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Paper Citation Record · LEDGER

MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 56 inbound Pith citation observations for arXiv:1810.02508.

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

pith.paper-citation-record.v1
1810.02508 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 56 of 56 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 56 of 56 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:17:44.363763Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T23:56:38.424836Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

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Pith citing papers

Observation e732cb0f-40bb-42a1-9497-d3443dd6c52b · inbound

Deep Multimodal Learning with Missing Modality: A Survey cites this paper.

Deep Multimodal Learning with Missing Modality: A Survey MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 50

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local_arxiv, observed 2026-05-17T22:26:03.889343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-17T22:26:03.706725Z digest=sha256:5c4fabd497932a6b5d90bf3d8e95df870eacb89a7ed6d01a8e1053b0f0bccfb4

Observation 3e58d9d8-59dc-430d-a7d1-c85b5f02d3de · inbound

Once More, With Feeling: Measuring Emotion of Acting Performances in Contemporary American Film cites this paper.

Once More, With Feeling: Measuring Emotion of Acting Performances in Contemporary American Film MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 10

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source=pdf_text observed=2026-08-12T20:08:42.804657Z digest=sha256:eb93ab184194da3514307a6d21e134ca4b76275f516998589c8180b530077c03

Observation c709dcf0-38fb-4d80-8873-b73e0644205c · inbound

WavChat: A Survey of Spoken Dialogue Models cites this paper.

WavChat: A Survey of Spoken Dialogue Models MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 168

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source=pdf_text observed=2026-08-12T20:13:57.880727Z digest=sha256:222325b26726879c32cf6ead17fc28e2cb2e4fcbac00e39a4682c2a40f926419

Observation 71f6a02a-5588-4675-a436-3c090e793f67 · inbound

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations cites this paper.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 18

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source=pdf_text observed=2026-08-12T15:48:47.444332Z digest=sha256:c9d913f8186e4a681c30fef952636d31340e91c1a96909259a4fc56925dad9c6

Observation f9366436-e76f-4f1f-8760-ae3355f798c9 · inbound

Who Can Withstand Chat-Audio Attacks? An Evaluation Benchmark for Large Audio-Language Models cites this paper.

Who Can Withstand Chat-Audio Attacks? An Evaluation Benchmark for Large Audio-Language Models MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 30

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source=arxiv_source observed=2026-08-12T14:53:50.255144Z digest=sha256:81e9b41d3c336add0fef8492db669265b6c5ebb1a7f0a32fd53ef784151b34e2

Observation 9c5c212b-0b8b-49d2-8e7d-3fdeb55bf159 · inbound

SentiXRL: An advanced large language Model Framework for Multilingual Fine-Grained Emotion Classification in Complex Text Environment cites this paper.

SentiXRL: An advanced large language Model Framework for Multilingual Fine-Grained Emotion Classification in Complex Text Environment MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 23

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source=arxiv_source observed=2026-08-12T11:31:54.626678Z digest=sha256:6db1265362fa99cee3c11a80b173ca6b88b33790cc56184999282ed58d34b408

Observation 51133a9c-8d8c-4a69-aedb-3d974d2b367a · inbound

MERCI: Multimodal Emotional and peRsonal Conversational Interactions Dataset cites this paper.

MERCI: Multimodal Emotional and peRsonal Conversational Interactions Dataset MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 19

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source=pdf_text observed=2026-08-11T21:12:11.318506Z digest=sha256:96c187338a97d681c50b0638c4dd6b9771f96a7cf8770157e7170109902d03aa

Observation 807482db-a36f-4fea-bd0d-bbce639f42f7 · inbound

WavFusion: Towards wav2vec 2.0 Multimodal Speech Emotion Recognition cites this paper.

WavFusion: Towards wav2vec 2.0 Multimodal Speech Emotion Recognition MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 22

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source=pdf_text observed=2026-08-11T20:38:01.958786Z digest=sha256:40f93615fc7d7eba6b0afa6e400d75d156f411a7f9a87cff7951c05be90093aa

Observation 1444384f-54c8-484c-b745-b60e68337c55 · inbound

EmoVerse: Exploring Multimodal Large Language Models for Sentiment and Emotion Understanding cites this paper.

EmoVerse: Exploring Multimodal Large Language Models for Sentiment and Emotion Understanding MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 24

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source=pdf_text observed=2026-08-11T18:21:40.053544Z digest=sha256:41c8f9e6ff016295255a64ddba0ed5e763b85e6f109dcfd42d76fa0a59215ade

Observation 5005b19b-13ce-4266-8976-4333e6c7a9ac · inbound

VSD2M: A Large-scale Vision-language Sticker Dataset for Multi-frame Animated Sticker Generation cites this paper.

VSD2M: A Large-scale Vision-language Sticker Dataset for Multi-frame Animated Sticker Generation MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 26

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source=arxiv_source observed=2026-08-11T18:05:13.492090Z digest=sha256:36cfb2e6bdc2fd886ffcf245e12e518008529774b60ac887538e6a58ed74de70

Observation e0b7fb3c-99a3-42fa-9fe0-cd07cb0558f3 · inbound

TouchASP: Elastic Automatic Speech Perception that Everyone Can Touch cites this paper.

TouchASP: Elastic Automatic Speech Perception that Everyone Can Touch MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 35

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source=pdf_text observed=2026-08-11T11:18:35.270979Z digest=sha256:b2cfe8aaaa1fffcec0ea769d4b4e188f0ca4d73d782ec8feff24a1787c72e446

Observation d1902ffc-96f6-4347-9c70-b11f8d60bded · inbound

Friends-MMC: A Dataset for Multi-modal Multi-party Conversation Understanding cites this paper.

Friends-MMC: A Dataset for Multi-modal Multi-party Conversation Understanding MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 28

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source=arxiv_source observed=2026-08-11T05:41:47.636044Z digest=sha256:e1ada476ecb62344f829214d8ed0fa20f190eea7380383b081634a4e8110e89e

Observation 9271ce35-a891-468b-8feb-7294782536e8 · inbound

TED: Turn Emphasis with Dialogue Feature Attention for Emotion Recognition in Conversation cites this paper.

TED: Turn Emphasis with Dialogue Feature Attention for Emotion Recognition in Conversation MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 2018

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source=pdf_text observed=2026-08-10T22:38:07.692940Z digest=sha256:a92938a00eb25ff55e92a66ad4e58b9c6b77a0d246d834a3f7bb8eed9874ccd7

Observation afe84b7f-9da2-47d1-bc17-7dabddfe33cb · inbound

OmniChat: Enhancing Spoken Dialogue Systems with Scalable Synthetic Data for Diverse Scenarios cites this paper.

OmniChat: Enhancing Spoken Dialogue Systems with Scalable Synthetic Data for Diverse Scenarios MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 16

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source=pdf_text observed=2026-08-10T22:32:05.020670Z digest=sha256:5b7960e3d9ee316c0761bed3063cde36e94fc1213fd2655bfdeebfb005667c82

Observation 41c10c31-bfe6-4d78-b665-8553b1dfd4fc · inbound

CG-MER: A Card Game-based Multimodal dataset for Emotion Recognition cites this paper.

CG-MER: A Card Game-based Multimodal dataset for Emotion Recognition MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 20

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source=pdf_text observed=2026-08-10T20:32:37.936955Z digest=sha256:8932e0d688a0f9ed83219865fed887596eaba6b0d9660679cd7af43d3a4990c2

Observation e6f5bcd4-f365-4d4a-a6fd-77819a7e2a7d · inbound

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition cites this paper.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 35

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source=pdf_text observed=2026-08-10T14:43:42.168958Z digest=sha256:f7ff93af4039514dd6ae35a90142201b2d1df42751514f80333db36e5d1584d7

Observation 418d0f7c-a1b0-4381-b94a-4142749fb903 · inbound

LUCY: Linguistic Understanding and Control Yielding Early Stage of Her cites this paper.

LUCY: Linguistic Understanding and Control Yielding Early Stage of Her MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 2025

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source=pdf_text observed=2026-08-10T13:34:25.692578Z digest=sha256:9faca8c9f186bf925de3506c5556f45a0c5e319874d5e5754e78bdc941ad4d07

Observation 476a4860-d038-4dbb-988b-e16c8978d0a9 · inbound

Fine-tuning Multimodal Transformers on Edge: A Parallel Split Learning Approach cites this paper.

Fine-tuning Multimodal Transformers on Edge: A Parallel Split Learning Approach MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 2015

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source=pdf_text observed=2026-08-08T15:45:46.158254Z digest=sha256:e59ee8517778127581778f983189e5aa7febae19ad685db1da8a3fb9139aec8c

Observation 59d79e34-7fbb-4f5c-83ba-5e63a64b6c67 · inbound

Indeterminacy in Affective Computing: Considering Meaning and Context in Data Collection Practices cites this paper.

Indeterminacy in Affective Computing: Considering Meaning and Context in Data Collection Practices MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 14

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source=pdf_text observed=2026-08-07T22:04:02.380997Z digest=sha256:6bbe45bdd55291abb6f791e2a30b1ec7fee3db5fc5de531607d1c238e59d1767

Observation 0b644c84-467b-4b84-85a6-854b1b43f699 · inbound

SARI: Structured Audio Reasoning via Curriculum-Guided Reinforcement Learning cites this paper.

SARI: Structured Audio Reasoning via Curriculum-Guided Reinforcement Learning MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 28

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source=pdf_text observed=2026-08-16T11:17:44.363763Z digest=sha256:f308c99a0d6d7fbb4eb7e4e36e0685117fd6eed3103a38bce685c44f554829d2

Observation 0bf973c9-bf35-4be1-b11e-6825249ac6fa · inbound

Kimi-Audio Technical Report cites this paper.

Kimi-Audio Technical Report MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 56

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arxiv_id, observed 2026-05-11T19:21:27.179423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-11T19:21:26.933349Z digest=sha256:c81024600bc00995b251631b29d3a86efdd7b4b2e4deab2dbb78c1c74b8584d6

Observation c160bdec-ea6c-4a37-b4b4-485b967983e1 · inbound

R^3-VQA: "Read the Room" by Video Social Reasoning cites this paper.

R^3-VQA: "Read the Room" by Video Social Reasoning MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 39

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source=pdf_text observed=2026-08-15T23:41:34.210293Z digest=sha256:650010dbb2d86bf594aa7b73d39437a79b189244da62e630314988417cb61ae1

Observation 62f30405-db45-4ef7-8616-bf9d23185149 · inbound

The Super Emotion Dataset cites this paper.

The Super Emotion Dataset MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 6

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source=arxiv_source observed=2026-08-07T15:21:32.662188Z digest=sha256:e8272a21e43ca3783713a92047d69cfef5b8f556c9717a99db85282414f4396e

Observation 18a472da-0eb3-43ad-a503-d4395e809cec · 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 MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 38

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source=pdf_text observed=2026-08-07T15:30:02.422904Z digest=sha256:8a2c35fdfb2c0fe89a40ba60c00ad2b7331388c4eb4a1b16687a144a150ea6bb

Observation 4255d708-4045-48ec-8599-290c2fe4213b · inbound

TEDI: Trustworthy and Ethical Dataset Indicators to Analyze and Compare Dataset Documentation cites this paper.

TEDI: Trustworthy and Ethical Dataset Indicators to Analyze and Compare Dataset Documentation MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 49

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source=pdf_text observed=2026-08-07T14:42:07.710509Z digest=sha256:8e25d8c0717335f235b035e664a599e0ba80ba2d22c318298d9d61c1371531e9

Observation 85309405-8326-4388-82fb-9ed6d554e342 · inbound

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants cites this paper.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 51

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source=pdf_text observed=2026-08-07T14:12:38.697653Z digest=sha256:cf460cab54e82620d9a33c92ad3868e13cf6e81c82cb79e7bff2be3fb561df0a

Observation b3669ce7-39d5-400b-bf49-6feadcd1544b · inbound

Multimodal Federated Learning: A Survey through the Lens of Different FL Paradigms cites this paper.

Multimodal Federated Learning: A Survey through the Lens of Different FL Paradigms MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 101

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source=pdf_text observed=2026-08-07T13:28:21.277655Z digest=sha256:e48f302b83f7bbd433044b0e387df7014813c6232ad87cd283a358492ac8316b

Observation 68fb445d-6e54-401c-9cb8-cca0d63f89d6 · inbound

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs cites this paper.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 27

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source=pdf_text observed=2026-08-07T13:11:42.287535Z digest=sha256:46009d11f3da491c1ec613f8e3a2187d22f761b9d08a1607ab07b6335605281a

Observation 08cbe19a-afec-47a9-93eb-ee42b94ebd1b · inbound

The iNaturalist Sounds Dataset cites this paper.

The iNaturalist Sounds Dataset MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 77

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source=pdf_text observed=2026-08-07T12:12:13.361772Z digest=sha256:eff8d0c8fa3fb22f66357e282f8171cb998b15e21a4c7d3f200b6c34ad2cfc35

Observation 013366a8-60d9-4d0e-ad8c-10682cab0683 · inbound

SIV-Bench: A Video Benchmark for Social Interaction Understanding and Reasoning cites this paper.

SIV-Bench: A Video Benchmark for Social Interaction Understanding and Reasoning MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 35

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local_arxiv, observed 2026-05-19T11:37:15.765324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-19T11:36:36.687324Z digest=sha256:54f03ba2b49ce1172b2d7c474b94154971be0613dff696da8ef0aba4324ff10b

Observation 8d704c22-2375-4045-865c-fcd9292121b6 · inbound

How to Retrieve Examples in In-context Learning to Improve Conversational Emotion Recognition using Large Language Models? cites this paper.

How to Retrieve Examples in In-context Learning to Improve Conversational Emotion Recognition using Large Language Models? MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 16

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source=pdf_text observed=2026-08-06T22:57:47.708657Z digest=sha256:4343e2a4449b1b432d35bd57f50cd665d7eb394cda78f4e6f48b5d35dddb1779

Observation 43e2da5b-9ae2-4425-ad17-ff14b9336e1f · inbound

Hyper-modal Imputation Diffusion Embedding with Dual-Distillation for Federated Multimodal Knowledge Graph Completion cites this paper.

Hyper-modal Imputation Diffusion Embedding with Dual-Distillation for Federated Multimodal Knowledge Graph Completion MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 57

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source=pdf_text observed=2026-08-06T22:19:10.758674Z digest=sha256:db72b0b168be8ef1a239acfa559583885b66038231fd5d01089ee7251d20fbbc

Observation c55c26f9-af2a-4fca-8ae3-8e4e11ad7396 · inbound

Audio Flamingo 3: Advancing Audio Intelligence with Fully Open Large Audio Language Models cites this paper.

Audio Flamingo 3: Advancing Audio Intelligence with Fully Open Large Audio Language Models MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 94

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local_arxiv, observed 2026-05-15T03:42:45.121348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-15T03:42:44.523919Z digest=sha256:c725bf5cc29c7d567a5ca4e62831f1709dfd77a7a6edc51381c51ebb06a39e87

Observation cb049c05-3b65-42f8-b241-f696b3dc92c2 · inbound

Salience Adjustment for Context-Based Emotion Recognition cites this paper.

Salience Adjustment for Context-Based Emotion Recognition MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 34

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source=pdf_text observed=2026-08-06T16:27:49.583461Z digest=sha256:41164c87bab0246fb7fde2baabb658c86733dade1d424c820d498247af6bb854

Observation d915f76c-e091-4c4e-8496-012f69e9870b · inbound

Multimodal Large Language Models for End-to-End Affective Computing: Benchmarking and Boosting with Generative Knowledge Prompting cites this paper.

Multimodal Large Language Models for End-to-End Affective Computing: Benchmarking and Boosting with Generative Knowledge Prompting MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 19

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no resolver link, observed 2026-08-06T05:02:24.438791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:02:24.438791Z digest=sha256:48bfb8a61d8185994c4f828721ed5b2ed9750149cea121d97a726c9ba02ad4ce

Observation 9a878111-3e64-45c5-be7f-f3070c80186d · inbound

Grounding Emotion Recognition with Visual Prototypes: VEGA -- Revisiting CLIP in MERC cites this paper.

Grounding Emotion Recognition with Visual Prototypes: VEGA -- Revisiting CLIP in MERC MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 34

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no resolver link, observed 2026-08-05T23:49:17.456516Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:49:17.456516Z digest=sha256:93ff05856263368516427102cfb4420a7fc9c29660383da8d70a2056d35084e1

Observation 594d4442-89ff-4a55-ad24-7a14fcc799f1 · inbound

A Trustworthy Method for Multimodal Emotion Recognition cites this paper.

A Trustworthy Method for Multimodal Emotion Recognition MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 48

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no resolver link, observed 2026-08-05T22:03:27.040416Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:03:27.040416Z digest=sha256:6b2ff467a7b19e866011d634f5aa24349b2f1b49803aab7e42f0fbc04b0ca899

Observation 9922ac05-b81e-4638-a22d-3422c6914f70 · inbound

LLaSO: A Foundational Framework for Reproducible Research in Large Language and Speech Model cites this paper.

LLaSO: A Foundational Framework for Reproducible Research in Large Language and Speech Model MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 66

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no resolver link, observed 2026-08-05T17:56:54.367312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:56:54.367312Z digest=sha256:95214fc28d65883c8d6db1d008dc15de79655c6988bd3a74bb02278c3fb377ed

Observation 8f3a2d7c-3c5c-4a82-ad09-b6f4e4ee3e4e · inbound

CodecBench: A Comprehensive Benchmark for Acoustic and Semantic Evaluation cites this paper.

CodecBench: A Comprehensive Benchmark for Acoustic and Semantic Evaluation MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 12

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no resolver link, observed 2026-08-05T15:00:14.045603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:00:14.045603Z digest=sha256:6477a2ec992c175f76f102a04db97a155772dea2e9892f6744b2057f2d5b680b

Observation de151e24-330f-45b9-866c-006bb4c8f4fc · inbound

AudioCodecBench: A Comprehensive Benchmark for Audio Codec Evaluation cites this paper.

AudioCodecBench: A Comprehensive Benchmark for Audio Codec Evaluation MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 31

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unresolved
no resolver link, observed 2026-08-05T11:41:02.074677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T11:41:02.074677Z digest=sha256:a484dac671260de2dd902ff2b129bc192aa60bb683fc394db18e07d1c8ec2723

Observation ddb7442b-451b-48e0-8207-beed547fc09a · inbound

Benchmarking Gaslighting Attacks Against Speech Large Language Models cites this paper.

Benchmarking Gaslighting Attacks Against Speech Large Language Models MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-05-25T08:10:31.473686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-25T08:06:59.951859Z digest=sha256:5aba979b5f91866e588c513858b1c17940aff3d430f0ea1c9a4e4297c9daf027

Observation 07e88292-3f1c-4f12-816f-e3de83876357 · inbound

StableToken: A Noise-Robust Semantic Speech Tokenizer for Resilient SpeechLLMs cites this paper.

StableToken: A Noise-Robust Semantic Speech Tokenizer for Resilient SpeechLLMs MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 62

Resolution
verified exact
local_arxiv, observed 2026-05-18T13:01:24.312792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-18T12:57:04.450462Z digest=sha256:359b0c699b161c9e125f1925bb2f4684b0dcbbc43e4fd27efe6907a3ff1fa10e

Observation dbc2b25d-b38f-466c-9474-26e972a603c6 · inbound

Revisiting Audio-language Pretraining for Learning General-purpose Audio Representation cites this paper.

Revisiting Audio-language Pretraining for Learning General-purpose Audio Representation MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 35

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unresolved
no resolver link, observed 2026-08-03T21:06:11.114113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T21:06:11.114113Z digest=sha256:00eaacf93dcc5d3b6b4497c881a8d1775f89890b3137c0ac6ada1d313e0ebc98

Observation 7bf5d356-7651-44cb-a359-53d21fec67f8 · inbound

Causal Emotion Recognition in Conversation: Context Saturation and Discourse-Marker Evidence cites this paper.

Causal Emotion Recognition in Conversation: Context Saturation and Discourse-Marker Evidence MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 8

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unresolved
no resolver link, observed 2026-08-03T13:12:34.368533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T13:12:34.368533Z digest=sha256:a701b39d7a50a3e3c6decd527e1c60e842fa332e867c9bcaa709abb5d645db77

Observation 80b713dd-d248-485c-a72a-d51c1cf7b3e3 · inbound

Cross-Modal Emotion Transfer for Emotion Editing in Talking Face Video cites this paper.

Cross-Modal Emotion Transfer for Emotion Editing in Talking Face Video MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:25:58.469582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-10T17:39:02.676295Z digest=sha256:548c43531ef98692ee71dfa05062cf4ffd5b3e39905b7def904563011df757b2

Observation 1d82bec8-1524-48c8-8061-e34d1fdb891b · inbound

Inter-Stance: A Dyadic Multimodal Corpus for Conversational Stance Analysis cites this paper.

Inter-Stance: A Dyadic Multimodal Corpus for Conversational Stance Analysis MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 32

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verified exact
arxiv_id, observed 2026-05-11T19:21:06.856879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-08T12:18:23.772037Z digest=sha256:95bf5e7551722d1b22b319b3fa3dd8d183c57f5733d913a10b34ad78c6ef0691

Observation 64c0ffad-ed57-43d2-95b1-aaef7b18b94b · inbound

VITA-QinYu: Expressive Spoken Language Model for Role-Playing and Singing cites this paper.

VITA-QinYu: Expressive Spoken Language Model for Role-Playing and Singing MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 62

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metadata mismatch
arxiv_id, observed 2026-05-11T04:50:55.887432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-11T01:03:09.942984Z digest=sha256:e72914dc957c3efd4b1b7a0035cedae81a5c102539b50b366d0e4c46b43ac1a9

Observation d5595b91-d2bd-4985-83b5-9bf5c52303c5 · inbound

Beyond Content: A Comprehensive Speech Toxicity Dataset and Detection Framework Incorporating Paralinguistic Cues cites this paper.

Beyond Content: A Comprehensive Speech Toxicity Dataset and Detection Framework Incorporating Paralinguistic Cues MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 21

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metadata mismatch
local_arxiv, observed 2026-05-19T18:37:42.809673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-19T18:36:34.351533Z digest=sha256:a533f42152b2decb0fe2c13f2452f38b853df8140930ad6f9acc5d39d0e8598e

Observation b1d74e34-972c-46c2-a5fe-c4aa3fd42fe4 · inbound

Multimodal Group Emotion Recognition In-the-Wild Towards a Privacy-Safe Non-Individual Approach cites this paper.

Multimodal Group Emotion Recognition In-the-Wild Towards a Privacy-Safe Non-Individual Approach MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 182

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verified exact
local_arxiv, observed 2026-06-29T13:03:26.051006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T13:01:00.924735Z digest=sha256:629a3fade086b872ca9b5cbc6092244a3de11a201799ab0dfde796bbf16ffa4f

Observation 1cb15cb7-161c-43bb-b952-ece211dbf0c8 · inbound

Real-time body pose non-verbal communication with a consistency-based reliability measure cites this paper.

Real-time body pose non-verbal communication with a consistency-based reliability measure MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 34

Resolution
verified exact
local_arxiv, observed 2026-07-03T00:17:28.685162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-27T17:23:54.914116Z digest=sha256:a5670c4d84b61ef4345184bbd9ef65e6a23a186887a135d0fb735b8a05be0fe7

Observation c3fff5a6-66bb-4438-bb61-b676638f5bd0 · inbound

MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition cites this paper.

MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 72

Resolution
verified exact
local_arxiv, observed 2026-07-03T23:19:03.677917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-26T22:32:15.878239Z digest=sha256:57183fa73c0367fb5afba5c1fd66465c7ecaeb979ad15fa90ce8096125416390

Observation c95a7239-c582-48b4-b650-f598e4f940e7 · inbound

Video2Reaction: Mapping Video to Audience Reaction Distribution in the Wild cites this paper.

Video2Reaction: Mapping Video to Audience Reaction Distribution in the Wild MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 25

Resolution
metadata mismatch
local_arxiv, observed 2026-07-09T23:56:38.426123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-09T23:51:55.422232Z digest=sha256:e9e41c0fd1f1b6386e9f9f7067ea43979a13c4917a344a4288d86f2913fa2418

Observation a89eed8e-1841-4a6c-843c-1245e60cd0d9 · inbound

InCarEmo: A Multimodal Dataset for In-Cabin Emotion Recognition and Driver State Monitoring cites this paper.

InCarEmo: A Multimodal Dataset for In-Cabin Emotion Recognition and Driver State Monitoring MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 25

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unresolved
no resolver link, observed 2026-08-02T01:25:07.637033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T01:25:07.637033Z digest=sha256:acc81b113df65db2e601ac699861112abdca4dc0b56c5f16074a890f52b01410

Observation acb99571-8d10-496e-a60d-d94f803d3602 · inbound

EII-SCL: Harnessing Emotional Inertia for Multimodal Emotion Recognition in Conversation cites this paper.

EII-SCL: Harnessing Emotional Inertia for Multimodal Emotion Recognition in Conversation MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 33

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unresolved
no resolver link, observed 2026-08-01T18:16:51.388447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:16:51.388447Z digest=sha256:a2734e57a401953a526a58ad1ebe200df35b46a65e5077bead9356d179c4ba00

Observation c46d8dc4-9ea7-4826-a273-816f7a411f02 · inbound

EmoEUS: Uncertainty Supervision for Multimodal Emotion Recognition in Conversation cites this paper.

EmoEUS: Uncertainty Supervision for Multimodal Emotion Recognition in Conversation MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 31

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unresolved
no resolver link, observed 2026-08-01T18:16:36.454435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:16:36.454435Z digest=sha256:55054530f0203ff2dc6e67cb0b23eef4f9f95c8265a03feb5f21611a88c51535

Observation 246322d0-02e8-47f8-a425-78bdd04036be · inbound

X$^3$-OPD: Distilling Reasoning into Large Audio-Language Models via On-Policy Alignment cites this paper.

X$^3$-OPD: Distilling Reasoning into Large Audio-Language Models via On-Policy Alignment MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 30

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unresolved
no resolver link, observed 2026-08-01T07:12:10.212235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T07:12:10.212235Z digest=sha256:9fbc16f1ddb16603fd0677091b66b1af7e47219dea60a0741d8bd097564b9870