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Paper Citation Record · LEDGER

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization

As of 8 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2607.21013.

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

pith.paper-citation-record.v1
2607.21013 v2

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T08:49:15.654400Z

measured 45 of 45 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

45 of 45 outbound references displayed

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  • unresolved45
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1661cd3e-af1c-46ee-832a-d9c56fc36dc1 · outbound

This paper cites an unresolved cited work.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

Reference 1

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source=pdf_text observed=2026-08-01T08:49:10.905017Z digest=sha256:d206d414d80ee413d3a1333330c2242340b1425668034353c3367ac699f1781b

Observation e0b33a40-24e4-4633-94c1-2150cdc69009 · outbound

This paper cites Qwen2.5-VL Technical Report.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Qwen2.5-VL Technical Report

Reference 3

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source=pdf_text observed=2026-08-01T08:49:11.056916Z digest=sha256:a7e52a3506a286c2adb370764e9fd4926ebcc389702ab6e24176497321d2d570

Observation 7aeb22c6-2965-4bbe-8344-74c0ca236186 · outbound

This paper cites an unresolved cited work.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

Reference 4

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source=pdf_text observed=2026-08-01T08:49:11.192718Z digest=sha256:f8e31b5d955b2a1af999c644b1eed11d523ea826a83399718557118f642be3e1

Observation 335d2f84-3d0d-46fa-9f68-f024efc74114 · outbound

This paper cites VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs

Reference 5

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source=pdf_text observed=2026-08-01T08:49:11.461440Z digest=sha256:2af9d5cb25c18d9c1ab1cd268a5f7de5d7d8fae7e4ac871928fb7d97e9dbd07a

Observation 7d452bcd-efad-4280-824a-702d95f9e228 · outbound

This paper cites an unresolved cited work.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

Reference 6

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source=pdf_text observed=2026-08-01T08:49:11.653079Z digest=sha256:86c56b2e92ab2e8e41d3e124917b4c6d872a1aec17e21e6e859e8c02a8bdb284

Observation ea150781-ebcc-4eee-99a7-274586254c88 · outbound

This paper cites Group-in-Group Policy Optimization for LLM Agent Training.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Group-in-Group Policy Optimization for LLM Agent Training

Reference 7

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source=pdf_text observed=2026-08-01T08:49:11.775928Z digest=sha256:dfbf676e8f50ecb06d2561528d5245ac45f1b172a008ac54d02162f88e83d84a

Observation a8c95a60-3a93-406d-876a-f1ed7ed1c895 · outbound

This paper cites an unresolved cited work.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

Reference 8

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source=pdf_text observed=2026-08-01T08:49:11.950233Z digest=sha256:5a11ea9e1f89b1cd3b03a354bb5b8cf1deab51a46060cd9021a34774eb8fc06d

Observation c522ffed-93d0-43b5-aa1f-5055ba40cb71 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 9

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source=pdf_text observed=2026-08-01T08:49:12.094840Z digest=sha256:5f8b4924fbf4fe0dbbf600df221a9122dd3c22ce9b1d26dc74af2bddc90c7b51

Observation 478eb93b-b4ad-447e-b4e6-104c02692f80 · outbound

This paper cites GPT-4o System Card.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization GPT-4o System Card

Reference 10

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Observation 69cdeff9-09ab-42f3-bffa-e48e65f9cd89 · outbound

This paper cites Chat-UniVi: Unified Visual Representation Empowers Large Language Models with Image and Video Understanding.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Chat-UniVi: Unified Visual Representation Empowers Large Language Models with Image and Video Understanding

Reference 11

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Observation 1180ac3c-e377-428e-98dd-06f587128004 · outbound

This paper cites an unresolved cited work.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

Reference 12

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Observation 5803d5fc-fdba-4b75-ad09-86a07bd66300 · outbound

This paper cites an unresolved cited work.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

Reference 13

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source=pdf_text observed=2026-08-01T08:49:12.622638Z digest=sha256:b6814454e6f10a00500486d9275834148bad900ceb20a21e98c494d3beb8b00a

Observation 34b55b1d-1333-4b2e-8e95-15d225fb4991 · outbound

This paper cites an unresolved cited work.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

Reference 14

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source=pdf_text observed=2026-08-01T08:49:12.645734Z digest=sha256:ec0da6da6cea9e055cfbb41055fb1bb16d0a89ea9b31c91b9c54153cc7612481

Observation 343db43f-eb21-412f-93f4-6c31e372719d · outbound

This paper cites VideoChat: Chat-Centric Video Understanding.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization VideoChat: Chat-Centric Video Understanding

Reference 15

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Observation a4360587-34b2-483b-97b3-d9b58cc3037a · outbound

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EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

Reference 16

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source=pdf_text observed=2026-08-01T08:49:12.759870Z digest=sha256:4eb914b423be2368e0c047c1daac1d442a3bd74a6fda8b0826abe542d5ce54e1

Observation f28593ff-06a0-4d7a-ad1e-44573bf37327 · outbound

This paper cites an unresolved cited work.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

Reference 17

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source=pdf_text observed=2026-08-01T08:49:12.819835Z digest=sha256:71bc856b0d216c51b37e76b7236cc86fb105deec2a23e039ce96a3b13ad0e511

Observation bf4ab915-b1e2-4dcd-a955-129529fa61e8 · outbound

This paper cites an unresolved cited work.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

Reference 18

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source=pdf_text observed=2026-08-01T08:49:12.868090Z digest=sha256:18a6307e4602b66296b68c7d436175ce7ebc9bae99966f9ac89c610ca765d935

Observation b95f051c-6a8e-40bc-9447-5dec8e7c6fe0 · outbound

This paper cites Reinforcement Learning with Human Feedback: Learning Dynamic Choices via Pessimism.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Reinforcement Learning with Human Feedback: Learning Dynamic Choices via Pessimism

Reference 19

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Observation e44c447f-7630-45a0-aadb-25b0a5f29312 · outbound

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EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

Reference 20

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Observation f3cb63eb-c373-4318-9751-a90a9ec61747 · outbound

This paper cites an unresolved cited work.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

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Observation f4c8b822-a571-478e-b80d-8ef8a4c96c95 · outbound

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EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

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Observation cf89f11a-50be-4838-a89a-4ad0dc242d1e · outbound

This paper cites an unresolved cited work.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

Reference 23

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source=pdf_text observed=2026-08-01T08:49:13.172348Z digest=sha256:0f1854a11e94e0e8f2ebef609b0dafa4c8111b7664907a31110569a68dec0fb7

Observation 30cccac3-b3ac-40f9-adef-3c640cb6616b · outbound

This paper cites Kangaroo: A Powerful Video-Language Model Supporting Long-context Video Input.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Kangaroo: A Powerful Video-Language Model Supporting Long-context Video Input

Reference 24

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Observation 4f7fdaff-54c2-4ced-86a3-c44683c7d1a1 · outbound

This paper cites Understanding R1-Zero-Like Training: A Critical Perspective.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Understanding R1-Zero-Like Training: A Critical Perspective

Reference 25

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Observation ea0d2259-c377-4a65-9e2d-3c4fe634035e · outbound

This paper cites NVILA: Efficient Frontier Visual Language Models.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization NVILA: Efficient Frontier Visual Language Models

Reference 26

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Observation 3511927c-87c6-4ba6-9db0-aa9c91452939 · outbound

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EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

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Observation 1a79d68a-28fc-49c1-8641-dcaf9a8de9eb · outbound

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EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

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source=pdf_text observed=2026-08-01T08:49:13.824748Z digest=sha256:515f30595d0f9876ef3ff1e6a9c3478f7ac575528226399b2e9912ad792f1766

Observation 50835670-d971-41ff-92f2-cce2ea2abf70 · outbound

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EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

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Observation 1e295c08-f524-4353-a496-faa56dd0255f · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 30

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Observation 6413a720-1198-4e21-830a-5b55ce3edb06 · outbound

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EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

Reference 31

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source=pdf_text observed=2026-08-01T08:49:14.267566Z digest=sha256:007149adf852d772ed55fa4b2cefcf46317c021df9e3524f7c58c7bb28e1f48b

Observation d5caed64-a3a3-43bf-b885-557b0a537f46 · outbound

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EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

Reference 32

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Observation 5065bb85-e243-4c09-b939-9f53b73111d5 · outbound

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EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

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Observation 0ac87f3e-eca8-4641-a7dc-9660ea53e82b · outbound

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EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

Reference 34

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Observation 49d0c8dc-fa16-4a70-aeda-7526f855f2a9 · outbound

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EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

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Observation 6c6b6216-194e-4b2f-a270-221153bb85ff · outbound

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EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

Reference 36

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Observation bd880192-12b8-4a7f-a8af-2cc0e0ec0aac · outbound

This paper cites Tenenbaum.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Tenenbaum

Reference 37

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source=pdf_text observed=2026-08-01T08:49:15.240895Z digest=sha256:299a629a71331a34b1b9234248555d39bca45f5dcb3e2ad441434708d1661cb0

Observation 538d335a-3c40-4909-82df-03c8d59afc1e · outbound

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EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Unresolved cited work

Reference 38

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source=pdf_text observed=2026-08-01T08:49:15.287043Z digest=sha256:c706677259e9e79a5c3182583d1ecdf14de5e44d597ae8d3d2ae47ef64c1a86a

Observation 3d56b3ea-a767-4efa-bdd1-fa8df4fdda76 · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 39

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source=pdf_text observed=2026-08-01T08:49:15.330140Z digest=sha256:a742c8029382f3578b568f2314a4ff49c83e974f2148386174c1ca1a4a631ad6

Observation 8ab6c6d3-98bc-4ecf-ab85-5e0e5fcb5f30 · outbound

This paper cites mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality

Reference 40

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source=pdf_text observed=2026-08-01T08:49:15.164333Z digest=sha256:25de2fc17457b6c0c157ed1e6d62056f22be462d2259ea1ba0c76ac23a7464e7

Observation d55d1f61-ca41-40d9-9a28-f01b0f5480f2 · outbound

This paper cites LLaVA-Video: Video Instruction Tuning With Synthetic Data.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization LLaVA-Video: Video Instruction Tuning With Synthetic Data

Reference 41

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source=pdf_text observed=2026-08-01T08:49:15.545006Z digest=sha256:72ba63f630aeb02e6adde99af7586ee5031accac6529759e5b32096ea3a72fe7

Observation 18ecc8a2-ebe1-4678-b989-9c8b88244285 · outbound

This paper cites R1-Omni: Explainable Omni-Multimodal Emotion Recognition with Reinforcement Learning.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization R1-Omni: Explainable Omni-Multimodal Emotion Recognition with Reinforcement Learning

Reference 42

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source=pdf_text observed=2026-08-01T08:49:15.654400Z digest=sha256:918c064d0f4bab7fad581646fb4992205473d8cb722e8a91d328a2fdc442a884

Observation c7448407-9300-44d5-adb3-44abdaae46bb · outbound

This paper cites Long Context Transfer from Language to Vision.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Long Context Transfer from Language to Vision

Reference 44

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source=pdf_text observed=2026-08-01T08:49:15.410966Z digest=sha256:ef36acbfb9fa41ce118af11eb92e65261235723539a8cc0af097f61e9ca8a8ce

Observation deee8af2-e613-4ac8-a72e-f6794952ee86 · outbound

This paper cites Proximal Policy Optimization Algorithms.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization Proximal Policy Optimization Algorithms

Reference 2017

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source=pdf_text observed=2026-08-01T08:49:14.035514Z digest=sha256:71d470a07201ff33a12e850a56b42db31f3c0503456299a8453cb59a67f1f2f2

Observation dd740b84-c8fd-4c35-8b50-0d3282ed7e84 · outbound

This paper cites In Annual Conference on Neural Information Processing Systems.

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization In Annual Conference on Neural Information Processing Systems

Reference 2021

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-01T08:49:14.507829Z digest=sha256:19f55cddafbd409f701eae29a8f88abda691b2c1e34ffe6600d770970d966af5

Observation e2962c2d-3365-4286-b8b9-a231651f0401 · outbound

This paper cites InProceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024).

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization InProceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024)

Reference 2024

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no resolver link, observed 2026-08-01T08:49:13.697518Z

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source=pdf_text observed=2026-08-01T08:49:13.697518Z digest=sha256:27a439ee0298cd2160d35973604af4ae3b4155d3f2611d2a06bb477585f37537

Pith citing papers

No inbound Pith citation observations are available.