test/*.parquet
  - config_name: beir-v1.0.0-cqadupstack-unix
    data_files:
      - split: corpus
        path: beir-v1.0.0-cqadupstack-unix/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-cqadupstack-unix/queries/test/*.parquet
  - config_name: beir-v1.0.0-cqadupstack-webmasters
    data_files:
      - split: corpus
        path: beir-v1.0.0-cqadupstack-webmasters/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-cqadupstack-webmasters/queries/test/*.parquet
  - config_name: beir-v1.0.0-cqadupstack-wordpress
    data_files:
      - split: corpus
        path: beir-v1.0.0-cqadupstack-wordpress/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-cqadupstack-wordpress/queries/test/*.parquet
  - config_name: beir-v1.0.0-dbpedia-entity
    data_files:
      - split: corpus
        path: beir-v1.0.0-dbpedia-entity/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-dbpedia-entity/queries/test/*.parquet
  - config_name: beir-v1.0.0-fever
    data_files:
      - split: corpus
        path: beir-v1.0.0-fever/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-fever/queries/test/*.parquet
  - config_name: beir-v1.0.0-fiqa
    data_files:
      - split: corpus
        path: beir-v1.0.0-fiqa/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-fiqa/queries/test/*.parquet
  - config_name: beir-v1.0.0-hotpotqa
    data_files:
      - split: corpus
        path: beir-v1.0.0-hotpotqa/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-hotpotqa/queries/test/*.parquet
  - config_name: beir-v1.0.0-nfcorpus
    data_files:
      - split: corpus
        path: beir-v1.0.0-nfcorpus/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-nfcorpus/queries/test/*.parquet
  - config_name: beir-v1.0.0-nq
    data_files:
      - split: corpus
        path: beir-v1.0.0-nq/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-nq/queries/test/*.parquet
  - config_name: beir-v1.0.0-quora
    data_files:
      - split: corpus
        path: beir-v1.0.0-quora/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-quora/queries/test/*.parquet
  - config_name: beir-v1.0.0-robust04
    data_files:
      - split: corpus
        path: beir-v1.0.0-robust04/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-robust04/queries/test/*.parquet
  - config_name: beir-v1.0.0-scidocs
    data_files:
      - split: corpus
        path: beir-v1.0.0-scidocs/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-scidocs/queries/test/*.parquet
  - config_name: beir-v1.0.0-scifact
    data_files:
      - split: corpus
        path: beir-v1.0.0-scifact/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-scifact/queries/test/*.parquet
  - config_name: beir-v1.0.0-signal1m
    data_files:
      - split: corpus
        path: beir-v1.0.0-signal1m/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-signal1m/queries/test/*.parquet
  - config_name: beir-v1.0.0-trec-covid
    data_files:
      - split: corpus
        path: beir-v1.0.0-trec-covid/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-trec-covid/queries/test/*.parquet
  - config_name: beir-v1.0.0-trec-news
    data_files:
      - split: corpus
        path: beir-v1.0.0-trec-news/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-trec-news/queries/test/*.parquet
  - config_name: beir-v1.0.0-webis-touche2020
    data_files:
      - split: corpus
        path: beir-v1.0.0-webis-touche2020/corpus/*.parquet
      - split: queries
        path: beir-v1.0.0-webis-touche2020/queries/test/*.parquet
  - config_name: msmarco-passage
    data_files:
      - split: corpus
        path: msmarco-passage/corpus/*.parquet
      - split: dl19_passage
        path: msmarco-passage/queries/dl19-passage/*.parquet
      - split: dl20
        path: msmarco-passage/queries/dl20/*.parquet
      - split: dev_subset
        path: msmarco-passage/queries/msmarco-passage.dev-subset/*.parquet

SlideOn sparse vectors for MS MARCO passage and BEIR

Pre-computed learned sparse vectors from lightonai/SlideOn (revision 370c600) for the MS MARCO v1 passage corpus and the 29 BEIR v1.0.0 corpora distributed with Anserini, plus their evaluation queries. Document ids, query ids and texts follow Anserini exactly (BEIR documents are encoded as title + " " + text), so the vectors drop into Anserini/Pyserini impact indexes. See the SlideOn & mSlideOn blog post for the models.

Layout

One config per dataset; each row is one document or query:

column type content
id string Anserini docid / qid
indices list active latents (0–32767), sorted by decreasing weight
weights list the model's weights, exactly as it outputs them (FP16, no quantization)

Scores are raw dot products between query and document vectors (no log, no normalization).

Choosing the sparsity (Matryoshka budgets)

SlideOn was trained with Matryoshka budgets of 512 or 1024 document latents and 32, 64 or 128 query latents. Because each row is sorted by weight, keeping the first k entries is exactly the model's max_active_dims=k output:

  • documents store the top 1024 latents (the largest trained document budget; docs with fewer active latents keep all of them). Truncating further (e.g. to 512) reduces index size and latency.
  • queries are stored unpruned; truncate to the trained query budgets for faster search.
from datasets import load_dataset

docs = load_dataset("lightonai/SlideOn-sparse-vectors", "beir-v1.0.0-scifact", split="corpus")
k = 512
docs = docs.map(lambda r: {"indices": r["indices"][:k], "weights": r["weights"][:k]})

Anserini

to_anserini.py (in this repo) truncates to top-k, quantizes weights as round(w * 100) (the SPLADE convention; costs ≤ 0.001 nDCG@10 in our checks) and writes JsonVectorCollection documents and TsvString topics:

python to_anserini.py beir-v1.0.0-scifact/corpus collections/scifact/part0.jsonl.gz --k 512
python to_anserini.py beir-v1.0.0-scifact/queries/test topics.scifact.tsv.gz --query

bin/run.sh io.anserini.index.IndexCollection -collection JsonVectorCollection -input collections/scifact \
  -index indexes/scifact.slideon -generator DefaultLuceneDocumentGenerator -threads 16 -impact -pretokenized
bin/run.sh io.anserini.search.SearchCollection -index indexes/scifact.slideon -topics topics.scifact.tsv.gz \
  -topicReader TsvString -output run.scifact.txt -impact -pretokenized -removeQuery -hits 1000

Citation 

@misc{moura2026slideon,
  author       = {Moura Junior, Paulo Roberto and Sourty, Raphaël},
  title        = {{SlideOn} \& {mSlideOn}: Sparsified late-interaction and dense retrievers},
  year         = {2026},
  howpublished = {Hugging Face Blog},
  url          = {https://huggingface.co/blog/lightonai/slideon-mslideon}
}