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Paper Citation Record · LEDGER

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

As of 14 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 2026-08-14T06:32:32.682623+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

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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:bd28850d13ebb9de93133f19fec4f881aac1d2ce41f333eb2c8e513810777bad

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:d29d57e4653c1f4ce130d02f0cdd420981a0b5da927492880830a344f71a6678

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:d23267eaa4027f65bc9b1115836fa4fcee0f6054e851b2befc58660d96cb0d99

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=sha256:2f23a5f42b5cf3a57f676e455a5c50d262081523d159bb99856056f274b196aa

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:ded2ea317040fe71212c86bc8f5aa78feb9d161c4428fd559cd72aaa863b5032

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=sha256:833b45d231011c23eb484c98aa3e8f1de55f2d469873e1624c8a3c6fa6f9c025

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:b299fae3539befca975be86f9f691ac76744f988641409ba05deb7d9aefa7a8f

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=sha256:7a44692ac62469ecbd89f735b80228365f1a2c09f362d6da3b2cdfb216a52b6c

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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source=pdf_text observed=2026-08-01T08:49:12.288025Z digest=sha256:4cab8d872916d25f75fdc07715b1b2139b9f7cc544adb2344b4a9f37852b0a0f

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=sha256:2fb2319141900ce5829ae842871ba9d69b35f3f108a6725859e693c36f97690a

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=sha256:92ed647823093a8b498f12487f47adb8a0ec4f1c2b1bbea6e1f5ad6b1f45fe39

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

This paper cites an unresolved cited work.

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:aab1854f16c7b5e1a73d7f4d78b9b836944e962f533eb8dff06b213f61361bf1

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

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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=sha256:4110b9cf396f144a1e12c0139b82e2b56ce4887e48b9a446043e6b4efb6706ba

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

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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:efdf0e7aeedd47079e19cb9129b3a073962cc9e4af1b6464689b12129044678d

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

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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 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:c8674c51fc198e90b0e3ed9c66fcbddd9050caa4c1f349c23666449ab93c13a9

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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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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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

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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=sha256:986da5d8215d5152d10bb75741e0a1e0c134609f6fc3cc55dc45bbddc986a97c

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=sha256:7781089e4f52e2baf17687427c2419c22b74298b428157bfe44e9f413c7be6ff

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=sha256:52b49a3766811133175970dadcddd2dbd2d9a3e5fecd410b24bbd3b6ec10760c

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=sha256:1655ce92dd65075edbd850bfad7a8cc3ec952593a0d529a030c073926c90cabf

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:e5d389253d56f74ed5ae9ddfe21fa85066f788a534352de4b65986008906a377

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=sha256:0d8326f36a6c87d824a7296d7847325e8f2c986564a91f569cdd4d62dfbfb4dd

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:ee5c5362d2ad7dbeee3b2c581ac37d8aee3ec016f0f08a7cd9f71c75271bb610

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=sha256:3d844a5cd959b707d18b904ce880304e414140ce8b108e574b0ffc0b5d6c799e

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=pdf_text observed=2026-08-01T08:49:14.507829Z digest=sha256:ad72e7c99b5a62dd512c23b9593e47712608e6d2fd50b92bc63778bf6d2a79f2

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=sha256:819eebdfd89f5cd991ca6b5ef166905336f714638c6945c09696c92d330a1588

Pith citing papers

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