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Paper Citation Record · LEDGER

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression

As of 11 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 0 inbound Pith citation observations for arXiv:2606.01608.

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

pith.paper-citation-record.v1
2606.01608 v1

Coverage vector

measured 69 of 69 reference resolution

Typed states for the displayed outbound observations.

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measured 69 of 69 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

69 of 69 outbound references displayed

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  • verified fuzzy0
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External citation measurements

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Outbound references

Observation d27fe8e0-4d25-4370-92b8-66eccc75b0a1 · outbound

This paper cites The jpeg still picture compression standard,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression The jpeg still picture compression standard,

Reference 1

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Observation 253f3761-6ada-4a9c-966a-f97ab6faeccd · outbound

This paper cites Overview of the versatile video coding (vvc) standard and its applications,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Overview of the versatile video coding (vvc) standard and its applications,

Reference 2

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Observation e64ed37d-4bab-45c5-8189-7060043ba6cb · outbound

This paper cites Learned image compression with mixed transformer-cnn architectures,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Learned image compression with mixed transformer-cnn architectures,

Reference 3

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Observation 6a674cb6-9acb-45d6-b2dc-ea868fe11c8b · outbound

This paper cites Frequency-Aware Transformer for Learned Image Compression.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Frequency-Aware Transformer for Learned Image Compression

Reference 4

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Observation bcafc239-2ee0-40b7-a67e-d841b8e0c5e7 · outbound

This paper cites Improving statistical fidelity for neural image compression with im- plicit local likelihood models,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Improving statistical fidelity for neural image compression with im- plicit local likelihood models,

Reference 5

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Observation ca7c7b2d-f667-49b7-9878-d807503902e6 · outbound

This paper cites Generative latent coding for ultra-low bitrate image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Generative latent coding for ultra-low bitrate image compression,

Reference 6

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Observation ce8d793e-d3e7-4133-9573-ddc099f5bf9c · outbound

This paper cites A lightweight model for perceptual image compression via implicit priors,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression A lightweight model for perceptual image compression via implicit priors,

Reference 7

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Observation 3c4566fe-b386-4afb-97ab-d8f5f0932cbc · outbound

This paper cites Towards extreme image compression with latent feature guidance and diffusion prior,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Towards extreme image compression with latent feature guidance and diffusion prior,

Reference 8

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Observation 317efbec-f80e-4546-8b89-f4910e183159 · outbound

This paper cites Rdeic: Accelerating diffusion-based extreme image compression with relay residual diffu- sion,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Rdeic: Accelerating diffusion-based extreme image compression with relay residual diffu- sion,

Reference 9

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Observation a7eea561-b5d3-4066-98f5-7c5cfd74e803 · outbound

This paper cites Extremely low-bitrate image compression semantically disentangled by lmms from a human perception perspective.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Extremely low-bitrate image compression semantically disentangled by lmms from a human perception perspective

Reference 10

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Observation c0db3d32-8548-4844-a747-8f2008c5b560 · outbound

This paper cites High- resolution image synthesis with latent diffusion models,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression High- resolution image synthesis with latent diffusion models,

Reference 11

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Observation 23a99c4a-1cb4-48a8-97de-cd595b08ed09 · outbound

This paper cites StableCodec: Taming One-Step Diffusion for Extreme Image Compression.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression StableCodec: Taming One-Step Diffusion for Extreme Image Compression

Reference 12

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Observation 241ff807-729a-4db5-b8cd-fdcac56d7b1f · outbound

This paper cites Oscar: One-step diffusion codec across multiple bit-rates.arXiv preprint arXiv:2505.16091.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Oscar: One-step diffusion codec across multiple bit-rates.arXiv preprint arXiv:2505.16091

Reference 13

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Observation fc368415-e583-4a6f-b9f6-c6f6a684df35 · outbound

This paper cites Steering one-step diffusion model with fidelity-rich decoder for fast image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Steering one-step diffusion model with fidelity-rich decoder for fast image compression,

Reference 14

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Observation 54946960-e42d-4a93-85de-43eda99744b5 · outbound

This paper cites Diffpc: Diffusion-based high perceptual fidelity image compression with semantic refinement,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Diffpc: Diffusion-based high perceptual fidelity image compression with semantic refinement,

Reference 15

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Observation 3b351999-b230-45ba-8f05-a0dc32570734 · outbound

This paper cites Elic: Efficient learned image compression with unevenly grouped space- channel contextual adaptive coding,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Elic: Efficient learned image compression with unevenly grouped space- channel contextual adaptive coding,

Reference 16

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Observation 49e9de87-4da9-4c25-bdf0-350a0c41fba0 · outbound

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Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Unresolved cited work

Reference 17

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Observation 1b4eab50-e14e-447d-a677-42bd33cbbe47 · outbound

This paper cites End-to-end optimized image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression End-to-end optimized image compression,

Reference 18

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Observation 06ea9d8d-ad59-4a38-9dbb-6d09f0f79193 · outbound

This paper cites Learned image com- pression with discretized gaussian mixture likelihoods and attention modules,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Learned image com- pression with discretized gaussian mixture likelihoods and attention modules,

Reference 19

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Observation 22ada246-6a06-4c25-8451-2df1791b6d8a · outbound

This paper cites Enhanced invertible encoding for learned image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Enhanced invertible encoding for learned image compression,

Reference 20

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Observation 7f40a828-3f37-40b1-8102-b36ee1a3b480 · outbound

This paper cites The devil is in the details: Window- based attention for image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression The devil is in the details: Window- based attention for image compression,

Reference 21

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Observation 879b6b06-9a64-4585-92f2-d500d2fbc5f4 · outbound

This paper cites Llic: Large receptive field transform coding with adaptive weights for learned image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Llic: Large receptive field transform coding with adaptive weights for learned image compression,

Reference 22

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Observation fc262100-b0ae-4b8c-85dd-b324f644ae04 · outbound

This paper cites Mambaic: State space models for high-performance learned image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Mambaic: State space models for high-performance learned image compression,

Reference 23

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Observation 6c691b1d-45a0-456f-a9ca-e70f059b66ff · outbound

This paper cites Linear attention modeling for learned image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Linear attention modeling for learned image compression,

Reference 24

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Observation 4eff3ee2-cf0f-46da-a26e-26aa9ccd8f00 · outbound

This paper cites Joint autoregressive and hierarchical priors for learned image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Joint autoregressive and hierarchical priors for learned image compression,

Reference 25

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Observation f48aca39-12db-407e-a672-d3eb8cd0cd15 · outbound

This paper cites Causal contextual prediction for learned image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Causal contextual prediction for learned image compression,

Reference 26

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Observation 6fb12817-7da0-4b51-9977-445f9a0fb9c1 · outbound

This paper cites Checkerboard context model for efficient learned image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Checkerboard context model for efficient learned image compression,

Reference 27

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Observation 52fa6259-7823-4e6d-98a1-8ceee4034714 · outbound

This paper cites Channel-wise autoregressive entropy models for learned image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Channel-wise autoregressive entropy models for learned image compression,

Reference 28

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Observation 9b964e49-f752-4958-8845-0ee7e214438d · outbound

This paper cites Mlic: Multi- reference entropy model for learned image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Mlic: Multi- reference entropy model for learned image compression,

Reference 29

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Observation 32bc0c43-ec5e-4fae-aa71-f89a8804d05b · outbound

This paper cites Mlic++: Linear com- plexity multi-reference entropy modeling for learned image compres- sion,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Mlic++: Linear com- plexity multi-reference entropy modeling for learned image compres- sion,

Reference 30

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Observation 44ee7535-87fd-45b3-afd5-99a8924cfcaa · outbound

This paper cites Learned image compression with dictionary-based entropy model,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Learned image compression with dictionary-based entropy model,

Reference 31

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Observation 1d9d106e-df44-40dd-8d82-900363d35ce1 · outbound

This paper cites Rethinking lossy compression: The rate- distortion-perception tradeoff,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Rethinking lossy compression: The rate- distortion-perception tradeoff,

Reference 32

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Observation 211e397a-d374-4534-8b5d-8143cf9cdd14 · outbound

This paper cites High- fidelity generative image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression High- fidelity generative image compression,

Reference 33

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Observation a86cb5ed-0a56-4814-a230-c1957203ad5a · outbound

This paper cites Multi-realism image compression with a conditional generator,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Multi-realism image compression with a conditional generator,

Reference 34

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Observation fd9a9b10-ecdd-442b-9709-33b9c0c7f9c0 · outbound

This paper cites Neural Image Compression with Text-guided Encoding for both Pixel-level and Perceptual Fidelity.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Neural Image Compression with Text-guided Encoding for both Pixel-level and Perceptual Fidelity

Reference 35

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Source-reported events for the cited work

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Observation 4ab94d92-5e72-4d01-a39b-d8c984f38df4 · outbound

This paper cites A Residual Diffusion Model for High Perceptual Quality Codec Augmentation.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression A Residual Diffusion Model for High Perceptual Quality Codec Augmentation

Reference 36

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Observation c083ad0a-9861-4c85-8172-ea2237a11eeb · outbound

This paper cites Consistency guided dif- fusion model with neural syntax for perceptual image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Consistency guided dif- fusion model with neural syntax for perceptual image compression,

Reference 37

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:844013ee6a7e1c61f11bf34e2724b153b14bb29ba161892d721412af1a3e18fa

Observation a6c8af94-620b-434b-9845-c0de5625b34c · outbound

This paper cites Controllable distortion-perception tradeoff through latent diffusion for neural image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Controllable distortion-perception tradeoff through latent diffusion for neural image compression,

Reference 38

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:4d272a6819b7f06293bb14fa059852279bfb1c9d4fa23afda6f246dd5ad581ec

Observation ece31cb5-d27a-46ee-b55f-152d8ab4fab9 · outbound

This paper cites Lossy image compression with conditional diffusion models,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Lossy image compression with conditional diffusion models,

Reference 39

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:d27ff0bdfe11c52c23537ba6533498ae98cfb10a5a6638a55613f9dbcffb5dd4

Observation 55897b96-c527-490e-9a3b-e1ac006de1e2 · outbound

This paper cites Correcting diffusion-based perceptual image compression with privileged end-to-end decoder,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Correcting diffusion-based perceptual image compression with privileged end-to-end decoder,

Reference 40

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:2a1fc0aadf0f23284ae631421124f836d8aea775aac1d0a7b88fbc3800ad29cf

Observation 39284622-9b07-40a7-a4b3-09d9cc24e333 · outbound

This paper cites Multi-modality deep network for extreme learned image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Multi-modality deep network for extreme learned image compression,

Reference 41

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:7035886ae547ac5b2a1945bc1c24a8656aac7704f1ec8dd30753e2c23c77c6a9

Observation be412547-4b2c-4bda-91e1-c132ac0eb989 · outbound

This paper cites Towards image compression with perfect realism at ultra-low bitrates,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Towards image compression with perfect realism at ultra-low bitrates,

Reference 42

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:dd2b7cdc928157dd096c23552650b4e8b5303e6ef65d8fb04dc30140b46ffc51

Observation ad09327d-c9e1-4aea-85c3-9b85a307e303 · outbound

This paper cites Text + Sketch: Image Compression at Ultra Low Rates.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Text + Sketch: Image Compression at Ultra Low Rates

Reference 43

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metadata mismatch
arxiv_id, observed 2026-07-01T22:06:15.727063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:efbbaf7288bdadc9a706fa33ba2519b18f3db77cfa64acbab2c6adf69a6af990

Observation 72dc8396-a5f3-4e9b-ae2c-c7f79a819f92 · outbound

This paper cites Misc: Ultra-low bitrate image semantic compression driven by large multimodal model,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Misc: Ultra-low bitrate image semantic compression driven by large multimodal model,

Reference 44

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:74ee8eaa0a9ec3024358fdae4b1c859b9c254334003f678d1aa45cb462d4ed47

Observation a2c767dc-fe28-44ee-8f1c-a166b024b21a · outbound

This paper cites Linearly transformed color guide for low- bitrate diffusion based image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Linearly transformed color guide for low- bitrate diffusion based image compression,

Reference 45

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:4ed667a3385d3ce49ecc3fca09970e1f9b45eefa9ef4c58072f52c2f69a77113

Observation ebf2ef11-e3d2-4c60-9d34-272a409b6106 · outbound

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

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Extreme image compression using fine-tuned vqgans,

Reference 46

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:4342151b50110c5d5aa3893bd41702986e8badc926fb1952e47e58ee23e437d0

Observation 7355e372-f3ce-43bb-aba2-70f10c5c4385 · outbound

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

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Taming transformers for high- resolution image synthesis,

Reference 47

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:52ab7fcc91d62bfe5fdff3a0c86df85999274254e2f94b28e9c3f5643f967f56

Observation fba95a25-7f3a-40a5-9a3c-0f4145733f6b · outbound

This paper cites Toward extreme image rescaling with generative prior and invertible prior,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Toward extreme image rescaling with generative prior and invertible prior,

Reference 48

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:1fe226f0195b4af01b21c0858aecf071c5ab6e35b67fb9cf25664a3344db4bfc

Observation 7efc9a51-58f8-4b8f-97a9-ce6540534125 · outbound

This paper cites Hybridflow: Infusing continuity into masked codebook for extreme low-bitrate image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Hybridflow: Infusing continuity into masked codebook for extreme low-bitrate image compression,

Reference 49

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:c426a9ceb10fe757e95e8c4ce1ae43270e8f6f35b6dcbac50706484e58f68909

Observation 0c1675da-2a0b-4135-b90f-37e79b169277 · outbound

This paper cites Dlf: Extreme image compression with dual- generative latent fusion.arXiv preprint arXiv:2503.01428.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Dlf: Extreme image compression with dual- generative latent fusion.arXiv preprint arXiv:2503.01428

Reference 50

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verified exact
arxiv_id, observed 2026-07-01T22:06:15.709560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:9eeedd85812b8a68f93e16019bcb25fab6ff70b3a5f9c1e5384ae1cd4af61528

Observation 05e777d6-03c3-46bc-9517-656b615dc619 · outbound

This paper cites Lmm-driven semantic image-text coding for ultra low-bitrate learned image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Lmm-driven semantic image-text coding for ultra low-bitrate learned image compression,

Reference 51

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:95e971fc056d1a1e77f61b5fc7ab7e68783f65b5bc6577ea157d05dea84d1e7b

Observation 678bf367-797b-4bde-ae59-0f994ad3ab86 · outbound

This paper cites Ultra Lowrate Image Compression with Semantic Residual Coding and Compression-aware Diffusion.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Ultra Lowrate Image Compression with Semantic Residual Coding and Compression-aware Diffusion

Reference 52

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verified exact
arxiv_id, observed 2026-07-01T22:06:15.716991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:eb5df39ef62765f36317b54680561e997fd49db2e5f71823b4c57e86b7b780aa

Observation 92c79409-4f9e-4871-9c41-58dc9431fbf1 · outbound

This paper cites Diffo: Single-step diffusion for image compression at ultra-low bi- trates.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Diffo: Single-step diffusion for image compression at ultra-low bi- trates

Reference 53

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verified exact
arxiv_id, observed 2026-07-01T22:06:15.720507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:afa570b1b74169414e30585965c3014bf0b893f0742710e05981bd737b177a65

Observation 2b826c3c-639f-40dd-a032-2676c9374ce3 · outbound

This paper cites Adversarial diffusion distillation,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Adversarial diffusion distillation,

Reference 54

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:03341b09f3854c882c177ef114ad934b4626cffcd9e575f804576b772f6273e6

Observation 6b1c5539-376f-4ffb-9861-4618e89a08ce · outbound

This paper cites Inceptionnext: When inception meets convnext,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Inceptionnext: When inception meets convnext,

Reference 55

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:250584ae2850cc76afa457c364236a0c8b9241b8e624407bf49e5001b34e3f8e

Observation 33e02283-e45c-4f79-ba23-46876e635f07 · outbound

This paper cites Mambaout: Do we really need mamba for vision?.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Mambaout: Do we really need mamba for vision?

Reference 56

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:292b3223cc59baf7b7b2711658104b2b3fc1e2c61cdb4344d89d447564abc1f8

Observation 4ad48ef2-b57a-4793-9497-f2f3aec70935 · outbound

This paper cites Lsdir: A large scale dataset for image restoration,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Lsdir: A large scale dataset for image restoration,

Reference 57

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:a85e68a96e79391384f2f010c489146a2383f395ae7501b82b1ad913050ef01a

Observation 618224cf-8ba6-46c8-811b-97c31fa3f13c · outbound

This paper cites A Unified End-to-End Framework for Efficient Deep Image Compression.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression A Unified End-to-End Framework for Efficient Deep Image Compression

Reference 58

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verified exact
arxiv_id, observed 2026-07-01T22:06:15.680878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:87360025c7ebcb1d6dd1c561d542b877b72c4899ec09fb105ee84c911e64f3f6

Observation 78cfc2ed-a394-41a9-95f0-fa3fa2e7d890 · outbound

This paper cites Kodak photocd dataset,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Kodak photocd dataset,

Reference 59

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:323c343b69dcd7e7ceb66b8ce5d7bc7adf104808a7a1032ad14c1cb1b410b4ed

Observation 26196361-5be1-454d-b90d-6bf79f17b72e · outbound

This paper cites Clic 2020: Challenge on learned image compression,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Clic 2020: Challenge on learned image compression,

Reference 60

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:b0e38e9111e2c9d0bdf4b99d13da667b7468a98bba432eb444b792ba27d4784b

Observation 799ca3e8-9b0f-413e-8c73-d7b93bf7eb0b · outbound

This paper cites Testimages: a large-scale archive for testing visual devices and basic image processing algorithms.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Testimages: a large-scale archive for testing visual devices and basic image processing algorithms

Reference 61

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:29d058442fc2fbdd6935604a0c5dc3ac9df8503cba9357d3cba4ee98b5108d1b

Observation d4b6c31f-73a8-4251-ad52-113bd4864c81 · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression The unreasonable effectiveness of deep features as a perceptual metric,

Reference 62

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:f4fa3a34221ab0eed66c14a7de57089f9111207a3e0688bfa43ec6006ad2859a

Observation 4ce3db0a-f71b-4d76-a6c9-593e662b13d7 · outbound

This paper cites Image quality assessment: Unifying structure and texture similarity,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Image quality assessment: Unifying structure and texture similarity,

Reference 63

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:32ac878be40aba6f70b9d0bb99f7d4653daa43d24f837166d04d8f49c1ff1026

Observation 33a5773d-af5c-453d-9371-dc693c0535df · outbound

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

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Gans trained by a two time-scale update rule converge to a local nash equilibrium,

Reference 64

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:4f153d4e5ea26d288653ac4bca7a2a347d1f3be4d8bf74c8e1628062d1af5346

Observation f6201adc-57c1-4952-8652-5f7457828e0c · outbound

This paper cites Demystifying MMD GANs.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Demystifying MMD GANs

Reference 65

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verified exact
local_arxiv, observed 2026-07-01T22:06:15.676781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:b024ba7fea35f2372ba19d347613a731395455c4ca50267d6af1f5cd38fd403b

Observation c9de1505-ab11-40d8-928d-556da36c55a3 · outbound

This paper cites Multiscale structural similarity for image quality assessment,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Multiscale structural similarity for image quality assessment,

Reference 66

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:8a1a1b25f21ec721e5d66909fa2761bbced06d30cbab10f085f9a7c87614e107

Observation b618748c-7d67-4b5b-a837-3ba088abd3ce · outbound

This paper cites Lora: Low-rank adaptation of large language models.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Lora: Low-rank adaptation of large language models

Reference 67

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source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:bc29af6c4ae25acdcb15ff497a377aafd306b7ace39d4de0e2b310292fcab31f

Observation 897d4ae6-89d2-4d10-ae8f-2c7cf4bf6af3 · outbound

This paper cites Dinov2: Learning robust visual features without supervision,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Dinov2: Learning robust visual features without supervision,

Reference 68

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:d32f741ce32f2a270f33a164638bb3e692214d21a525f9722b32e7b2ad74417b

Observation 46260453-d63f-4c1b-bd29-a2a4e7a90d94 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression Learning transferable visual models from natural language supervision,

Reference 69

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T15:51:24.936264Z digest=sha256:2c0a963c74a5c20221f137539f051424a59e4d9ebb3276b29b7df76ba47fd2a5

Pith citing papers

No inbound Pith citation observations are available.