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Paper Citation Record · LEDGER

PanoSent: A Panoptic Sextuple Extraction Benchmark for Multimodal Conversational Aspect-based Sentiment Analysis

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2408.09481.

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

pith.paper-citation-record.v1
2408.09481 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:43:05.664555Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T21:23:27.769310Z

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 dbbe53f4-361e-4a30-b62c-42c117851ec2 · inbound

Recent Advances in Multimodal Affective Computing: An NLP Perspective cites this paper.

Recent Advances in Multimodal Affective Computing: An NLP Perspective PanoSent: A Panoptic Sextuple Extraction Benchmark for Multimodal Conversational Aspect-based Sentiment Analysis

Reference 263

Resolution
verified exact
arxiv_id, observed 2026-05-23T21:23:27.772834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-23T21:19:06.228443Z digest=sha256:2260042cd3453faeae4321d7f25384fe8c6425d3d43e522eabe292e48bd3462f

Observation 30acc78e-3ab1-4d1f-84b9-04eb110a645c · inbound

Large Language Models Enhanced by Plug and Play Syntactic Knowledge for Aspect-based Sentiment Analysis cites this paper.

Large Language Models Enhanced by Plug and Play Syntactic Knowledge for Aspect-based Sentiment Analysis PanoSent: A Panoptic Sextuple Extraction Benchmark for Multimodal Conversational Aspect-based Sentiment Analysis

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T00:43:05.664555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:43:05.664555Z digest=sha256:ebc95efc8135a5c68ed137ee98172046fb5c4e63baab624ed6b3e84ea4d4e413