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Paper Citation Record · LEDGER

SummScreen: A Dataset for Abstractive Screenplay Summarization

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2104.07091.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2104.07091 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:55:01.394063Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-11T20:29:59.783919Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 234fb7f1-6519-44b0-a38b-e18bd7fef55a · inbound

Retentive Network: A Successor to Transformer for Large Language Models cites this paper.

Retentive Network: A Successor to Transformer for Large Language Models SummScreen: A Dataset for Abstractive Screenplay Summarization

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-11T20:29:59.788158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-11T20:29:59.633357Z digest=sha256:66ff4ed86925334eb9a221e720f57c4b30c6d5b38c0159db168dc6757b4f1231

Observation df1be5b7-76d5-4efc-81e9-36ae2b186cae · inbound

FriendsQA: A New Large-Scale Deep Video Understanding Dataset with Fine-grained Topic Categorization for Story Videos cites this paper.

FriendsQA: A New Large-Scale Deep Video Understanding Dataset with Fine-grained Topic Categorization for Story Videos SummScreen: A Dataset for Abstractive Screenplay Summarization

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-11T05:55:01.394063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:55:01.394063Z digest=sha256:0a606dceebc63c7ec32655f179af967292e781a6e51a7299e3a2892395ad520e

Observation d51955f2-bf2a-40e0-b48f-02a45a354d95 · inbound

Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models cites this paper.

Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models SummScreen: A Dataset for Abstractive Screenplay Summarization

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-10T16:15:39.297757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:15:39.297757Z digest=sha256:d7ddf25e0f98c14cfcc2b075dcfb3d660cd9fbf48456a71056ddfc3b3a03e0c8

Observation 17f4e5ca-9e28-457a-8cd7-859646cc2529 · inbound

HoPE: Hyperbolic Rotary Positional Encoding for Stable Long-Range Dependency Modeling in Large Language Models cites this paper.

HoPE: Hyperbolic Rotary Positional Encoding for Stable Long-Range Dependency Modeling in Large Language Models SummScreen: A Dataset for Abstractive Screenplay Summarization

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-05T05:36:52.435869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T05:36:52.435869Z digest=sha256:238a9a1923570125c3d0343d8087bdf6af6a3d67542e9717b35e0da9d0ca0281

Observation 6745dae9-29f2-4bb5-909a-3dbc1c6f6135 · inbound

Whose Story Gets Told? Positionality and Bias in LLM Summaries of Life Narratives cites this paper.

Whose Story Gets Told? Positionality and Bias in LLM Summaries of Life Narratives SummScreen: A Dataset for Abstractive Screenplay Summarization

Reference 122

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T01:04:50.225010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-10T01:00:41.543394Z digest=sha256:cd47029380bea83bb713ae4b607c0ab787b7f98b604c908830b4e48336f03312