Paper Citation Record · LEDGER

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations

As of 11 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 4 inbound Pith citation observations for arXiv:2501.11468.

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

pith.paper-citation-record.v1
2501.11468 v1

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T18:17:35.636796Z

measured 61 of 61 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:47:55.530450Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

57 of 57 outbound references displayed

verified exact2
verified fuzzy43
unresolved12
parse uncertain0
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External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 866cf597-9335-406d-af67-1484c8a6e549 · outbound

This paper cites Affective multimodal human-computer interaction,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Affective multimodal human-computer interaction,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.305023Z

Source-reported events for the cited work

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Observation 5e41bea9-d8ef-46ba-a1d7-82db4dd73f62 · outbound

This paper cites Emotion Detection and Analysis on Social Media.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Emotion Detection and Analysis on Social Media

Reference 2

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Source-reported events for the cited work

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Observation cd31bab1-5abc-41bb-8447-aa75562f066c · outbound

This paper cites Acoustic and lexical sentiment analysis for customer service calls,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Acoustic and lexical sentiment analysis for customer service calls,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.294668Z

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Observation 5319079b-84c2-4e01-9db7-8ffd75547ee5 · outbound

This paper cites EmoKey: An emotion-aware smartphone keyboard for mental health monitoring,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations EmoKey: An emotion-aware smartphone keyboard for mental health monitoring,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.282950Z

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Observation de201f61-bf36-4ec1-b4ee-70e1d2a40216 · outbound

This paper cites K-EmoCon, a multimodal sensor dataset for contin- uous emotion recognition in naturalistic conversations,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations K-EmoCon, a multimodal sensor dataset for contin- uous emotion recognition in naturalistic conversations,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.271536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation eecb4f29-c582-4d43-8fd0-ba01e5eb10ce · outbound

This paper cites Emotion recognition in conversation: Research chal- lenges, datasets, and recent advances,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Emotion recognition in conversation: Research chal- lenges, datasets, and recent advances,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.260309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 218d5c2b-eae6-457d-8f5f-916ed708f7b3 · outbound

This paper cites Emotion recognition using facial expressions,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Emotion recognition using facial expressions,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.249711Z

Source-reported events for the cited work

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Observation 0aec1a22-6ce1-4d44-8121-9b7926a4d39a · outbound

This paper cites an unresolved cited work.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Unresolved cited work

Reference 8

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Source-reported events for the cited work

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Observation 03c98362-25c2-4815-ac91-5c702c1eea98 · outbound

This paper cites Individuality in communicative bodily behaviours,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Individuality in communicative bodily behaviours,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.229318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 13dac0de-cf6a-4ddd-86f1-3b1c8e49fe9d · outbound

This paper cites Physiological signals and their use in augment- ing emotion recognition for human–machine interaction,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Physiological signals and their use in augment- ing emotion recognition for human–machine interaction,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.218408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d03fef3a-3b49-4967-8bd5-5023e83342b6 · outbound

This paper cites A review of affective computing: From unimodal analysis to multimodal fusion,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations A review of affective computing: From unimodal analysis to multimodal fusion,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.207108Z

Source-reported events for the cited work

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Observation 989aff56-1feb-4c8f-a2f4-cb1cb21871d7 · outbound

This paper cites Some aspects of fundamental frequency and envelope amplitude as related to the emotional content of speech,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Some aspects of fundamental frequency and envelope amplitude as related to the emotional content of speech,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.196734Z

Source-reported events for the cited work

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Observation c77b0d66-4f67-4b0a-92f8-e9749555649f · outbound

This paper cites Emotion in speech: Recognition and application to call centers,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Emotion in speech: Recognition and application to call centers,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.184870Z

Source-reported events for the cited work

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Observation e9a6ee3c-1466-45d7-ae3e-1c3b7447c96c · outbound

This paper cites Speech emotion recognition using spectrogram & phoneme embedding.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Speech emotion recognition using spectrogram & phoneme embedding

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.173743Z

Source-reported events for the cited work

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Observation d7b145a2-bfcd-4657-a864-db92f7ed2fb7 · outbound

This paper cites Effective attention mechanism in dynamic models for speech emotion recognition,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Effective attention mechanism in dynamic models for speech emotion recognition,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.161775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 31555f2e-c111-478b-9a1e-364b9796a3d7 · outbound

This paper cites Multimodal transformer with learnable frontend and self attention for emotion recognition,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Multimodal transformer with learnable frontend and self attention for emotion recognition,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.150548Z

Source-reported events for the cited work

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Observation 04007e6f-651a-474a-ba31-f4ff45361c37 · outbound

This paper cites wav2vec 2.0: A framework for self-supervised learning of speech representations,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations wav2vec 2.0: A framework for self-supervised learning of speech representations,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.139343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d9d93a3d-1382-4c1f-a520-50a97a349f2e · outbound

This paper cites HuBERT: Self-supervised speech representation learning by masked prediction of hidden units,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations HuBERT: Self-supervised speech representation learning by masked prediction of hidden units,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.128421Z

Source-reported events for the cited work

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Observation 49ce9a4a-afdc-4d20-acc7-d777167e1482 · outbound

This paper cites WavLM: Large-scale self-supervised pre-training for full stack speech processing,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations WavLM: Large-scale self-supervised pre-training for full stack speech processing,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.117598Z

Source-reported events for the cited work

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Observation b8e6a9b6-7d14-47cb-b97e-903404c352bc · outbound

This paper cites SALMONN: Towards Generic Hearing Abilities for Large Language Models.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations SALMONN: Towards Generic Hearing Abilities for Large Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T18:17:35.493122Z

Source-reported events for the cited work

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Observation 5bad9113-8d95-4f27-a1a3-14cd052698d5 · outbound

This paper cites WavLLM: Towards Robust and Adaptive Speech Large Language Model.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations WavLLM: Towards Robust and Adaptive Speech Large Language Model

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T18:17:35.497624Z

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Observation a3447811-b9b6-4417-8a0d-10521405b4ab · outbound

This paper cites Sentiwordnet: A publicly available lexical resource for opinion mining,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Sentiwordnet: A publicly available lexical resource for opinion mining,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.106808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 37643e19-2583-49fe-afe9-3064e0cf88be · outbound

This paper cites Lexicon-based methods for sentiment analysis,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Lexicon-based methods for sentiment analysis,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.096339Z

Source-reported events for the cited work

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Observation f6aeab6a-b0fd-4378-a3b0-6a0e19ca802f · outbound

This paper cites Convolutional neural networks for sentence classification,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Convolutional neural networks for sentence classification,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.085890Z

Source-reported events for the cited work

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Observation 38599d5a-c0aa-494a-9682-8b7d7cf801db · outbound

This paper cites Opinion mining with deep recurrent neural networks,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Opinion mining with deep recurrent neural networks,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.074582Z

Source-reported events for the cited work

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Observation f94de10d-12ca-4dcf-a399-f01ae3d52001 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.063251Z

Source-reported events for the cited work

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Observation 60430582-59ab-4ca4-93d9-031a6dcc20dd · outbound

This paper cites Aspect-based sentiment analysis using bert,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Aspect-based sentiment analysis using bert,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.052343Z

Source-reported events for the cited work

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Observation be1fea05-c0a6-4952-a307-3895643a27de · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 28

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Observation e6f24913-5941-4531-8902-4544698ab002 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Exploring the limits of transfer learning with a unified text-to-text transformer,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.041059Z

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Observation b34c2d07-636b-45f7-bcb1-cd2c7c338514 · outbound

This paper cites Sentiment Analysis in the Era of Large Language Models: A Reality Check.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Sentiment Analysis in the Era of Large Language Models: A Reality Check

Reference 30

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Observation 3f9dff2c-2cfb-4ba9-a79d-daf0c93186ac · outbound

This paper cites HCAM -- Hierarchical Cross Attention Model for Multi-modal Emotion Recognition.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations HCAM -- Hierarchical Cross Attention Model for Multi-modal Emotion Recognition

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T18:17:35.535448Z

Source-reported events for the cited work

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Observation 628fa957-8825-452e-9b37-1576f981fcb4 · outbound

This paper cites DialogueGCN: A Graph Convolutional Neural Net- work for Emotion Recognition in Conversation,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations DialogueGCN: A Graph Convolutional Neural Net- work for Emotion Recognition in Conversation,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.024440Z

Source-reported events for the cited work

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Observation 53af04c7-8f1a-45a9-9f5c-23ebba94c50a · outbound

This paper cites EmoCaps: Emotion capsule based model for conversational emotion recognition,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations EmoCaps: Emotion capsule based model for conversational emotion recognition,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.013202Z

Source-reported events for the cited work

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Observation 5f74b22b-3d8e-4c30-b979-a65fbf207f0d · outbound

This paper cites Robust speech recognition via large-scale weak supervision,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Robust speech recognition via large-scale weak supervision,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:36.002290Z

Source-reported events for the cited work

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Observation 10937777-6e3f-4a52-bf68-6b82ec5aaeeb · outbound

This paper cites Leveraging Content and Acoustic Representations for Speech Emotion Recognition.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Leveraging Content and Acoustic Representations for Speech Emotion Recognition

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T18:17:35.549930Z

Source-reported events for the cited work

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Observation 6239004e-c073-4f25-811d-0a1009bf31e1 · outbound

This paper cites Vilbert: Pretraining task-agnostic visiolinguistic represen- tations for vision-and-language tasks,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Vilbert: Pretraining task-agnostic visiolinguistic represen- tations for vision-and-language tasks,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:35.991294Z

Source-reported events for the cited work

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Observation 07ceb723-15c5-4e72-aa22-fd10da2abb48 · outbound

This paper cites IEMOCAP: Interactive emotional dyadic motion capture database,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations IEMOCAP: Interactive emotional dyadic motion capture database,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:35.978298Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation dcd13b27-cd19-4848-a278-21dae32acc67 · outbound

This paper cites MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:35.967174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation cc33a720-c270-41bf-b79c-549335ee802a · outbound

This paper cites MOSI: Multimodal Corpus of Sentiment Intensity and Subjectivity Analysis in Online Opinion Videos.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations MOSI: Multimodal Corpus of Sentiment Intensity and Subjectivity Analysis in Online Opinion Videos

Reference 39

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Observation ba0b7b62-d813-4610-a861-c73c36a4113b · outbound

This paper cites Is ChatGPT a Good Sentiment Analyzer? A Preliminary Study.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Is ChatGPT a Good Sentiment Analyzer? A Preliminary Study

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-10T18:17:35.569004Z

Source-reported events for the cited work

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Observation 7aa58c72-1264-467d-9e83-fae4e456f139 · outbound

This paper cites Can ChatGPT Understand Too? A Comparative Study on ChatGPT and Fine-tuned BERT.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Can ChatGPT Understand Too? A Comparative Study on ChatGPT and Fine-tuned BERT

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-10T18:17:35.573236Z

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Observation 89ff986e-c5a6-4810-9e0d-76275c3aef26 · outbound

This paper cites Emotionflow: Capture the dialogue level emotion transitions,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Emotionflow: Capture the dialogue level emotion transitions,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:35.956180Z

Source-reported events for the cited work

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Observation 9468b5ce-94e0-41cf-9c22-49d9cd9c4254 · outbound

This paper cites Supervised adversarial contrastive learning for emotion recognition in conversations,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Supervised adversarial contrastive learning for emotion recognition in conversations,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:35.945083Z

Source-reported events for the cited work

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Observation dcc564e9-e5b1-49e1-b1dc-1cd9653da385 · outbound

This paper cites Hierarchical Dialogue Understanding with Special Tokens and Turn-level Attention.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Hierarchical Dialogue Understanding with Special Tokens and Turn-level Attention

Reference 44

Resolution: verified exact; local_arxiv, observed 2026-08-10T18:17:35.703566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9c9854e4-7106-45b2-9f96-33bac1d6c7b7 · outbound

This paper cites Emotion-anchored contrastive learning framework for emotion recognition in conversation,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Emotion-anchored contrastive learning framework for emotion recognition in conversation,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:35.934154Z

Source-reported events for the cited work

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Observation 91dcfdf9-c96e-4999-9462-bccca90ed5a5 · outbound

This paper cites Multi-task self-supervised learning for robust speech recognition,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Multi-task self-supervised learning for robust speech recognition,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:35.923873Z

Source-reported events for the cited work

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Observation acc39a6f-e84f-4aa0-a71e-aecf078a4ba2 · outbound

This paper cites SUPERB: Speech Processing Universal PERfor- mance Benchmark,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations SUPERB: Speech Processing Universal PERfor- mance Benchmark,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:35.911298Z

Source-reported events for the cited work

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Observation a0e681ba-0310-4cfe-a927-27915f74f7f2 · outbound

This paper cites ASR and Emotional Speech: A Word-Level Investigation of the Mutual Impact of Speech and Emotion Recognition.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations ASR and Emotional Speech: A Word-Level Investigation of the Mutual Impact of Speech and Emotion Recognition

Reference 48

Resolution: verified exact; local_arxiv, observed 2026-08-10T18:17:35.686611Z

Source-reported events for the cited work

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Observation 5249a9f6-c1bc-48d7-a0d8-50eec549ae25 · outbound

This paper cites Building naturalistic emotionally balanced speech corpus by retrieving emotional speech from existing podcast recordings,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Building naturalistic emotionally balanced speech corpus by retrieving emotional speech from existing podcast recordings,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:35.900529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 77d57589-31ed-4fac-b5c6-d910b47bf336 · outbound

This paper cites Context-dependent sentiment analysis in user-generated videos,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Context-dependent sentiment analysis in user-generated videos,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:35.889219Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b3afd40b-4c7d-4c1e-8f44-6d7e66da2914 · outbound

This paper cites Decoupled weight decay regularization,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Decoupled weight decay regularization,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:35.877120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d27ca7da-ccad-46a4-aa13-3f5e2d22e1e7 · outbound

This paper cites Locally confined modality fusion network with a global perspective for multimodal human affective computing,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations Locally confined modality fusion network with a global perspective for multimodal human affective computing,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:35.864016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 66a9c210-d7cd-4975-a918-c3ff7f8e270a · outbound

This paper cites M3er: Multiplicative multimodal emotion recognition using facial, textual, and speech cues,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations M3er: Multiplicative multimodal emotion recognition using facial, textual, and speech cues,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:35.852336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 66de570d-dc6f-4aa7-b5eb-e9a92af914ca · outbound

This paper cites DialogueTRM: Exploring multi-modal emotional dy- namics in a conversation,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations DialogueTRM: Exploring multi-modal emotional dy- namics in a conversation,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:35.840844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7d2c6473-a9a9-47b9-8410-c9785ada2a3e · outbound

This paper cites SMIN: Semi-supervised Multi-modal Interaction Net- work for Conversational Emotion Recognition,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations SMIN: Semi-supervised Multi-modal Interaction Net- work for Conversational Emotion Recognition,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:35.830161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 130df2fd-f238-405d-b6d9-aed2f2d9285e · outbound

This paper cites UniMSE: Towards Unified Multimodal Sentiment Analysis and Emotion Recognition.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations UniMSE: Towards Unified Multimodal Sentiment Analysis and Emotion Recognition

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-10T18:17:35.633069Z

Source-reported events for the cited work

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Observation 6921e8d7-6667-400a-a7e7-27feda6d958f · outbound

This paper cites TelME: Teacher-leading Multimodal Fusion Network for Emotion Recognition in Conversation,.

LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations TelME: Teacher-leading Multimodal Fusion Network for Emotion Recognition in Conversation,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:17:35.818465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

Observation 2d189dd6-ead4-46ae-af79-a67e5ba7d5bf · inbound

ABHINAYA -- A System for Speech Emotion Recognition In Naturalistic Conditions Challenge cites this paper.

ABHINAYA -- A System for Speech Emotion Recognition In Naturalistic Conditions Challenge LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T14:47:55.530450Z

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Observation 69c4f873-9993-4f4a-9f03-b79854db2ad6 · inbound

Multimodal Emotion Recognition in Conversations: A Survey of Methods, Trends, Challenges and Prospects cites this paper.

Multimodal Emotion Recognition in Conversations: A Survey of Methods, Trends, Challenges and Prospects LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T13:56:45.620948Z

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Observation 5b5d3e63-f6b8-439a-ab2d-f0034b509ce6 · inbound

EmotionRankCLAP: Bridging Natural Language Speaking Styles and Ordinal Speech Emotion via Rank-N-Contrast cites this paper.

EmotionRankCLAP: Bridging Natural Language Speaking Styles and Ordinal Speech Emotion via Rank-N-Contrast LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T12:45:09.683582Z

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Observation e0492a22-5dd2-4387-bf09-750e0ec97054 · inbound

Retrieval-Augmented Personalization with Foundation Models for Wearable Stress Detection cites this paper.

Retrieval-Augmented Personalization with Foundation Models for Wearable Stress Detection LLM supervised Pre-training for Multimodal Emotion Recognition in Conversations

Reference 96

Resolution: verified exact; arxiv_id, observed 2026-06-26T00:28:42.836140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.