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Paper Citation Record · LEDGER

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models

As of 7 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 2 inbound Pith citation observations for arXiv:2602.23802.

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

pith.paper-citation-record.v1
2602.23802 v2

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T20:14:04.208238Z

measured 72 of 72 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T20:58:30.855338Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:49:18.237054Z

Reference resolution

70 of 70 outbound references displayed

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Outbound references

Observation 4cd56d96-2b52-4103-a29d-74bb6f807d40 · outbound

This paper cites Qwen2.5-VL Technical Report.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Qwen2.5-VL Technical Report

Reference 1

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source=pdf_text observed=2026-08-02T20:14:03.926761Z digest=sha256:796c9567dbe82516d61f1d5a7d8fc1e42c5895f64960d47578f8e6bd22401db5

Observation 3e6a2209-868a-4065-a677-5949b44dea94 · outbound

This paper cites Chat-based person retrieval via dialogue-refined cross- modal alignment.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Chat-based person retrieval via dialogue-refined cross- modal alignment

Reference 2

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Observation f5f82134-7950-47e0-b50e-59a4701f04db · outbound

This paper cites LLaVA Steering: Visual Instruction Tuning with 500x Fewer Parameters through Modality Linear Representation-Steering.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models LLaVA Steering: Visual Instruction Tuning with 500x Fewer Parameters through Modality Linear Representation-Steering

Reference 3

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Observation 4b031acc-1e60-4a7e-9592-a5d988094944 · outbound

This paper cites SEED-GRPO: Semantic Entropy Enhanced GRPO for Uncertainty-Aware Policy Optimization.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models SEED-GRPO: Semantic Entropy Enhanced GRPO for Uncertainty-Aware Policy Optimization

Reference 4

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Observation b75a2b15-288a-46cc-bfc9-084c113ae010 · outbound

This paper cites Internvl: Scaling up vision foundation mod- els and aligning for generic visual-linguistic tasks.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Internvl: Scaling up vision foundation mod- els and aligning for generic visual-linguistic tasks

Reference 5

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Observation 867c155f-91dd-45cd-84de-92652adef16f · outbound

This paper cites Emotion-llama: Multimodal emo- tion recognition and reasoning with instruction tuning.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Emotion-llama: Multimodal emo- tion recognition and reasoning with instruction tuning

Reference 6

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Observation 2c596fe0-263a-40e7-ae4c-fc5c78ff0345 · outbound

This paper cites Emoe: Modality-specific enhanced dynamic emotion experts.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Emoe: Modality-specific enhanced dynamic emotion experts

Reference 7

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Observation e3a43277-9b65-48cc-8d6c-d0ace6ab562c · outbound

This paper cites Catch your emotion: Sharpening emotion perception in multimodal large language models.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Catch your emotion: Sharpening emotion perception in multimodal large language models

Reference 8

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Observation 69e9830d-e0f9-489f-9055-05e1339ef576 · outbound

This paper cites Video-R1: Reinforcing Video Reasoning in MLLMs.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Video-R1: Reinforcing Video Reasoning in MLLMs

Reference 9

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Observation 4c969bbd-7ccb-46ba-894c-6d7ce7317ced · outbound

This paper cites On Designing Effective RL Reward at Training Time for LLM Reasoning.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models On Designing Effective RL Reward at Training Time for LLM Reasoning

Reference 10

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Observation 169d64ab-9bc3-4aaa-a3d1-e31d2e091adb · outbound

This paper cites Making the V in VQA matter: Ele- vating the role of image understanding in Visual Question Answering.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Making the V in VQA matter: Ele- vating the role of image understanding in Visual Question Answering

Reference 11

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Observation 0e5c2c49-9e68-49f4-821b-c86b13211d03 · outbound

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

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 12

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Observation c884e79d-b998-4036-9c26-39a9e3a79689 · outbound

This paper cites Onellm: One framework to align all modalities with language.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Onellm: One framework to align all modalities with language

Reference 13

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Observation 88669c8e-ff9e-460f-a9bc-475363cf071b · outbound

This paper cites Boosting MLLM Reasoning with Text-Debiased Hint-GRPO.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Boosting MLLM Reasoning with Text-Debiased Hint-GRPO

Reference 14

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Observation 09b70d92-c221-4c5d-bb18-351c279dd5fc · outbound

This paper cites Keeping Yourself is Important in Downstream Tuning Multimodal Large Language Model.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Keeping Yourself is Important in Downstream Tuning Multimodal Large Language Model

Reference 15

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Observation 166182ab-f88f-4a23-94be-1b58b69e413f · outbound

This paper cites Learn from downstream and be yourself in multimodal large language model fine-tuning.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Learn from downstream and be yourself in multimodal large language model fine-tuning

Reference 16

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Observation b49e719c-bbed-4059-8cbf-2654b980bcec · outbound

This paper cites Be confident: Uncovering overfitting in mllm multi-task tuning.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Be confident: Uncovering overfitting in mllm multi-task tuning

Reference 17

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Observation f978c6f9-0930-4f9e-9c52-2fafc4da15a5 · outbound

This paper cites Mapo: Mixed advantage policy optimization.arXiv preprint arXiv:2509.18849, 2025.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Mapo: Mixed advantage policy optimization.arXiv preprint arXiv:2509.18849, 2025

Reference 18

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Observation 8d0ee372-0197-4789-b5fd-33a3547311bf · outbound

This paper cites Gqa: A new dataset for real-world visual reasoning and compositional question answering.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Gqa: A new dataset for real-world visual reasoning and compositional question answering

Reference 19

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Observation 6ba12ad3-7345-43f1-b9d5-bf74065a11d0 · outbound

This paper cites Learning from teaching reg- ularization: Generalizable correlations should be easy to im- itate.NeurIPS, 37:966–994, 2024.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Learning from teaching reg- ularization: Generalizable correlations should be easy to im- itate.NeurIPS, 37:966–994, 2024

Reference 20

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Observation b643d058-c196-4ab9-8cf6-775d461e7f7e · outbound

This paper cites Two Heads are Better Than One: Test-time Scaling of Multi-agent Collaborative Reasoning.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Two Heads are Better Than One: Test-time Scaling of Multi-agent Collaborative Reasoning

Reference 21

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Observation 4f545ca4-f4e5-46f0-8ab6-9fc7b8480e2a · outbound

This paper cites LLaVA-OneVision: Easy Visual Task Transfer.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models LLaVA-OneVision: Easy Visual Task Transfer

Reference 22

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Observation e9ed3b7d-bb1c-48e3-8590-3c8bb8682315 · outbound

This paper cites VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-Tuning.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-Tuning

Reference 23

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Observation 52a03b49-545a-4add-8801-f2ef62ba0e70 · outbound

This paper cites Mon- key: Image resolution and text label are important things for large multi-modal models.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Mon- key: Image resolution and text label are important things for large multi-modal models

Reference 24

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Observation 59cc902c-ffc9-4312-b13e-d044579918a7 · outbound

This paper cites Explainable Multimodal Emotion Recognition.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Explainable Multimodal Emotion Recognition

Reference 25

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Observation 6259af68-65e9-4987-87fb-aeb8c558bf51 · outbound

This paper cites Ex- plainable multimodal emotion reasoning.CoRR, 2023.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Ex- plainable multimodal emotion reasoning.CoRR, 2023

Reference 26

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

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

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

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Observation 27510ae0-731b-4a09-ba3b-d1d3fa7dfc4a · outbound

This paper cites Lorasculpt: Sculpting lora for harmonizing gen- eral and specialized knowledge in multimodal large language models.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Lorasculpt: Sculpting lora for harmonizing gen- eral and specialized knowledge in multimodal large language models

Reference 28

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Observation 5198f810-e98c-4f43-a03b-29e392bb71b6 · outbound

This paper cites Microsoft coco: Common objects in context.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Microsoft coco: Common objects in context

Reference 29

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Observation f2c09ffd-9984-4cc6-8f12-dffbfb00adc5 · outbound

This paper cites Improved baselines with visual instruction tuning.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Improved baselines with visual instruction tuning

Reference 30

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Observation 0e13ce9d-1ac6-4f46-ba5e-ece760393791 · outbound

This paper cites Reinforcement Learning Meets Large Language Models: A Survey of Advancements and Applications Across the LLM Lifecycle.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Reinforcement Learning Meets Large Language Models: A Survey of Advancements and Applications Across the LLM Lifecycle

Reference 31

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Observation ca3dee2f-ea98-4697-b24c-e2cc7392bf62 · outbound

This paper cites DoRA: Weight-Decomposed Low-Rank Adaptation.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models DoRA: Weight-Decomposed Low-Rank Adaptation

Reference 32

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source=pdf_text observed=2026-08-02T20:14:04.064395Z digest=sha256:02f564e229c7294e9df08b7d73aa507a1b1c2a5220c8439a2a49217fc6c44797

Observation 3d6b8d6d-4372-4639-b0c1-1623d1bf4361 · outbound

This paper cites GuardReasoner-VL: Safeguarding VLMs via Reinforced Reasoning.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models GuardReasoner-VL: Safeguarding VLMs via Reinforced Reasoning

Reference 33

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Observation 962da5aa-3069-4019-b7c8-bbc4b4b49f14 · outbound

This paper cites Visual-RFT: Visual Reinforcement Fine-Tuning.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Visual-RFT: Visual Reinforcement Fine-Tuning

Reference 34

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Observation 99ecd203-8520-4069-aa2e-076ab866789e · outbound

This paper cites Learn to explain: Multimodal reasoning via thought chains for science question answering.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Learn to explain: Multimodal reasoning via thought chains for science question answering

Reference 35

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Observation 92ee911f-cf4c-47d1-9d89-8c804cb215b8 · outbound

This paper cites ChartQA: A benchmark for question answering about charts with visual and logical reasoning.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models ChartQA: A benchmark for question answering about charts with visual and logical reasoning

Reference 36

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Observation aff71ea1-2ca9-4465-803d-97ee918da007 · outbound

This paper cites Con- templating visual emotions: Understanding and overcoming dataset bias.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Con- templating visual emotions: Understanding and overcoming dataset bias

Reference 37

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Observation 27520b90-5628-4f04-b25c-a61d3aa78a1f · outbound

This paper cites A mixed bag of emotions: Model, predict, and transfer emotion distributions.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models A mixed bag of emotions: Model, predict, and transfer emotion distributions

Reference 38

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Observation 0bf45be1-2d87-43d4-819e-b047bcce5e4d · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.NeurIPS, 36:53728–53741, 2023.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Direct preference optimization: Your language model is secretly a reward model.NeurIPS, 36:53728–53741, 2023

Reference 39

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source=pdf_text observed=2026-08-02T20:14:04.090762Z digest=sha256:c526b2c822827ef8fee36561ce5c9b9897c0d23bd8e653fac96459f2388808d0

Observation 6a028c1d-a1f0-43e3-8bb6-79290508172e · outbound

This paper cites Scalpel vs. Hammer: GRPO Amplifies Existing Capabilities, SFT Replaces Them.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Scalpel vs. Hammer: GRPO Amplifies Existing Capabilities, SFT Replaces Them

Reference 40

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Observation 4728e5c8-49e0-4840-8f3d-9bea881b4156 · outbound

This paper cites Group robust preference optimization in reward- free rlhf.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Group robust preference optimization in reward- free rlhf

Reference 41

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source=pdf_text observed=2026-08-02T20:14:04.097359Z digest=sha256:ef24e2efe16803c5fcbdd24e4b822be6b3b0c9f6ac1557f02f78f6ce03d65062

Observation c4a76982-bab2-4716-b3a1-911f1a06ad74 · outbound

This paper cites Improving LLM-Generated Code Quality with GRPO.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Improving LLM-Generated Code Quality with GRPO

Reference 42

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source=pdf_text observed=2026-08-02T20:14:04.101113Z digest=sha256:da32dea9f8cf15c992e46072eee48c04773ed43d58dad0ee5cb2ca3e06613aa9

Observation c032eb3f-1a85-4ae7-80d9-82f2ad050429 · outbound

This paper cites Backdoor Cleaning without External Guidance in MLLM Fine-tuning.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Backdoor Cleaning without External Guidance in MLLM Fine-tuning

Reference 43

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source=pdf_text observed=2026-08-02T20:14:04.105502Z digest=sha256:832a09bbe99cb34c2d8434d136e63a3d4d2a1335c4c272dfd9a5d1c62c31ed12

Observation 46c5102c-3f2c-401e-89c3-e8042cc4199c · outbound

This paper cites Safegrpo: Self-rewarded mul- timodal safety alignment via rule-governed policy optimiza- tion.arXiv preprint arXiv:2511.12982, 2025.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Safegrpo: Self-rewarded mul- timodal safety alignment via rule-governed policy optimiza- tion.arXiv preprint arXiv:2511.12982, 2025

Reference 44

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source=pdf_text observed=2026-08-02T20:14:04.109291Z digest=sha256:004569b5f5d004f86595f37f569fc20f06d304c572b12431ed7e991a7efb2b0e

Observation 69886bcf-14df-4f05-8660-906311129984 · outbound

This paper cites Proximal Policy Optimization Algorithms.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Proximal Policy Optimization Algorithms

Reference 45

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source=pdf_text observed=2026-08-02T20:14:04.113356Z digest=sha256:b0b28ece6e81474604ffdb5ab43cc0dd79fe941a0e1e55e434c3f1e05faf1f1c

Observation 1e57f08a-bbc3-4180-9778-995074537ebb · outbound

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

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 46

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source=pdf_text observed=2026-08-02T20:14:04.117269Z digest=sha256:c4496b98823a3ab6cb0b35359ca8eb4b93eb0c3936105cefd2bcd58cadcc07ac

Observation ecce399c-cda8-4b52-b950-650d78ca25d5 · outbound

This paper cites Towards vqa models that can read.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Towards vqa models that can read

Reference 47

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source=pdf_text observed=2026-08-02T20:14:04.120825Z digest=sha256:5ecb9706a0f80e87fa447334ab28f3af615f754bd3ad5921ca7ecbefdeb42286

Observation f372d45e-5e7b-40e5-94aa-87ed35887192 · outbound

This paper cites Delving into RL for Image Generation with CoT: A Study on DPO vs. GRPO.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Delving into RL for Image Generation with CoT: A Study on DPO vs. GRPO

Reference 48

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source=pdf_text observed=2026-08-02T20:14:04.125091Z digest=sha256:7ec2fd8319f9d164b2f0ddd7c7a47f30a2702d82d5f158329cc8a40d936647f4

Observation 7a3c0ec5-ac01-4374-90f1-de67f8959d2e · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models LLaMA: Open and Efficient Foundation Language Models

Reference 49

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source=pdf_text observed=2026-08-02T20:14:04.128711Z digest=sha256:e3b9f5b2f2473fb99643263cb079f8bbc201ede05e9f4bcb08ae662e8b767d2a

Observation 522417f4-1a78-4044-a568-0fd3d45fca66 · outbound

This paper cites Safety in Large Reasoning Models: A Survey.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Safety in Large Reasoning Models: A Survey

Reference 50

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source=pdf_text observed=2026-08-02T20:14:04.132863Z digest=sha256:006a5d73a34be5f562f9b327e076949d454e6945c6fe2252897e303ac93cb7b3

Observation 22e2dcba-707d-4f81-b689-e8ad3995e6b8 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 51

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source=pdf_text observed=2026-08-02T20:14:04.136705Z digest=sha256:52a562d2195a22914723dc29cda04be0c3bc5b3d0ca1025624bf1f8ae4f1ce29

Observation 59060050-f419-4957-89b1-643d4c823cba · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large lan- guage models.NeurIPS, 35:24824–24837, 2022.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Chain-of-thought prompting elicits reasoning in large lan- guage models.NeurIPS, 35:24824–24837, 2022

Reference 52

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source=pdf_text observed=2026-08-02T20:14:04.140872Z digest=sha256:4ab0bb9d50c54b686711ad3e004bd0545ac27bfc6d97e260b25a2ef1d5d7eb29

Observation c1e93403-6ca3-4643-ac57-c4e73cf20b0e · outbound

This paper cites Emovit: Revolutionizing emotion insights with vi- sual instruction tuning.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Emovit: Revolutionizing emotion insights with vi- sual instruction tuning

Reference 53

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source=pdf_text observed=2026-08-02T20:14:04.144878Z digest=sha256:c52b289576998a5f7574057bbc98ba01c46c49f78dc8d29f1c98169d1cef7174

Observation 87fc2543-5052-495c-859b-030fe9d8634d · outbound

This paper cites EMO-LLaMA: Enhancing Facial Emotion Understanding with Instruction Tuning.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models EMO-LLaMA: Enhancing Facial Emotion Understanding with Instruction Tuning

Reference 54

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source=pdf_text observed=2026-08-02T20:14:04.148188Z digest=sha256:f27d32a332bb66b893a52ca2aa369dce088b3a836389be710111f9f90552830e

Observation 3df01c42-bc3c-42a3-bcce-7636b9fec44e · outbound

This paper cites Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study

Reference 55

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source=pdf_text observed=2026-08-02T20:14:04.152731Z digest=sha256:f4cb1f1e06998b5ebdad58eb6311bc0b0186d212a76cefa9284567b5ed6d333e

Observation 692916be-1ac3-489f-a15d-be3cdbf6720c · outbound

This paper cites Context de-confounded emo- tion recognition.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Context de-confounded emo- tion recognition

Reference 56

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source=pdf_text observed=2026-08-02T20:14:04.156268Z digest=sha256:da98c80cda4d422e94de5af24be93c7df2df13f2185753e0e0eeb72f0b9a3203

Observation af7a6d69-2908-4c83-93d8-f171cf81bf40 · outbound

This paper cites Emoset: A large-scale visual emotion dataset with rich attributes.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Emoset: A large-scale visual emotion dataset with rich attributes

Reference 57

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source=pdf_text observed=2026-08-02T20:14:04.160499Z digest=sha256:4577b174d90f650eb391dee1904ef2ceb456d07af2607341914d2f51fb7c98ab

Observation f35fdd9d-b03b-4a5d-aa92-085b7533807b · outbound

This paper cites EmoLLM: Multimodal Emotional Understanding Meets Large Language Models.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models EmoLLM: Multimodal Emotional Understanding Meets Large Language Models

Reference 58

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source=pdf_text observed=2026-08-02T20:14:04.163905Z digest=sha256:d44b2151ac162d149529a3373560aa02b1c057016ffda8724e535b1d84728d4f

Observation 556aad84-e02d-4eb8-89cc-e5b46b98d3bf · outbound

This paper cites Treerpo: Tree relative policy optimization.arXiv preprint arXiv:2506.05183, 2025.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Treerpo: Tree relative policy optimization.arXiv preprint arXiv:2506.05183, 2025

Reference 59

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source=pdf_text observed=2026-08-02T20:14:04.167966Z digest=sha256:99ecae381108cf4aac668f7c84936d146391a88e7cb9b4f8e7d92cf8477555aa

Observation 8f57803f-09a7-4de7-acb0-196233095552 · outbound

This paper cites R1-ShareVL: Incentivizing Reasoning Capability of Multimodal Large Language Models via Share-GRPO.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models R1-ShareVL: Incentivizing Reasoning Capability of Multimodal Large Language Models via Share-GRPO

Reference 60

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source=pdf_text observed=2026-08-02T20:14:04.172212Z digest=sha256:ee4972ffe12ef3be501dc5ed2e749803b64d68b8bf1a12ef6a39a53a39973f1f

Observation 62ccc93d-2d7e-438a-95c0-4eb85a2c60fa · outbound

This paper cites A Survey of Safety on Large Vision-Language Models: Attacks, Defenses and Evaluations.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models A Survey of Safety on Large Vision-Language Models: Attacks, Defenses and Evaluations

Reference 61

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source=pdf_text observed=2026-08-02T20:14:04.175590Z digest=sha256:ec030c78193de1fa86a3e88a3c30a56f92f55a14df72298d84d7d71f1867d20e

Observation 3dcfe257-3936-4fa6-b59a-5fe1adcdfa63 · outbound

This paper cites From image descriptions to visual denotations: New similarity metrics for semantic inference over event descrip- tions.TACL, 2:67–78, 2014.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models From image descriptions to visual denotations: New similarity metrics for semantic inference over event descrip- tions.TACL, 2:67–78, 2014

Reference 62

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source=pdf_text observed=2026-08-02T20:14:04.179183Z digest=sha256:96967b7f300c0a928b766bb7bec9cae7c461d32893ecc85490c97b634d0a59a8

Observation 6d08763c-cd4f-4ed1-8cd7-fb6ff35ccfcf · outbound

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

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 63

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source=pdf_text observed=2026-08-02T20:14:04.182502Z digest=sha256:b5608bf4b40049c5a42994c4ee1ccb58d725073c0da389c0b724afc00549c0c6

Observation cbd7b248-e55a-4389-b6b7-990c45a2056c · outbound

This paper cites R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization

Reference 64

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source=pdf_text observed=2026-08-02T20:14:04.186690Z digest=sha256:900609b2fe16d73006dc3a873787dcf8a7819c50f6e53d6fabe8eab53e5fa4da

Observation 66cb5cf7-9f92-45a8-8ccb-796b1d8260de · outbound

This paper cites Microemo: Time-sensitive multimodal emotion recognition with subtle clue dynamics in video dialogues.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Microemo: Time-sensitive multimodal emotion recognition with subtle clue dynamics in video dialogues

Reference 65

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source=pdf_text observed=2026-08-02T20:14:04.190105Z digest=sha256:1accd78c5a7e1f47ac8a90e1fe576dcfabf5dcd30fd19873204d0773dc113de8

Observation 8d8e9f2e-b3b5-446e-9ad1-4a64d29f34d9 · outbound

This paper cites How Can LLM Guide RL? A Value-Based Approach.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models How Can LLM Guide RL? A Value-Based Approach

Reference 66

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source=pdf_text observed=2026-08-02T20:14:04.194029Z digest=sha256:664fd7f2496993d229811cd130ac6e780dce8b557a5d09071be63366f9b0a434

Observation 52018fda-f74d-4068-8447-68a61f8ef8f0 · outbound

This paper cites Facephi: Lightweight multimodal large language model for facial landmark emotion recogni- tion.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Facephi: Lightweight multimodal large language model for facial landmark emotion recogni- tion

Reference 67

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source=pdf_text observed=2026-08-02T20:14:04.198029Z digest=sha256:a7097bb5ba951c3aa216793c31e4348c6b819f57d89338b1d1816d11eb389f16

Observation 76d0ea6c-b4c6-4acf-a1aa-53d26834d7d3 · outbound

This paper cites GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection

Reference 68

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source=pdf_text observed=2026-08-02T20:14:04.201189Z digest=sha256:5d5ab764557bfefbdfcf78f3ac92cd652eabbd247f1e0888602ef7cc63f65679

Observation da0ed51d-46e0-4298-a61d-1cb6ba46f34e · outbound

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

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models R1-Omni: Explainable Omni-Multimodal Emotion Recognition with Reinforcement Learning

Reference 69

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source=pdf_text observed=2026-08-02T20:14:04.204686Z digest=sha256:2e0094a53bbe6c43c7f2669b6bb99764f6fa0ce99160462d26f31fcdb970bf33

Observation 2c6fc92a-3f10-48c5-9a5d-e03dc2aaa7f9 · outbound

This paper cites Reinforced MLLM: A Survey on RL-Based Reasoning in Multimodal Large Language Models.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models Reinforced MLLM: A Survey on RL-Based Reasoning in Multimodal Large Language Models

Reference 70

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source=pdf_text observed=2026-08-02T20:14:04.208238Z digest=sha256:b97979fd2dbe44bb6a62f4e6f1c39b03af94fa88b05fe7fcb5b9322b4a02c7e2

Pith citing papers

Observation fa78e801-308f-4fc0-9c07-e87da5f93f55 · 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 EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models

Reference 6

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verified exact
arxiv_id, observed 2026-07-09T02:19:51.159867Z

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:fffb6f4253517303a1f4a3f2625ce2573286172985b09441833a6e474086335e

Observation 69fc91f4-6db2-471b-96ed-195c024bd24c · inbound

ThinkDeception: A Progressive Reinforcement Learning Framework for Interpretable Multimodal Deception Detection cites this paper.

ThinkDeception: A Progressive Reinforcement Learning Framework for Interpretable Multimodal Deception Detection EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models

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arxiv_id, observed 2026-07-09T02:19:51.159867Z

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=2026-06-26T20:58:30.855338Z digest=sha256:295373c77cd9f0e8018934b3701a2b8b360786990e154634bfd1e977703409db