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Paper Citation Record · LEDGER

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient

As of 19 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 5 inbound Pith citation observations for arXiv:2411.17787.

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

pith.paper-citation-record.v1
2411.17787 v1

Coverage vector

measured 75 of 75 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:06:01.218497Z

measured 80 of 80 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:16:12.670870Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T21:27:24.413629Z

Reference resolution

75 of 75 outbound references displayed

  • verified exact0
  • verified fuzzy9
  • unresolved66
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7ea29251-8ceb-4bc7-9483-24017ad2b1ac · outbound

This paper cites Qwen Technical Report.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Qwen Technical Report

Reference 1

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Observation 7f70426b-d403-41bd-964b-26cdd5770f88 · outbound

This paper cites Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models

Reference 2

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source=pdf_text observed=2026-08-12T12:06:00.827844Z digest=sha256:6c11f44cafd6391723fc1d575151f19b496ba96815c02f4044d5b047f8a643e7

Observation 2e87246e-1877-486a-8275-c514bac2883a · outbound

This paper cites Maskgit: Masked generative image transformer.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Maskgit: Masked generative image transformer

Reference 3

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source=pdf_text observed=2026-08-12T12:06:00.833154Z digest=sha256:994757f8008bb52896273f9013711aad13f793f5c2141467ed18fe70cbab851c

Observation 71e83295-7227-4267-80ba-8d47134cb028 · outbound

This paper cites Generative pre- training from pixels.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Generative pre- training from pixels

Reference 4

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source=pdf_text observed=2026-08-12T12:06:00.838014Z digest=sha256:53c4b27d2fdb9ba34ac0b059ce506540a42f57956a8a1ad2239f4125a5947bbf

Observation 07163891-1d53-4c65-8e23-d2d1df601bf9 · outbound

This paper cites SlimSAM: 0.1% Data Makes Segment Anything Slim.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient SlimSAM: 0.1% Data Makes Segment Anything Slim

Reference 5

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Observation 0ff93a30-106a-42d3-9bfb-0da021dcda20 · outbound

This paper cites AsyncDiff: Parallelizing Diffusion Models by Asynchronous Denoising.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient AsyncDiff: Parallelizing Diffusion Models by Asynchronous Denoising

Reference 6

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source=pdf_text observed=2026-08-12T12:06:00.847855Z digest=sha256:91714612704b530e8287d196136b7ff80336da1abdb79e02b54f46ffa431bf5a

Observation b255cd6f-5e4a-4a27-b839-cae890bd3df3 · outbound

This paper cites Flashattention: Fast and memory-efficient exact at- tention with io-awareness.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Flashattention: Fast and memory-efficient exact at- tention with io-awareness

Reference 7

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source=pdf_text observed=2026-08-12T12:06:00.853426Z digest=sha256:4a602b6eeeee11d73447fcef49403f7cf597b03187a7b1bfff9483db484cce96

Observation d05f2834-3bc5-4ee3-a62c-5de7225b2401 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Imagenet: A large-scale hierarchical image database

Reference 8

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation ad474c54-9b9d-4d05-b4a7-2226f1128509 · outbound

This paper cites The Llama 3 Herd of Models.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient The Llama 3 Herd of Models

Reference 9

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source=pdf_text observed=2026-08-12T12:06:00.863630Z digest=sha256:337ff7cca9e187eee81231c47aa654eab9f393a13bf59f1703dd176c5bb1fc90

Observation effbbf50-814c-4867-8d74-b146ca37b589 · outbound

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

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Taming transformers for high-resolution image synthesis

Reference 10

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source=pdf_text observed=2026-08-12T12:06:00.869652Z digest=sha256:6a93962926e95d65a75bf571eeeb8e922c1c0af3123117eb359bbd8567995ba6

Observation 85561da2-3013-465f-bf78-68612848d9b8 · outbound

This paper cites Depgraph: Towards any structural pruning.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Depgraph: Towards any structural pruning

Reference 11

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source=pdf_text observed=2026-08-12T12:06:00.874719Z digest=sha256:0dcd4fde8de5718bc77b0722c633e9a4b68c8bd14d60f1b6b19d1762ae5f083e

Observation 876f2246-19bd-4c0d-9aaf-b73e3b6bef16 · outbound

This paper cites Structural pruning for diffusion models.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Structural pruning for diffusion models

Reference 12

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source=pdf_text observed=2026-08-12T12:06:00.880154Z digest=sha256:156c20e6ebb33005ba7eba0f817b36ca1e8c64c1a7b7f184d50ef18c1572a97e

Observation 681b836e-5f51-49f2-ad08-f0a515b54c7e · outbound

This paper cites xDiT: an Inference Engine for Diffusion Transformers (DiTs) with Massive Parallelism.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient xDiT: an Inference Engine for Diffusion Transformers (DiTs) with Massive Parallelism

Reference 13

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source=pdf_text observed=2026-08-12T12:06:00.885322Z digest=sha256:70a4566ff158e7e7b0a5cf392a474b4cfd573a9c48b95da5e15f0dad72e182c3

Observation 56c81c6e-0184-479d-b203-e22583c26bf1 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 14

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source=pdf_text observed=2026-08-12T12:06:00.891448Z digest=sha256:6e30160c3efab5abdf51feb24c2e9bfeec4db1f08337da1a9059d55f21f8faed

Observation 04b1d529-1278-43eb-9edf-9e6885249631 · outbound

This paper cites DART: Denoising Autoregressive Transformer for Scalable Text-to-Image Generation.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient DART: Denoising Autoregressive Transformer for Scalable Text-to-Image Generation

Reference 15

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source=pdf_text observed=2026-08-12T12:06:00.896175Z digest=sha256:184b37e68db10d860c9f26a33d8a1f0fd70db2a7e9c91ef62103177c9b6dfe74

Observation e26eb48c-256f-4f3f-b92f-6e197cea0515 · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 16

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Observation faeb81e8-b07b-401b-b72b-c7fbe3f4c9c3 · outbound

This paper cites A survey on vision transformer.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient A survey on vision transformer

Reference 17

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source=pdf_text observed=2026-08-12T12:06:00.906700Z digest=sha256:92a03abc0504cdbf63dd9e65d4328c6eb6673044ea231601b2d70b8ca0a2c32c

Observation aea5fde9-22b4-426b-afa4-dcb4a7f7cdb0 · outbound

This paper cites MARS: Mixture of Auto-Regressive Models for Fine-grained Text-to-image Synthesis.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient MARS: Mixture of Auto-Regressive Models for Fine-grained Text-to-image Synthesis

Reference 18

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Observation fd101286-f93c-4ac9-803a-1d7afe8a3993 · outbound

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

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Gans trained by a two time-scale update rule converge to a local nash equilib- rium

Reference 19

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T12:06:00.916822Z digest=sha256:e04984c4ba954f76f1c4fce9e3e5ee2c5ddcc192442512b2a22418d4ff3624b8

Observation 9431f11b-68ff-4b2d-bd95-462f347d66d4 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Distilling the Knowledge in a Neural Network

Reference 20

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source=pdf_text observed=2026-08-12T12:06:00.921912Z digest=sha256:f69848df400f87509116508823fc9123a5abadbf69ec431e5e22cfe140d39a32

Observation e229b145-4c2a-4be7-931d-00b5d23d6f2a · outbound

This paper cites LANTERN: Accelerating Visual Autoregressive Models with Relaxed Speculative Decoding.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient LANTERN: Accelerating Visual Autoregressive Models with Relaxed Speculative Decoding

Reference 21

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Observation 49703b2c-e9c7-4583-97ec-1227c75e4e8c · outbound

This paper cites Musiq: Multi-scale image quality transformer.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Musiq: Multi-scale image quality transformer

Reference 22

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source=pdf_text observed=2026-08-12T12:06:00.934966Z digest=sha256:2351ccbc185c9f1c6390cced67afbceae19c678e60dcaf31a295e1ab06d4493f

Observation ce70e656-6ca7-4c16-aafa-84e41a25b0e3 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Adam: A Method for Stochastic Optimization

Reference 23

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Observation 748b54f3-78e3-4677-8ecb-66915a3cc3cb · outbound

This paper cites Scalable autoregressive image generation with mamba.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Scalable autoregressive image generation with mamba

Reference 24

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source=pdf_text observed=2026-08-12T12:06:00.945383Z digest=sha256:f467b6cb6b10c79ac07aae43e9486465495623d6dc7876c6b5c5f84af7f5ead6

Observation 23c86ecd-cd16-4d6b-8a31-9d907950cd73 · outbound

This paper cites Distri- fusion: Distributed parallel inference for high-resolution dif- fusion models.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Distri- fusion: Distributed parallel inference for high-resolution dif- fusion models

Reference 25

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source=pdf_text observed=2026-08-12T12:06:00.951191Z digest=sha256:7c1434091a4261cc21b2d1d4bfab5b141b756decaaea1ee65887fa0b815db8a2

Observation 135b9975-b704-41bd-8823-93db563fa360 · outbound

This paper cites Svdquant: Absorbing outliers by low- rank components for 4-bit diffusion models.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Svdquant: Absorbing outliers by low- rank components for 4-bit diffusion models

Reference 26

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source=pdf_text observed=2026-08-12T12:06:00.956595Z digest=sha256:4736760a0aea0fa7673f3c191bc6d4a84d3e0cefd621dfea97ee670a6f66d462

Observation 5a61af7e-7015-43e5-bacc-799298b594e8 · outbound

This paper cites Faster Diffusion: Rethinking the Role of the Encoder for Diffusion Model Inference.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Faster Diffusion: Rethinking the Role of the Encoder for Diffusion Model Inference

Reference 27

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source=pdf_text observed=2026-08-12T12:06:00.962546Z digest=sha256:8b5a8168d5d0c52ecb3609af2e3d54268b92cfd79e165e1bdbba43909dc8b26b

Observation 6383f43c-1806-4cda-8175-f9bb77e9cd93 · outbound

This paper cites Autoregressive Image Generation without Vector Quantization.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Autoregressive Image Generation without Vector Quantization

Reference 28

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source=pdf_text observed=2026-08-12T12:06:00.968754Z digest=sha256:207f95c4966a1178ca0c31dfb09f5be2baa64211621e1f7fdc003b20d78dbe66

Observation 3420117d-a3fa-49eb-b640-389f1c4bf19e · outbound

This paper cites Q-diffusion: Quantizing diffusion models.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Q-diffusion: Quantizing diffusion models

Reference 29

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source=pdf_text observed=2026-08-12T12:06:00.974203Z digest=sha256:1670e61f15a69e2a0714993b2689991fcf54418fea3b2b3a2fdaafed56af5763

Observation bed95b59-8dbe-47e9-b14f-81879ea35bba · outbound

This paper cites ImageFolder: Autoregressive Image Generation with Folded Tokens.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient ImageFolder: Autoregressive Image Generation with Folded Tokens

Reference 30

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source=pdf_text observed=2026-08-12T12:06:00.979246Z digest=sha256:24d2afe0fbb50be8d4a9de70c8c2669e727a54fbd6ad24c36c89b14dee969b04

Observation 6b0acc77-3f03-407b-8586-acb720539bf6 · outbound

This paper cites ControlVAR: Exploring Controllable Visual Autoregressive Modeling.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient ControlVAR: Exploring Controllable Visual Autoregressive Modeling

Reference 31

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source=pdf_text observed=2026-08-12T12:06:00.984359Z digest=sha256:eda2aa16307d85d509ac48863d1aca249b00ca008dec8ecf050ba4d69cc06857

Observation 89f9d24b-53fc-42e0-8a6c-ee0643000b92 · outbound

This paper cites Snap- fusion: Text-to-image diffusion model on mobile devices within two seconds.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Snap- fusion: Text-to-image diffusion model on mobile devices within two seconds

Reference 32

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T12:06:00.989344Z digest=sha256:0563c64ed101f90368eab1eea15467fef8494a827ea0dec1277931a20fd9bba9

Observation e7259b41-92cf-4b55-ab58-4b6780ea20b9 · outbound

This paper cites ControlAR: Controllable Image Generation with Autoregressive Models.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient ControlAR: Controllable Image Generation with Autoregressive Models

Reference 33

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source=pdf_text observed=2026-08-12T12:06:00.995117Z digest=sha256:25416d25bc39ae10844a53f1523636b32c3281d7a43594f100b0a6796a7c49b8

Observation 324b261a-1d65-47fa-9985-edba713facc7 · outbound

This paper cites Lumina-mGPT: Illuminate Flexible Photorealistic Text-to-Image Generation with Multimodal Generative Pretraining.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Lumina-mGPT: Illuminate Flexible Photorealistic Text-to-Image Generation with Multimodal Generative Pretraining

Reference 34

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source=pdf_text observed=2026-08-12T12:06:01.000349Z digest=sha256:dddbaeb138322e4a8fed523392f3264e15c9b6b398990efb534c447612b50ae8

Observation dc83de5b-060b-4d52-be68-d9ba151336fb · outbound

This paper cites Pseudo Numerical Methods for Diffusion Models on Manifolds.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Pseudo Numerical Methods for Diffusion Models on Manifolds

Reference 35

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source=pdf_text observed=2026-08-12T12:06:01.005492Z digest=sha256:b2c7422b05ca04d8ed6701c65ee4f98b3e8ec12102d965a3b71b8068415561d0

Observation 398bf983-3b0f-4a94-b2c1-82b78a573843 · outbound

This paper cites Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps

Reference 36

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source=pdf_text observed=2026-08-12T12:06:01.010782Z digest=sha256:85dd17484a6b01a4924ab778d11d4dfd4e9c124a9667ef735d766b47b6eca89e

Observation 03fd1dc9-c9c1-4a0d-bf59-af57760dc973 · outbound

This paper cites Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference

Reference 37

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source=pdf_text observed=2026-08-12T12:06:01.016817Z digest=sha256:3b16f9751d66fed500663b21f323e9e831589d71bee477db4fa4985a29a80f61

Observation 06f79ac3-74eb-4c1e-be4e-5a691768c681 · outbound

This paper cites Open-MAGVIT2: An Open-Source Project Toward Democratizing Auto-regressive Visual Generation.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Open-MAGVIT2: An Open-Source Project Toward Democratizing Auto-regressive Visual Generation

Reference 38

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source=pdf_text observed=2026-08-12T12:06:01.022735Z digest=sha256:8408bdda6c1b7705888a195f6851f338309bdcf9a57d2d447310750df18aabe4

Observation f6588738-2024-4c92-8f9b-f38fb8b6bb37 · outbound

This paper cites Accelerating Diffusion Models via Early Stop of the Diffusion Process.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Accelerating Diffusion Models via Early Stop of the Diffusion Process

Reference 39

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source=pdf_text observed=2026-08-12T12:06:01.028368Z digest=sha256:fecbb4aef1f7f1b0b0da08993479c002d5a724cb412b796781c2b8f8f4b7a3ac

Observation 091e2ac2-1b30-4422-aeb0-c2196294fb84 · outbound

This paper cites DeepCache: Accelerating Diffusion Models for Free.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient DeepCache: Accelerating Diffusion Models for Free

Reference 40

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source=pdf_text observed=2026-08-12T12:06:01.034183Z digest=sha256:92a84d5cb11d07063452a3782f68d8cdc69ad6bb4795fa70cf8915582f5f6043

Observation 0213bec1-28a6-4cd9-9fe4-ca54a3ceb1be · outbound

This paper cites STAR: Scale-wise Text-conditioned AutoRegressive image generation.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient STAR: Scale-wise Text-conditioned AutoRegressive image generation

Reference 41

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source=pdf_text observed=2026-08-12T12:06:01.040356Z digest=sha256:9adbb6286761315b963ad752ee2ac9a19b295a37b95909a13a389c59afe6441c

Observation cb2a9fdd-ecfe-4007-ad85-64ed92f6932f · outbound

This paper cites completely blind.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient completely blind

Reference 42

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T12:06:01.045659Z digest=sha256:b61ba51297ef330e741795b07957ec4d43a5b6935b52579e6d97c2a2732b1830

Observation a0085082-cc8c-4665-995a-535de8b18de8 · outbound

This paper cites Pytorch: An im- perative style, high-performance deep learning library.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Pytorch: An im- perative style, high-performance deep learning library

Reference 43

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source=pdf_text observed=2026-08-12T12:06:01.050581Z digest=sha256:cfe567548b831a88910bf5ab3a2352906543edc8c48e0e2f78e6a8d59f472d08

Observation 2233b2e0-77d5-433d-9c0a-ee6779c9832f · outbound

This paper cites Scalable diffusion models with transformers.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Scalable diffusion models with transformers

Reference 44

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source=pdf_text observed=2026-08-12T12:06:01.055203Z digest=sha256:38cf6f30a89144f43185c8b36cc808e2ab44f8656a2cc52f07c41924ca4da256

Observation d54f1179-7b73-4ea2-a89a-fe7ceeb133ee · outbound

This paper cites Efficient Autoregressive Audio Modeling via Next-Scale Prediction.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Efficient Autoregressive Audio Modeling via Next-Scale Prediction

Reference 45

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source=pdf_text observed=2026-08-12T12:06:01.059947Z digest=sha256:a35e255eabf584ea8433f28de4a98c84fa135e9d41a2ff5425bd97ab50cddbd3

Observation e1fa93f8-8dc1-4618-8670-3bb7b6beb98f · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Learning transferable visual models from natural language supervi- sion

Reference 46

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source=pdf_text observed=2026-08-12T12:06:01.064942Z digest=sha256:5abd6d12f597b9c8104ee718b6ccc0b73e5e5754a4e58ed55bc2e24d253ac5d0

Observation 9f633698-2602-4027-9801-da493a5ef7d5 · outbound

This paper cites Progressive Distillation for Fast Sampling of Diffusion Models.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Progressive Distillation for Fast Sampling of Diffusion Models

Reference 47

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source=pdf_text observed=2026-08-12T12:06:01.069770Z digest=sha256:746df90cccdfc882e5fc29ff165a4715cc31791b86f86d81e024f8334e80e47f

Observation 759271ac-9130-4a6d-961b-c9531abc83ef · outbound

This paper cites Adversarial Diffusion Distillation.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Adversarial Diffusion Distillation

Reference 48

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source=pdf_text observed=2026-08-12T12:06:01.074696Z digest=sha256:327eda22cd8bcbdec3964fc91c831cc7d2bff696c1227293a53ce16c80c7d9e0

Observation b1f872cb-fd35-4bb6-a1e9-6b3e23b1d6df · outbound

This paper cites Post-training quantization on diffusion models.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Post-training quantization on diffusion models

Reference 49

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source=pdf_text observed=2026-08-12T12:06:01.079825Z digest=sha256:2f51b7c7e0077a264b70e3fde4b8de3312bc7355d51845dcc494a64cfc4e6f11

Observation 2368a399-a1b0-4777-867f-bdaf6d650a25 · outbound

This paper cites FRDiff : Feature Reuse for Universal Training-free Acceleration of Diffusion Models.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient FRDiff : Feature Reuse for Universal Training-free Acceleration of Diffusion Models

Reference 50

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source=pdf_text observed=2026-08-12T12:06:01.087740Z digest=sha256:522af0965e450332f3223bd4946ae896baccdc5baebeff8744752c6ab3652caa

Observation 1f1c0d37-4510-487d-9b61-269bddbae82e · outbound

This paper cites Denoising Diffusion Implicit Models.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Denoising Diffusion Implicit Models

Reference 51

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source=pdf_text observed=2026-08-12T12:06:01.093548Z digest=sha256:90e06c80cde56380a3230475df775c1403e3a1917702afedc694f1580de5da92

Observation ab095ba0-8abd-4f31-8862-5d6b940afe53 · outbound

This paper cites Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Reference 52

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source=pdf_text observed=2026-08-12T12:06:01.099189Z digest=sha256:1dbd6963eaee41dfedb5524edce05ad05c59cebfabae5b4c2bca41e6c3f403c1

Observation abbfedb2-901c-453a-b193-f7a431f2704e · outbound

This paper cites HART: Efficient Visual Generation with Hybrid Autoregressive Transformer.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient HART: Efficient Visual Generation with Hybrid Autoregressive Transformer

Reference 53

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source=pdf_text observed=2026-08-12T12:06:01.103975Z digest=sha256:37d35a3ab3bd119e530b7b94c1a6ed23d0633d2fa5fa18ea34ab218e5051c9c3

Observation b9244f1e-fd3d-4598-8abc-69a48bfd771e · outbound

This paper cites Accelerating Auto-regressive Text-to-Image Generation with Training-free Speculative Jacobi Decoding.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Accelerating Auto-regressive Text-to-Image Generation with Training-free Speculative Jacobi Decoding

Reference 54

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source=pdf_text observed=2026-08-12T12:06:01.108964Z digest=sha256:6fc7ec7ea8b69faca8fe22d02068b7780d39e1fdf84e3a5475f18d398749f15d

Observation 44416ad8-384b-4578-a805-db13308549a7 · outbound

This paper cites Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction

Reference 55

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source=pdf_text observed=2026-08-12T12:06:01.114005Z digest=sha256:cdbd9624f1f18ffa4863990cf4fd5afb100f1b7f6b355b97c190875bd2d24fbf

Observation b0d6e350-be44-4f7d-9bde-2b9df30b8715 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 56

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source=pdf_text observed=2026-08-12T12:06:01.119328Z digest=sha256:b1a3e4bdd19ab536561ac4e7b468cfbf8bee3da765b3adfe861185ecbea7884f

Observation cdf0e4ca-2e60-46a7-8b1a-16e7f524d3d2 · outbound

This paper cites Conditional image genera- tion with pixelcnn decoders.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Conditional image genera- tion with pixelcnn decoders

Reference 57

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source=pdf_text observed=2026-08-12T12:06:01.125028Z digest=sha256:e0d70b82019543d082ead1746403c6ec3786387c014dbd692567170555350714

Observation 3eb0a456-a858-4e1a-922e-35a273b016fd · outbound

This paper cites Neural discrete representation learning.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Neural discrete representation learning

Reference 58

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source=pdf_text observed=2026-08-12T12:06:01.130765Z digest=sha256:d75e18bdafdee35bbac2c6d6de27a887af37bec1ae24af74bee78101e9829a4c

Observation a7ef895c-5988-4986-834c-7b19e455ad10 · outbound

This paper cites Ex- ploring clip for assessing the look and feel of images.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Ex- ploring clip for assessing the look and feel of images

Reference 59

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T12:06:01.135511Z digest=sha256:e402be09419dd1680e33940046c34a08e3d6579b7df582054bc145f6356b7e46

Observation c4470b04-6f16-4de9-9681-b7511823fe4d · outbound

This paper cites Cache Me if You Can: Accelerating Diffusion Models through Block Caching.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Cache Me if You Can: Accelerating Diffusion Models through Block Caching

Reference 60

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source=pdf_text observed=2026-08-12T12:06:01.140145Z digest=sha256:e845425bf7f82eb4cb63ba205554763543d159ee4ca70a30a571ab7cca06b55e

Observation 20e5c35d-3a5d-46fb-bfd4-dc5bb113d714 · outbound

This paper cites Show-o: One Single Transformer to Unify Multimodal Understanding and Generation.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Show-o: One Single Transformer to Unify Multimodal Understanding and Generation

Reference 61

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source=pdf_text observed=2026-08-12T12:06:01.146162Z digest=sha256:efc072e128bb22302f68703c2534fda74806d69d4ba6b21bb34ecc77e8b12797

Observation f1fde042-a4a3-4f40-87ac-cac40b278d1a · outbound

This paper cites Hash3D: Training-free Acceleration for 3D Generation.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Hash3D: Training-free Acceleration for 3D Generation

Reference 62

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source=pdf_text observed=2026-08-12T12:06:01.151609Z digest=sha256:06d55819544fbd9f251584c8e1d4414912a175111e68d6e2fac76e5566f3701a

Observation 3228f5f7-2e9e-4967-af98-94d7ea04ee9a · outbound

This paper cites Diffusion probabilistic model made slim.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Diffusion probabilistic model made slim

Reference 63

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T12:06:01.156677Z digest=sha256:c378a314643fe47e45e9ac17feb2d35752a1a01bef1c57d1c1f5368a50483374

Observation 12c112f8-ab58-424b-92d1-d8df4cdedc7c · outbound

This paper cites CAR: Controllable Autoregressive Modeling for Visual Generation.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient CAR: Controllable Autoregressive Modeling for Visual Generation

Reference 64

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source=pdf_text observed=2026-08-12T12:06:01.161614Z digest=sha256:51a9e82f3f7dc092a66d4c49143240ace02775424ca4672a96337472f57decad

Observation 351ef7da-6e42-44a8-af25-79e92c2bcfb4 · outbound

This paper cites One-step Diffusion with Distribution Matching Distillation.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient One-step Diffusion with Distribution Matching Distillation

Reference 65

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source=pdf_text observed=2026-08-12T12:06:01.167041Z digest=sha256:1df4a6c9d7cf14f6349ba75ee0d3f552776372d2cfa850f30f781effda622f2e

Observation b79837d3-5ad8-422c-9fc8-77b8bf75f680 · outbound

This paper cites Resshift: Efficient diffusion model for image super- resolution by residual shifting.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Resshift: Efficient diffusion model for image super- resolution by residual shifting

Reference 66

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raw_fallback, observed 2026-08-12T12:06:02.419397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T12:06:01.171803Z digest=sha256:d7f8b277ce254cff424386dbfaa63898124059a2710b433fda6c163c81454e57

Observation c1d51bcc-1f4d-4487-95c0-0fdddd013664 · outbound

This paper cites LAPTOP-Diff: Layer Pruning and Normalized Distillation for Compressing Diffusion Models.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient LAPTOP-Diff: Layer Pruning and Normalized Distillation for Compressing Diffusion Models

Reference 67

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source=pdf_text observed=2026-08-12T12:06:01.176398Z digest=sha256:73bb0ed153ce96efb4afb268e79fd2988ed23205a81689dc7f8f0ff09c60e66d

Observation 03b45b37-840b-4bb3-8f8f-e9577ba934ba · outbound

This paper cites G3PT: Unleash the power of Autoregressive Modeling in 3D Generation via Cross-scale Querying Transformer.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient G3PT: Unleash the power of Autoregressive Modeling in 3D Generation via Cross-scale Querying Transformer

Reference 68

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source=pdf_text observed=2026-08-12T12:06:01.181628Z digest=sha256:9a873e0a834083247406c44bbbf338e5bae287f6029cced7c3c224d0d7c63f05

Observation 3695f0a9-994f-48f7-baca-f2e7b2d9ee99 · outbound

This paper cites Fast Sampling of Diffusion Models with Exponential Integrator.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Fast Sampling of Diffusion Models with Exponential Integrator

Reference 69

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T12:06:01.187511Z digest=sha256:19e06d40a790a9e83330e6abe469bb6130452566c6608c632fbe7dde7f93f39a

Observation cc2f965e-3780-4d6f-bd82-95c5d4c116e6 · outbound

This paper cites VAR-CLIP: Text-to-Image Generator with Visual Auto-Regressive Modeling.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient VAR-CLIP: Text-to-Image Generator with Visual Auto-Regressive Modeling

Reference 70

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T12:06:01.192629Z digest=sha256:add26687ab0ad36fb32346491ebe2fb3a5d51b97ec356edb0a319c7d75dab75f

Observation 4affad3b-796b-4e7b-ae2f-b156f4b938a3 · outbound

This paper cites Faster Diffusion via Temporal Attention Decomposition.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Faster Diffusion via Temporal Attention Decomposition

Reference 71

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T12:06:01.198255Z digest=sha256:cd8dcaf2497cbc3e4f957df737a62111fed02bec0536cd75700905d2dd5f3166

Observation 672a973f-3971-48f5-8845-8eee16213a04 · outbound

This paper cites Real-Time Video Generation with Pyramid Attention Broadcast.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Real-Time Video Generation with Pyramid Attention Broadcast

Reference 72

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source=pdf_text observed=2026-08-12T12:06:01.203068Z digest=sha256:4b42cf473da912ee986c490abd5dfd6c03f005c729b89f9650fced0f151c5966

Observation 9f276dd2-d1f9-420c-902b-bfc8e599175b · outbound

This paper cites MobileDiffusion: Instant Text-to-Image Generation on Mobile Devices.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient MobileDiffusion: Instant Text-to-Image Generation on Mobile Devices

Reference 73

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:06:01.208187Z digest=sha256:765e022edc6b184e53c89694ba9c6ce2545edd34d159bf9a06adf5b686c421cc

Observation a7cb3764-b568-4eeb-81e8-df624495d175 · outbound

This paper cites Dpm- solver-v3: Improved diffusion ode solver with empirical model statistics.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Dpm- solver-v3: Improved diffusion ode solver with empirical model statistics

Reference 74

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verified fuzzy
raw_fallback, observed 2026-08-12T12:06:02.398355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T12:06:01.213828Z digest=sha256:9274f449e277605ddc304249717fe9a1033eeb0b5570137aa648064273154cd6

Observation 2ff60dfb-6593-4491-9a6d-bb3e98d131a3 · outbound

This paper cites Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model

Reference 75

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T12:06:01.218497Z digest=sha256:4783e460af5ee37f428bcb72506636660cd51ff368fe6a78303ef630503ecd96

Pith citing papers

Observation aa1f79b0-8e6d-406e-8dfa-1e8a18d509a4 · inbound

Memory-Efficient Visual Autoregressive Modeling with Scale-Aware KV Cache Compression cites this paper.

Memory-Efficient Visual Autoregressive Modeling with Scale-Aware KV Cache Compression Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient

Reference 7

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unresolved
no resolver link, observed 2026-08-07T14:16:12.670870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:16:12.670870Z digest=sha256:f26d95a18e4b2fe2a539600ae6bf09e9b9508387a444ec966389882cd21e46c0

Observation 13a7575a-d813-492b-87e7-ed2d4d607f4f · inbound

HMAR: Efficient Hierarchical Masked Auto-Regressive Image Generation cites this paper.

HMAR: Efficient Hierarchical Masked Auto-Regressive Image Generation Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T10:47:52.277927Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T10:47:52.277927Z digest=sha256:7de4102976eeefccd72ea47b7287c7ff683f235a96598c7404e3a0cb4a4d3133

Observation ffe0c12d-1a86-49ba-83df-a0f46bbde0de · inbound

SkipVAR: Accelerating Visual Autoregressive Modeling via Adaptive Frequency-Aware Skipping cites this paper.

SkipVAR: Accelerating Visual Autoregressive Modeling via Adaptive Frequency-Aware Skipping Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T05:05:00.091225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:05:00.091225Z digest=sha256:cb695d9c90ecfc3b349ce5353a526bf190f0915bde0b5a5e694a78faddca5ee2

Observation f3f8b3ac-f320-46cd-8758-8e241995f1bb · inbound

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer cites this paper.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T19:41:23.650563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:41:23.650563Z digest=sha256:31849f3da4cfbdda8be133ed7d9065d790903a51d57fcbd2aa6f15f316fc3e0d

Observation 4e9856ad-57c8-4913-a904-3b437fd7b117 · inbound

HACK++: Towards More Effective Head-Aware Key-Value Compression for Efficient Visual Autoregressive Modeling cites this paper.

HACK++: Towards More Effective Head-Aware Key-Value Compression for Efficient Visual Autoregressive Modeling Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-07-02T21:27:24.415141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-27T19:46:43.514413Z digest=sha256:feac095b61677347e20ec7a46c980d760dd8617e5ea256e9ec46d87501844ddf