Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Emotion and Intent Joint Understanding in Multimodal Conversation: A Benchmarking Dataset
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2407.02751.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:59:25.277830Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-10T14:45:47.554280Z
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 85f1b478-a1c2-47ae-88a7-c07cff3450a9 · inbound
EmotionTalk: An Interactive Chinese Multimodal Emotion Dataset With Rich Annotations cites this paper.
EmotionTalk: An Interactive Chinese Multimodal Emotion Dataset With Rich Annotations Emotion and Intent Joint Understanding in Multimodal Conversation: A Benchmarking Dataset
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:59:25.277830Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e822ecf1-6d2a-44da-8ba2-e1245a6bdfaa · inbound
End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning cites this paper.
End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Emotion and Intent Joint Understanding in Multimodal Conversation: A Benchmarking Dataset
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:36:05.795773Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6da1e265-d2a5-4e83-b894-b666742f7e1c · inbound
Deep Learning Approaches for Multimodal Intent Recognition: A Survey cites this paper.
Deep Learning Approaches for Multimodal Intent Recognition: A Survey Emotion and Intent Joint Understanding in Multimodal Conversation: A Benchmarking Dataset
Reference 84
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:36:33.744146Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3809e920-260d-4155-bcb8-67d043bb1216 · inbound
MISID: A Multimodal Multi-turn Dataset for Complex Intent Recognition in Strategic Deception Games cites this paper.
MISID: A Multimodal Multi-turn Dataset for Complex Intent Recognition in Strategic Deception Games Emotion and Intent Joint Understanding in Multimodal Conversation: A Benchmarking Dataset
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T14:45:47.600669Z
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.
Observation 0de157f2-39aa-4fff-aa17-457a6b77ef5a · inbound
OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing cites this paper.
OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing Emotion and Intent Joint Understanding in Multimodal Conversation: A Benchmarking Dataset
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T13:55:58.460765Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.