Paper Citation Record · LEDGER

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation

As of 21 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 1 inbound Pith citation observation for arXiv:2506.18226.

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

pith.paper-citation-record.v1
2506.18226 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:27:20.833525Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T15:27:55.009337Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T22:26:16.863070Z

Reference resolution

39 of 39 outbound references displayed

verified exact0
verified fuzzy27
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a57953e6-d5a0-4555-a578-137d39854d1e · outbound

This paper cites Roformer: Enhanced transformer with rotary position embedding.Neurocomputing, 2024.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Roformer: Enhanced transformer with rotary position embedding.Neurocomputing, 2024

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:20.710302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6376b9e8-ec9b-41f9-967b-6758eebd25c8 · outbound

This paper cites Qwen technical report.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Qwen technical report

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:21.207103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 55825ece-416b-42ef-add4-380a2c90047f · outbound

This paper cites Llama: Open and efficient foundation language models.CoRR, 2023.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Llama: Open and efficient foundation language models.CoRR, 2023

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:21.195706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 10bccf2e-5536-458d-95e1-e2474ecf3e08 · outbound

This paper cites Llama 2: Open foundation and fine-tuned chat models.CoRR, 2023.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Llama 2: Open foundation and fine-tuned chat models.CoRR, 2023

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:21.185783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c803ace4-978b-4fa0-8ded-77e938f5b716 · outbound

This paper cites an unresolved cited work.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-06T23:27:21.175041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3544f0f8-db91-4951-8592-06fac6825064 · outbound

This paper cites GPT-4 technical report.CoRR, 2023.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation GPT-4 technical report.CoRR, 2023

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:21.165352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1cb0e3ec-ca12-41f2-a96b-eabdf50f7ffb · outbound

This paper cites Autore- gressive model beats diffusion: Llama for scalable image generation.CoRR, 2024.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Autore- gressive model beats diffusion: Llama for scalable image generation.CoRR, 2024

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:21.155562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 219e9c64-fa8e-4255-b767-c4ecd79eb445 · outbound

This paper cites Autoregressive image generation without vector quantization.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Autoregressive image generation without vector quantization

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:20.735216Z

Source-reported events for the cited work

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Observation 3df6ad3b-1128-4bc5-a8e8-ce85bc690382 · outbound

This paper cites an unresolved cited work.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Unresolved cited work

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:20.738395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c825669e-6c9c-43b4-b222-69b5cbe982e7 · outbound

This paper cites Freeman, Michael Rubinstein, Yuanzhen Li, and Dilip Krishnan.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Freeman, Michael Rubinstein, Yuanzhen Li, and Dilip Krishnan

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:21.133299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 96c0083c-2ecb-46e3-946b-bf815b604178 · outbound

This paper cites Neural discrete representation learning.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Neural discrete representation learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:20.744661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27294b00-80d8-4f4e-a9ec-6622f4e646f5 · outbound

This paper cites Visual autoregressive modeling: Scalable image generation via next-scale prediction.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Visual autoregressive modeling: Scalable image generation via next-scale prediction

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:20.747754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58867405-ad5f-40c5-b608-64e8623d0bfe · outbound

This paper cites Semhitok: A unified image tokenizer via semantic-guided hierarchical codebook for multimodal understanding and generation.CoRR, 2025.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Semhitok: A unified image tokenizer via semantic-guided hierarchical codebook for multimodal understanding and generation.CoRR, 2025

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:21.111936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d117cc41-ce87-4b06-aa30-a7425d56d5a3 · outbound

This paper cites Robust latent matters: Boosting image generation with sampling error synthesis.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Robust latent matters: Boosting image generation with sampling error synthesis

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:21.102120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 57962df8-83d7-47b9-8ec1-49ed5a6a3f53 · outbound

This paper cites Subobject-level image tokenization.CoRR, 2024.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Subobject-level image tokenization.CoRR, 2024

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:21.092735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation eeba3c8f-a8e1-4c06-adb4-78cbed64c72e · outbound

This paper cites Unitok: A unified tokenizer for visual generation and understanding.CoRR, 2025.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Unitok: A unified tokenizer for visual generation and understanding.CoRR, 2025

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:21.082560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d54674ac-b4bc-4fbd-b61d-66a976357295 · outbound

This paper cites Imagefolder: Autoregressive image generation with folded tokens.CoRR, 2024.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Imagefolder: Autoregressive image generation with folded tokens.CoRR, 2024

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:21.071626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4d8ddda0-34be-4f06-b933-3683a9eb2f49 · outbound

This paper cites Infllm: Training-free long-context extrapolation for llms with an efficient context memory.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Infllm: Training-free long-context extrapolation for llms with an efficient context memory

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:21.061344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fcfaf2f2-bfaf-4d76-ab72-236fd107746e · outbound

This paper cites Reattention: Training-free infinite context with finite attention scope.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Reattention: Training-free infinite context with finite attention scope

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:21.051400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 26bf444c-de2c-4d73-8f7c-1c33077510f6 · outbound

This paper cites Efficient streaming language models with attention sinks.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Efficient streaming language models with attention sinks

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:20.772771Z

Source-reported events for the cited work

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Observation a235ac60-16ce-4429-9601-b8e44b9e8a99 · outbound

This paper cites Generating long sequences with sparse transformers.CoRR, 2019.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Generating long sequences with sparse transformers.CoRR, 2019

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:21.035383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 106cd0a3-751f-451a-8aec-5ef0a0dc22dd · outbound

This paper cites Zipar: Accelerating auto-regressive image generation through spatial locality.CoRR, 2024.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Zipar: Accelerating auto-regressive image generation through spatial locality.CoRR, 2024

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:21.024395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b09f64e9-4b65-4091-b261-8dc5ad02924b · outbound

This paper cites Freeman, and Yu-Xiong Wang.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Freeman, and Yu-Xiong Wang

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:21.013863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a3f57708-e743-4a45-b6cf-dd688903f9fb · outbound

This paper cites Neighboring autoregressive modeling for efficient visual generation.CoRR, 2025.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Neighboring autoregressive modeling for efficient visual generation.CoRR, 2025

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:21.003001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1e1fb317-9b2d-4480-a5ee-adaebc23f8db · outbound

This paper cites Frequency autoregressive image generation with continuous tokens.CoRR, 2025.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Frequency autoregressive image generation with continuous tokens.CoRR, 2025

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:20.992695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0db071da-37a9-432a-b085-8e55996af523 · outbound

This paper cites Fluid: Scaling autoregressive text-to-image generative models with continuous tokens.CoRR, 2024.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Fluid: Scaling autoregressive text-to-image generative models with continuous tokens.CoRR, 2024

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:20.980948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ef710ed3-e26b-4ada-b6c2-ad8ed9fffb93 · outbound

This paper cites Vector-quantized image modeling with improved VQGAN.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Vector-quantized image modeling with improved VQGAN

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:20.795500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 811eeea0-07e0-4558-b17f-64129b2e5a21 · outbound

This paper cites Zero-shot text-to-image generation.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Zero-shot text-to-image generation

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:20.798502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb4e0df4-385b-485e-938e-7a912103a8d9 · outbound

This paper cites Autoregressive image generation with randomized parallel decoding.CoRR, 2025.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Autoregressive image generation with randomized parallel decoding.CoRR, 2025

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:20.958255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9054ea29-2404-4562-aae1-75bfb44dd058 · outbound

This paper cites Focus directions make your language models pay more attention to relevant contexts.CoRR, 2025.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Focus directions make your language models pay more attention to relevant contexts.CoRR, 2025

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:20.946490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5b82b4a1-31c1-4e12-825a-9ff4d231344c · outbound

This paper cites When attention sink emerges in language models: An empirical view.ICLR, 2025.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation When attention sink emerges in language models: An empirical view.ICLR, 2025

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:20.936387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e0574fcd-8ed5-4bb5-aa53-a8177c21a68f · outbound

This paper cites Longheads: Multi-head attention is secretly a long context processor.CoRR, 2024.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Longheads: Multi-head attention is secretly a long context processor.CoRR, 2024

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:20.925565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 60f71def-6b12-4108-96c2-fc609415ee51 · outbound

This paper cites Minference 1.0: Accelerating pre-filling for long-context llms via dynamic sparse attention.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Minference 1.0: Accelerating pre-filling for long-context llms via dynamic sparse attention

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:20.915192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a05cb066-f064-41a8-a698-11f3f3c2882b · outbound

This paper cites Retrievalattention: Accelerating long-context LLM inference via vector retrieval.CoRR, 2024.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Retrievalattention: Accelerating long-context LLM inference via vector retrieval.CoRR, 2024

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:20.905014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 99b3be7a-6ee8-4fca-9564-ee128fb8b1ba · outbound

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

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Learning transferable visual models from natural language supervision

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:20.820592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e34148a0-8d4e-4e9f-8c5c-30d9c7c04f67 · outbound

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

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:20.824126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e680b3b8-e884-424c-b0f5-317688d22db5 · outbound

This paper cites Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:20.882392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4d0a9e11-36d7-4d11-b884-6810086032f8 · outbound

This paper cites Scaling up gans for text-to-image synthesis.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation Scaling up gans for text-to-image synthesis

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:20.830482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5548042f-edc5-490f-9521-3ad89833ff9c · outbound

This paper cites High-resolution image synthesis with latent diffusion models.CVPR, 2022.

Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation High-resolution image synthesis with latent diffusion models.CVPR, 2022

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:20.864282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

Observation 4fcd77ff-6021-49ed-856b-2672110cab3a · inbound

Geometry-Aware Implicit Memory for Video World Models cites this paper.

Geometry-Aware Implicit Memory for Video World Models Make It Efficient: Dynamic Sparse Attention for Autoregressive Image Generation

Reference 57

Resolution: verified exact; arxiv_id, observed 2026-07-01T22:26:16.864916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.