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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=sha256:57150a4c9b38f5d30ac812f5e7076f03943a0beffd7d5ba7c49eba06b188b4cf

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=sha256:2e93add35088dda52502f361e1cf23084da44500796799c61610a3914f3c3e72

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=sha256:4c6423f89f532b8717cc0cab64ae30a897e3e6373f644f8d04a655dce8e48ef1

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=sha256:293e893dde2094da9c1283b575c8d9befeb20681ab9947c2561fa66cd67c70ad

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=sha256:929b0844f2c5e3633af910fa04ea31b5b1b1c12ee56242c835a42f04614fa6e5