LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency | Paper Citation Record

Observation 0750206d-f5d6-4797-9e1b-012b09ec0705 · outbound

This paper cites Implementation Challenges and Opportunities in Beyond-5G and 6G Communication,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Implementation Challenges and Opportunities in Beyond-5G and 6G Communication,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.934898Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c2f6ef41-a74c-4de6-a523-402ddb335dbd · outbound

This paper cites A mathematical theory of communication,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency A mathematical theory of communication,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.918754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a88c2b2d-e396-49d9-a12c-5283ad5dbaeb · outbound

This paper cites Diff-GO: Diffusion Goal-Oriented Communications to Achieve Ultra-High Spectrum Efficiency.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Diff-GO: Diffusion Goal-Oriented Communications to Achieve Ultra-High Spectrum Efficiency

Reference 3

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Source-reported events for the cited work

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Observation 49aa06a2-28c8-4a58-91c0-7f54c05664dc · outbound

This paper cites GO+: An Efficient Diffusion Goal-Oriented Communication System with Local Feedback,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency GO+: An Efficient Diffusion Goal-Oriented Communication System with Local Feedback,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.900331Z

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Observation 5514d62e-a4d7-48b0-9863-16a9e90dd386 · outbound

This paper cites 6G networks: Beyond Shannon towards semantic and goal-oriented communications,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency 6G networks: Beyond Shannon towards semantic and goal-oriented communications,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.883614Z

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Observation caa7d754-19e9-4682-a39b-c1e62b47291a · outbound

This paper cites Diff-GO n: Enhancing Diffusion Models for Goal-Oriented Communications,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Diff-GO n: Enhancing Diffusion Models for Goal-Oriented Communications,

Reference 6

Resolution: verified exact; raw_fallback, observed 2026-08-11T13:06:24.061329Z

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Observation cf529bd9-e291-4a4a-a8fb-78baca517bc9 · outbound

This paper cites Taming transformers for high- resolution image synthesis.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Taming transformers for high- resolution image synthesis

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.865256Z

Source-reported events for the cited work

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Observation 595cf7dd-f78b-4cbd-9db5-6da71455072f · outbound

This paper cites Generative Semantic Communication: Diffusion Models Beyond Bit Recovery.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Generative Semantic Communication: Diffusion Models Beyond Bit Recovery

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T13:06:23.489847Z

Source-reported events for the cited work

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Observation 144f84b4-2de5-4155-afb2-da4eb99f7266 · outbound

This paper cites Semantic-preserving image coding based on conditional diffusion models.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Semantic-preserving image coding based on conditional diffusion models

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.847359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e5853c01-a640-4051-be14-6202d788fa96 · outbound

This paper cites Robust semantic communications with masked vq-vae enabled codebook.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Robust semantic communications with masked vq-vae enabled codebook

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.828602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6c904c5a-8f21-4de6-9634-54784977d0c5 · outbound

This paper cites Autoencoder-based semantic communication systems with relay channels.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Autoencoder-based semantic communication systems with relay channels

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.810318Z

Source-reported events for the cited work

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Observation ef303e86-a61c-4247-94dd-88861226797c · outbound

This paper cites Communication beyond transmitting bits: Semantics-guided source and channel coding.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Communication beyond transmitting bits: Semantics-guided source and channel coding

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.792485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bd6e10d8-170b-40a0-abb0-dbd37d9689da · outbound

This paper cites Neural discrete representation learning,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Neural discrete representation learning,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.773748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f98f79bb-a36e-4c18-9264-d335d6e10e28 · outbound

This paper cites A theory of goal-oriented communication,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency A theory of goal-oriented communication,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.745297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6840c0ab-c313-40ea-88c9-d0dae5a13853 · outbound

This paper cites Deep learning enabled semantic communications with speech recognition and synthesis,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Deep learning enabled semantic communications with speech recognition and synthesis,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.724998Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 348a1f2c-1ba0-46fb-b861-023efdef7885 · outbound

This paper cites Rethinking modern communication from semantic coding to semantic communication,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Rethinking modern communication from semantic coding to semantic communication,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.705791Z

Source-reported events for the cited work

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Observation f1716def-3d9c-4ff6-8739-8f23828af085 · outbound

This paper cites A lite distributed semantic communication system for internet of things,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency A lite distributed semantic communication system for internet of things,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.687222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d4767aef-8659-45f7-abf7-91adf57a2360 · outbound

This paper cites Multimodal semantic communication accelerated bidirectional caching for 6G mec.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Multimodal semantic communication accelerated bidirectional caching for 6G mec

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.666557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f444d32b-0729-4b9d-95ac-796b3938ff5e · outbound

This paper cites A unified multi- task semantic communication system for multimodal data,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency A unified multi- task semantic communication system for multimodal data,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.648415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 11f6034d-ac51-4448-a9f5-9c8ca5877de2 · outbound

This paper cites Large AI Model Empowered Multimodal Semantic Communications.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Large AI Model Empowered Multimodal Semantic Communications

Reference 20

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Source-reported events for the cited work

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Observation 910dee3f-3a01-458c-8e10-cd10c59d4a99 · outbound

This paper cites Denoising diffusion probabilistic models,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Denoising diffusion probabilistic models,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T13:06:23.565658Z

Source-reported events for the cited work

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Observation 8c05a76d-41e9-4aec-995c-a62196ab7e6a · outbound

This paper cites Taming transformers for high- resolution image synthesis,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Taming transformers for high- resolution image synthesis,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.617198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7aaa77b6-90fa-48f4-93e2-0c3be3f83909 · outbound

This paper cites Blip-2: Bootstrapping language- image pre-training with frozen image encoders and large language models.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Blip-2: Bootstrapping language- image pre-training with frozen image encoders and large language models

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.597755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 78dd6fb8-5968-4c0b-9d58-688e50b728f4 · outbound

This paper cites A novel sampling scheme for text-and image-conditional image synthesis in quantized latent spaces.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency A novel sampling scheme for text-and image-conditional image synthesis in quantized latent spaces

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.579369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 357e4042-b9a7-4455-80bd-1ae1377ad3cc · outbound

This paper cites Xue et al., ‘Byt5: Towards a token-free future with pre-trained byte- to-byte models’, Transactions of the Association for Computational Linguistics, vol.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Xue et al., ‘Byt5: Towards a token-free future with pre-trained byte- to-byte models’, Transactions of the Association for Computational Linguistics, vol

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.561899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 08418934-6e64-46bd-b96d-2720b2c5feea · outbound

This paper cites Radford et al., ‘Learning transferable visual models from natural language supervision’, in International conference on machine learning, 2021, pp.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Radford et al., ‘Learning transferable visual models from natural language supervision’, in International conference on machine learning, 2021, pp

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.545131Z

Source-reported events for the cited work

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Observation 7f62756a-4864-4a13-8025-a182ff6bce26 · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency The cityscapes dataset for semantic urban scene understanding,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.529317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6acb96f9-1584-47d9-b553-f621f6f9180f · outbound

This paper cites From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.511267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 33c8001a-27ec-481f-82ee-35ab3329f40d · outbound

This paper cites Coco-stuff: Thing and stuff classes in context.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Coco-stuff: Thing and stuff classes in context

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.492553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 232a23d6-0984-4168-8a46-dba787adbda8 · outbound

This paper cites Microsoft coco: Common objects in context.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Microsoft coco: Common objects in context

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.474423Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e45b6b52-089a-4472-a553-4003fc244aab · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Gans trained by a two time-scale update rule converge to a local nash equilibrium,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.454739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation eb77b127-2586-4e9d-a479-c27186064148 · outbound

This paper cites Learned perceptual image enhancement,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Learned perceptual image enhancement,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.437246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation aa1a323a-9720-4971-bd8a-97014d729126 · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.420892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 17198fba-6670-4c47-9d38-cc40e3ef0c43 · outbound

This paper cites Retrieval-based spatially adaptive normalization for semantic image synthesis,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Retrieval-based spatially adaptive normalization for semantic image synthesis,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.401013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c30c3a98-22cf-4aac-bcd7-049ca8600a3e · outbound

This paper cites Learning to predict layout-to- image conditional convolutions for semantic image synthesis,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Learning to predict layout-to- image conditional convolutions for semantic image synthesis,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.384528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 35e4afd4-8c1f-4f71-a33f-f51b48b10c62 · outbound

This paper cites Semantically multi-modal image synthesis,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Semantically multi-modal image synthesis,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.365387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1bbf12a0-12dc-4445-9e53-a44881ce76db · outbound

This paper cites You Only Need Adversarial Supervision for Semantic Image Synthesis.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency You Only Need Adversarial Supervision for Semantic Image Synthesis

Reference 37

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Source-reported events for the cited work

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Observation b6d0adec-c4c5-4309-861f-7d1f30620a00 · outbound

This paper cites Semantic image synthesis via diffusion models,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Semantic image synthesis via diffusion models,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-11T13:06:23.678820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d819e72-92c2-42f8-a0fa-642d29b5f472 · outbound

This paper cites Ranftl, K.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Ranftl, K

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.346710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9498d0cc-8e96-4d11-8d9f-18f1869143ac · outbound

This paper cites Detrs with collaborative hybrid as- signments training.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Detrs with collaborative hybrid as- signments training

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.329512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 72470121-75f4-4cd8-bf5e-49eabe162178 · outbound

This paper cites Extreme image compression using fine-tuned vqgans.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Extreme image compression using fine-tuned vqgans

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.309327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b367ffec-3cfe-4773-8f41-507dfd501c1b · outbound

This paper cites Dm-gan: Dynamic memory generative adversarial networks for textto-image synthesis,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Dm-gan: Dynamic memory generative adversarial networks for textto-image synthesis,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.289024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f484a730-0bd5-4c01-b7d0-51ebbbec2920 · outbound

This paper cites Cross-modal contrastive learning for text-to-image generation,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Cross-modal contrastive learning for text-to-image generation,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.262625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 998fa52c-4cb2-4a29-aa63-f3b918d7fa65 · outbound

This paper cites Df-gan: Deep fusion generative adversarial networks for text-to-image synthesis,.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Df-gan: Deep fusion generative adversarial networks for text-to-image synthesis,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.244992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c4b03fc2-0afa-483e-8a0e-109091d28cb0 · outbound

This paper cites Text to image generation with semantic-spatial aware gan.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Text to image generation with semantic-spatial aware gan

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.226442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 29ed364d-671c-41ff-851f-c90bf46b2391 · outbound

This paper cites Dse-gan: Dynamic semantic evolution generative adversarial network for text- to-image generation.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Dse-gan: Dynamic semantic evolution generative adversarial network for text- to-image generation

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.207790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6d27777f-3a97-4b4e-9126-0aa5875ece34 · outbound

This paper cites Vector quantized diffusion model for text-to-image synthesis.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Vector quantized diffusion model for text-to-image synthesis

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.186550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 82289858-65ba-4d97-b6a6-5cadd958d80e · outbound

This paper cites Not all image regions matter: Masked vector quantization for autoregressive image genera- tion.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Not all image regions matter: Masked vector quantization for autoregressive image genera- tion

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.169533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8c8076ff-a9d7-4ddc-a250-47a1a4fa5df5 · outbound

This paper cites Lapidoth, ”The performance of convolutional codes on the block erasure channel using various finite interleaving techniques,” in IEEE Transactions on Information Theory, vol.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Lapidoth, ”The performance of convolutional codes on the block erasure channel using various finite interleaving techniques,” in IEEE Transactions on Information Theory, vol

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:06:24.150505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 31ad51e8-6451-4adc-88b7-116077300cb9 · outbound

This paper cites an unresolved cited work.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Unresolved cited work

Reference 50

Resolution: unresolved; raw_fallback, observed 2026-08-11T13:06:24.129339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a94ab4fd-6826-4cbc-aca6-88e53a1d025b · outbound

This paper cites an unresolved cited work.

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency Unresolved cited work

Reference 51

Resolution: unresolved; raw_fallback, observed 2026-08-11T13:06:24.109447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers