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Paper Citation Record · LEDGER

AGIF: An Adaptive Graph-Interactive Framework for Joint Multiple Intent Detection and Slot Filling

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2004.10087.

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

pith.paper-citation-record.v1
2004.10087 v4

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 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T04:46:39.666283Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T04:46:40.169869Z

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 8131ab32-8555-4715-a9cf-bde790f56030 · inbound

Training-Free versus Training-Based Intent Classification in LLMs: Accuracy, Robustness, and Failure Modes cites this paper.

Training-Free versus Training-Based Intent Classification in LLMs: Accuracy, Robustness, and Failure Modes AGIF: An Adaptive Graph-Interactive Framework for Joint Multiple Intent Detection and Slot Filling

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-04T07:49:36.636612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:49:36.636612Z digest=sha256:be44557f2e95bb58db98fa28370c5433cade70920930bd26d7074e3b905c7538

Observation 9fb7097d-4845-4a57-9791-e4eb8693a43a · inbound

Spoken Function Calling: A New Perspective on Spoken Language Understanding for Large Audio Language Models cites this paper.

Spoken Function Calling: A New Perspective on Spoken Language Understanding for Large Audio Language Models AGIF: An Adaptive Graph-Interactive Framework for Joint Multiple Intent Detection and Slot Filling

Reference 29

Resolution
verified exact
local_arxiv, observed 2026-08-06T04:46:40.175397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T04:46:39.666283Z digest=sha256:258a865cc4450e4363f102c6f55cd629cf15b422f293ca36746299d944f38701