MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition | Paper Citation Record

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This paper cites write newline.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition write newline

Reference 1

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This paper cites GPT-4 Technical Report.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition GPT-4 Technical Report

Reference 2

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This paper cites S., Senior, A., Vinyals, O., and Zisserman, A.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition S., Senior, A., Vinyals, O., and Zisserman, A

Reference 3

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Observation 09235db7-3652-4033-92ad-731095d6de81 · outbound

This paper cites LRS3-TED: a large-scale dataset for visual speech recognition.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition LRS3-TED: a large-scale dataset for visual speech recognition

Reference 4

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This paper cites Gqa: Training generalized multi-query transformer models from multi-head checkpoints.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Gqa: Training generalized multi-query transformer models from multi-head checkpoints

Reference 5

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This paper cites Muavic: A multilingual audio-visual corpus for robust speech recognition and robust speech-to-text translation.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Muavic: A multilingual audio-visual corpus for robust speech recognition and robust speech-to-text translation

Reference 6

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This paper cites Xls-r: Self-supervised cross-lingual speech representation learning at scale.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Xls-r: Self-supervised cross-lingual speech representation learning at scale

Reference 7

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

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition wav2vec 2.0: A framework for self-supervised learning of speech representations

Reference 8

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This paper cites SeamlessM4T: Massively Multilingual & Multimodal Machine Translation.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition SeamlessM4T: Massively Multilingual & Multimodal Machine Translation

Reference 9

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This paper cites and Timofte, R.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition and Timofte, R

Reference 10

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This paper cites Large Language Models are Strong Audio-Visual Speech Recognition Learners.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Large Language Models are Strong Audio-Visual Speech Recognition Learners

Reference 11

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MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Unresolved cited work

Reference 12

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

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Wavlm: Large-scale self-supervised pre-training for full stack speech processing

Reference 13

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This paper cites Mixtures of experts for audio-visual learning.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Mixtures of experts for audio-visual learning

Reference 14

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This paper cites Self-supervised learning with random-projection quantizer for speech recognition.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Self-supervised learning with random-projection quantizer for speech recognition

Reference 15

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This paper cites J., Kim, M., and Ro, Y.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition J., Kim, M., and Ro, Y

Reference 16

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This paper cites S., Nagrani, A., and Zisserman, A.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition S., Nagrani, A., and Zisserman, A

Reference 17

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This paper cites Unified scaling laws for routed language models.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Unified scaling laws for routed language models

Reference 18

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This paper cites Stablemoe: Stable routing strategy for mixture of experts.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Stablemoe: Stable routing strategy for mixture of experts

Reference 19

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This paper cites A study of dropout-induced modality bias on robustness to missing video frames for audio-visual speech recognition.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition A study of dropout-induced modality bias on robustness to missing video frames for audio-visual speech recognition

Reference 20

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This paper cites and Luettin, J.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition and Luettin, J

Reference 21

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This paper cites W., and Matt, P.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition W., and Matt, P

Reference 22

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This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity

Reference 23

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This paper cites Boosting speech recognition robustness to modality-distortion with contrast-augmented prompts.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Boosting speech recognition robustness to modality-distortion with contrast-augmented prompts

Reference 24

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This paper cites Conformer: Convolution-augmented transformer for speech recognition.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Conformer: Convolution-augmented transformer for speech recognition

Reference 25

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

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 26

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This paper cites Jointly learning visual and auditory speech representations from raw data.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Jointly learning visual and auditory speech representations from raw data

Reference 27

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This paper cites Braven: Improving self-supervised pre-training for visual and auditory speech recognition.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Braven: Improving self-supervised pre-training for visual and auditory speech recognition

Reference 28

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This paper cites XLAVS - R : Cross-lingual audio-visual speech representation learning for noise-robust speech perception.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition XLAVS - R : Cross-lingual audio-visual speech representation learning for noise-robust speech perception

Reference 29

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MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Unresolved cited work

Reference 30

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MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Unresolved cited work

Reference 31

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MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition and Shi, B

Reference 32

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MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition H., Lakhotia, K., Salakhutdinov, R., and Mohamed, A

Reference 33

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MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition N., Zhang, Y., and Beaufays, F

Reference 34

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MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Unresolved cited work

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MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Unresolved cited work

Reference 36

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MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Unresolved cited work

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MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition A., Jordan, M

Reference 38

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MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Mixtral of Experts

Reference 39

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MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Unresolved cited work

Reference 40

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MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Scaling Laws for Neural Language Models

Reference 41

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This paper cites Learning video temporal dynamics with cross-modal attention for robust audio-visual speech recognition.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Learning video temporal dynamics with cross-modal attention for robust audio-visual speech recognition

Reference 42

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MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Multi-task corrupted prediction for learning robust audio-visual speech representation

Reference 43

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This paper cites Adam: A Method for Stochastic Optimization.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Adam: A Method for Stochastic Optimization

Reference 44

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MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Moai: Mixture of all intelligence for large language and vision models

Reference 45

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This paper cites \ GS \ hard: Scaling giant models with conditional computation and automatic sharding.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition \ GS \ hard: Scaling giant models with conditional computation and automatic sharding

Reference 46

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This paper cites Unified cross-modal attention: Robust audio-visual speech recognition and beyond.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Unified cross-modal attention: Robust audio-visual speech recognition and beyond

Reference 47

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This paper cites Pace: Unified multi-modal dialogue pre-training with progressive and compositional experts.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Pace: Unified multi-modal dialogue pre-training with progressive and compositional experts

Reference 48

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This paper cites Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts

Reference 49

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This paper cites Av-data2vec: Self-supervised learning of audio-visual speech representations with contextualized target representations.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Av-data2vec: Self-supervised learning of audio-visual speech representations with contextualized target representations

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.750980Z

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This paper cites MoE-LLaVA: Mixture of Experts for Large Vision-Language Models.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition MoE-LLaVA: Mixture of Experts for Large Vision-Language Models

Reference 51

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This paper cites W., and Pantic, M.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition W., and Pantic, M

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.740438Z

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Observation decb22d6-5180-42cb-b35a-4c68ea23fd0b · outbound

This paper cites End-to-end audio-visual speech recognition with conformers.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition End-to-end audio-visual speech recognition with conformers

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.730261Z

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Observation b6e30b98-4524-45fd-ba64-55921ab1de61 · outbound

This paper cites Auto-avsr: Audio-visual speech recognition with automatic labels.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Auto-avsr: Audio-visual speech recognition with automatic labels

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.719069Z

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.

Observation 7a4dd371-89e0-49d0-8b75-82ee9dfb957c · outbound

This paper cites Recurrent neural network transducer for audio-visual speech recognition.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Recurrent neural network transducer for audio-visual speech recognition

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.707947Z

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.

Observation 40f518dc-ba49-4251-969c-5dbce41495e0 · outbound

This paper cites Mm1: methods, analysis and insights from multimodal llm pre-training.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Mm1: methods, analysis and insights from multimodal llm pre-training

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.696792Z

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.

Observation 736a4236-703c-4be2-8c3b-53dfb9d93e9c · outbound

This paper cites Multimodal contrastive learning with limoe: the language-image mixture of experts.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Multimodal contrastive learning with limoe: the language-image mixture of experts

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.686160Z

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.

Observation 262ab514-50ef-47a2-abb3-201a5b8f83c8 · outbound

This paper cites G., and Ogata, T.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition G., and Ogata, T

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.675558Z

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.

Observation a554eb4e-ae2a-4261-95fa-43ec6a0329ce · outbound

This paper cites Leveraging unimodal self-supervised learning for multimodal audio-visual speech recognition.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Leveraging unimodal self-supervised learning for multimodal audio-visual speech recognition

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.665127Z

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.

Observation 3a623aaa-0e13-431f-8564-fb3387ff6617 · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Bleu: a method for automatic evaluation of machine translation

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-08T12:46:12.179726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c91ae05-3531-44c0-99b7-4a1e6ee84503 · outbound

This paper cites A call for clarity in reporting bleu scores.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition A call for clarity in reporting bleu scores

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.648936Z

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.

Observation faf4f2ff-e926-49b8-9ebe-e85bfd014e25 · outbound

This paper cites Lipsound2: Self-supervised pre-training for lip-to-speech reconstruction and lip reading.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Lipsound2: Self-supervised pre-training for lip-to-speech reconstruction and lip reading

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.638468Z

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.

Observation 1b11b7af-4db4-4e2b-92e6-e9953ef6fad7 · outbound

This paper cites W., Xu, T., Brockman, G., McLeavey, C., and Sutskever, I.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition W., Xu, T., Brockman, G., McLeavey, C., and Sutskever, I

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-08T12:46:12.190741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e558eeb-03d6-4dde-9b12-1e0885aa2506 · outbound

This paper cites Learning from the master: Distilling cross-modal advanced knowledge for lip reading.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Learning from the master: Distilling cross-modal advanced knowledge for lip reading

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.622031Z

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.

Observation e5f9b8f4-3539-49df-ba88-92dbcfee486b · outbound

This paper cites wav2vec: Unsupervised pre-training for speech recognition.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition wav2vec: Unsupervised pre-training for speech recognition

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.611683Z

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.

Observation e6fe91de-707b-404d-b25d-68d2f3a1f931 · outbound

This paper cites H., Nagrani, A., and Schmid, C.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition H., Nagrani, A., and Schmid, C

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.600769Z

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.

Observation 93c99fbf-3002-4c1e-bd85-c855be4c7cd0 · outbound

This paper cites Outrageously large neural networks: The sparsely-gated mixture-of-experts layer.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Outrageously large neural networks: The sparsely-gated mixture-of-experts layer

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.589682Z

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.

Observation 698d2898-de93-452b-a09a-31664d927a91 · outbound

This paper cites Scaling vision-language models with sparse mixture of experts.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Scaling vision-language models with sparse mixture of experts

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.579332Z

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.

Observation 761244b3-694b-40ea-b43e-498b303e25b9 · outbound

This paper cites Learning audio-visual speech representation by masked multimodal cluster prediction.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Learning audio-visual speech representation by masked multimodal cluster prediction

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.567388Z

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.

Observation 6455672e-f8dc-4faa-beec-aee8ca7f209d · outbound

This paper cites Robust self-supervised audio-visual speech recognition.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Robust self-supervised audio-visual speech recognition

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.556400Z

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.

Observation e469726c-a996-4160-b4cf-4052afa9dfe9 · outbound

This paper cites MUSAN: A Music, Speech, and Noise Corpus.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition MUSAN: A Music, Speech, and Noise Corpus

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-08T12:46:12.219928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea26ca4a-a117-4a82-87d1-9e3eb8a279eb · outbound

This paper cites The diverse environments multi-channel acoustic noise database (demand): A database of multichannel environmental noise recordings.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition The diverse environments multi-channel acoustic noise database (demand): A database of multichannel environmental noise recordings

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-08T12:46:12.223984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70e6dd0a-b44f-498d-b5c3-5266d235f667 · outbound

This paper cites N., Kaiser, ., and Polosukhin, I.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition N., Kaiser, ., and Polosukhin, I

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-08T12:46:12.227915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 683256ca-aa77-47d4-9a5f-4f8c754714e0 · outbound

This paper cites T., and Li, H.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition T., and Li, H

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.534091Z

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.

Observation 1e95febc-e8b0-4589-b53d-916f1e2398be · outbound

This paper cites Language-routing mixture of experts for multilingual and code-switching speech recognition.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Language-routing mixture of experts for multilingual and code-switching speech recognition

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.524068Z

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.

Observation 555f1a1d-5da3-4299-9a20-b307e07dc4fe · outbound

This paper cites R., and Hayashi, T.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition R., and Hayashi, T

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.513677Z

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.

Observation 962a535d-9a14-443b-9c67-34f771193ca1 · outbound

This paper cites Robust audiovisual speech recognition models with mixture-of-experts.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Robust audiovisual speech recognition models with mixture-of-experts

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.503834Z

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.

Observation 3584682c-30ff-4622-9c96-728984916f11 · outbound

This paper cites Speechmoe: Scaling to large acoustic models with dynamic routing mixture of experts.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Speechmoe: Scaling to large acoustic models with dynamic routing mixture of experts

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.492396Z

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.

Observation d8f1c0d4-9dd2-4fcb-81c8-501a463e55d6 · outbound

This paper cites Speechmoe2: Mixture-of-experts model with improved routing.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Speechmoe2: Mixture-of-experts model with improved routing

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.477707Z

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.

Observation 08b33f54-e9a5-4b79-b0ed-562a83643f94 · outbound

This paper cites Visual hallucination elevates speech recognition.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Visual hallucination elevates speech recognition

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.464533Z

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.

Observation 5b13026c-fa99-4c0d-970f-b9f68f4aff78 · outbound

This paper cites Self-supervised audio-visual speech representations learning by multimodal self-distillation.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Self-supervised audio-visual speech representations learning by multimodal self-distillation

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.453215Z

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.

Observation 3515f5d7-0b53-4273-bafd-96cd12610c8b · outbound

This paper cites Uni-perceiver-moe: Learning sparse generalist models with conditional moes.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Uni-perceiver-moe: Learning sparse generalist models with conditional moes

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.440286Z

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.

Observation 0a2625e8-12f8-4dad-8059-86cde6accefa · outbound

This paper cites Vatlm: Visual-audio-text pre-training with unified masked prediction for speech representation learning.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Vatlm: Visual-audio-text pre-training with unified masked prediction for speech representation learning

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:46:12.425112Z

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.

Observation b3cea8a1-ca54-4a16-b6fc-d1420e753587 · outbound

This paper cites ST-MoE: Designing Stable and Transferable Sparse Expert Models.

MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition ST-MoE: Designing Stable and Transferable Sparse Expert Models

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-08T12:46:12.269019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Reference resolution

Outbound references

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