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Paper Citation Record · LEDGER

A Fully Automated Pipeline for Conversational Discourse Annotation: Tree Scheme Generation and Labeling with Large Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2504.08961.

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

pith.paper-citation-record.v1
2504.08961 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 2026-08-07T14:16:53.710371Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T05:33:28.947521Z

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 dc7f618f-cfde-40e4-9b06-6e25b459551b · inbound

Analyzing Biases in Political Dialogue: Tagging U.S. Presidential Debates with an Extended DAMSL Framework cites this paper.

Analyzing Biases in Political Dialogue: Tagging U.S. Presidential Debates with an Extended DAMSL Framework A Fully Automated Pipeline for Conversational Discourse Annotation: Tree Scheme Generation and Labeling with Large Language Models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T14:16:53.710371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:16:53.710371Z digest=sha256:1d85e8a41b5219bd005b83e506886a6a95e271cafe78d5bdf7f909a5f9377100

Observation 9df11ec7-bed3-4f62-a38e-7bda1dec6d9f · inbound

Intent Matters: Enhancing AI Tutoring with Fine-Grained Pedagogical Intent Annotation cites this paper.

Intent Matters: Enhancing AI Tutoring with Fine-Grained Pedagogical Intent Annotation A Fully Automated Pipeline for Conversational Discourse Annotation: Tree Scheme Generation and Labeling with Large Language Models

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-08-07T05:33:29.040064Z

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=arxiv_source observed=2026-08-07T05:33:27.891247Z digest=sha256:414944dd34972eb166adfc8f09e2bb1df61c1120f0172b9e50998ad1b34bba09