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Paper Citation Record · LEDGER

AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2501.16566.

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

pith.paper-citation-record.v1
2501.16566 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:30:01.599045Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T14:08:22.075048Z

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 2709bacd-1e47-4e65-b0df-341064a66a43 · inbound

EmoSign: A Multimodal Dataset for Understanding Emotions in American Sign Language cites this paper.

EmoSign: A Multimodal Dataset for Understanding Emotions in American Sign Language AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T15:30:01.599045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:30:01.599045Z digest=sha256:091860a050b1b26d25d4d21e63c122725f89325b59afa2bfd79090a21377f3eb

Observation 9ff15cd6-87af-4345-9f2f-47c7635f8d50 · inbound

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions cites this paper.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-06T13:07:27.597574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:07:27.597574Z digest=sha256:11faa3e6de1852116e8d4358688cb41731c653f95186dddd1702afce1bbe677a

Observation 53e94391-8752-4c87-91f6-da012278d3c6 · inbound

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models cites this paper.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-02T20:14:04.044246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T20:14:04.044246Z digest=sha256:4e485a7c1cd87f50ff664c50d893e89221b337626c90a598c3a9ffc0de4b3101

Observation a6e8d0c8-77e7-4658-85ff-ef5eb51f3f29 · inbound

EmoTrans: A Benchmark for Understanding, Reasoning, and Predicting Emotion Transitions in Multimodal LLMs cites this paper.

EmoTrans: A Benchmark for Understanding, Reasoning, and Predicting Emotion Transitions in Multimodal LLMs AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-11T20:31:15.298129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-08T08:34:14.297331Z digest=sha256:c4ec5dfef81cf9d6c6c5803b816361a6ae04f0e98149db29943cadb4f61e4ecd

Observation 2596fc17-bdad-4a8a-80d2-2093b1c4b358 · inbound

EmoS: A High-Fidelity Multimodal Benchmark for Fine-grained Streaming Emotional Understanding cites this paper.

EmoS: A High-Fidelity Multimodal Benchmark for Fine-grained Streaming Emotional Understanding AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models

Reference 57

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:31:33.427912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-12T02:32:35.333227Z digest=sha256:43cf235843f9887c1a5fbc1740e9358203cc9efd1bebd3f024879673b263f220

Observation d08fce51-bbd1-4dd9-ba08-0544184343ba · inbound

MOTOR-Bench: A Real-world Dataset and Multi-agent Framework for Zero-shot Human Mental State Understanding cites this paper.

MOTOR-Bench: A Real-world Dataset and Multi-agent Framework for Zero-shot Human Mental State Understanding AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-12T02:51:17.689880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-12T02:50:10.046572Z digest=sha256:5798a9336d4a899fc791c659d37d095830ffd138be912ff937444c98267c0214

Observation c9ace2b9-3300-4a4d-b359-546770cf6fdd · inbound

DeceptionX: From Multimodal Evidence to Explainable Deception Detection cites this paper.

DeceptionX: From Multimodal Evidence to Explainable Deception Detection AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-07-03T05:27:40.107506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T13:15:49.796647Z digest=sha256:25aa83b906b4cd7bdb9afa838fb633a305c57349ffdd94c1ace3510b536b8a65

Observation b03e81a9-caae-4d49-98d9-88d8ae409121 · inbound

DeceptionX: From Multimodal Evidence to Explainable Deception Detection cites this paper.

DeceptionX: From Multimodal Evidence to Explainable Deception Detection AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-04T03:03:32.875571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T03:03:32.875571Z digest=sha256:14dd4824bca4dd44766c43cf3f5fe3e460c47c9bb1d9cdb3d8d5480cf2b9f085

Observation 35ba8b94-5697-4183-ac91-a172fc11c732 · inbound

Reasoning for Mobile User Experience with Multimodal LLMs: Task, Benchmark, and Approach cites this paper.

Reasoning for Mobile User Experience with Multimodal LLMs: Task, Benchmark, and Approach AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-07-03T14:08:22.076550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T07:12:44.999056Z digest=sha256:346ce82d2f973af9cf4e92293b6637d61e8d9ca362b2b41fe93555b5ea1e327f

Observation 0cde136d-44ef-459f-8cce-3807cd4da7be · inbound

Toward Annotation-Efficient Continuous Emotion Arousal Quantification via Group-Level EEG Dynamic Neural Synchrony cites this paper.

Toward Annotation-Efficient Continuous Emotion Arousal Quantification via Group-Level EEG Dynamic Neural Synchrony AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models

Reference 293

Resolution
unresolved
no resolver link, observed 2026-07-31T14:47:03.023064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T14:47:03.023064Z digest=sha256:69dd7f2fe5756e6c066d4ebd31305460ff9babc4ed97453e7e8620c7aa81c856

Observation d1a33118-3b7d-49d1-b429-eb24363fd0d6 · inbound

COSI-Lab: Conference Living Lab for Modeling Multi-Perspective Multimodal Social Intention cites this paper.

COSI-Lab: Conference Living Lab for Modeling Multi-Perspective Multimodal Social Intention AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-03T00:52:08.338727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T00:52:08.338727Z digest=sha256:64f410662d2191ff7dc4f4b76a1f9b85a88968a0a796e8ffe3a2a5952cec2436