Paper Citation Record · LEDGER

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization

As of 21 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 7 inbound Pith citation observations for arXiv:2411.17178.

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

pith.paper-citation-record.v1
2411.17178 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:27:38.392725Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:08:18.268294Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T21:27:24.400732Z

Reference resolution

21 of 21 outbound references displayed

verified exact0
verified fuzzy1
unresolved19
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dda2de5b-590a-4a00-9627-c57d4e5ab470 · outbound

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

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T12:27:38.292739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11304437-a7c0-42a6-99ab-efdfbf335de1 · outbound

This paper cites Classifier-Free Diffusion Guidance.

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization Classifier-Free Diffusion Guidance

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T12:27:38.297956Z

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Observation 251b3c81-772f-406a-828b-b69d691197d5 · outbound

This paper cites Quantization and training of neural networks for efficient integer-arithmetic-only inference.

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization Quantization and training of neural networks for efficient integer-arithmetic-only inference

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T12:27:38.302785Z

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Observation 9ea4499d-7c0c-4c6f-b84a-16203d044bad · outbound

This paper cites QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving.

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T12:27:38.307670Z

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Observation 8ee1c7ca-34f4-4841-8a44-24e482a5c762 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization Swin transformer: Hierarchical vision transformer using shifted windows

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T12:27:38.313207Z

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Observation b30a721f-7d4f-42de-8f7b-b85fecb64f83 · outbound

This paper cites Finite Scalar Quantization: VQ-VAE Made Simple.

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization Finite Scalar Quantization: VQ-VAE Made Simple

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T12:27:38.318041Z

Source-reported events for the cited work

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Observation f8b5dbe1-24d8-4e44-bb8e-6478af75fe3f · outbound

This paper cites A White Paper on Neural Network Quantization.

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization A White Paper on Neural Network Quantization

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T12:27:38.324261Z

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Observation 7e59727e-bdb2-4cc7-ba80-0accf952aee5 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T12:27:38.329213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74da2547-1882-4369-90ed-05c4abde76aa · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization Photorealistic text-to-image diffusion models with deep language understanding

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T12:27:38.333944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df17ad03-0b16-4cb9-b72e-957c1770b613 · outbound

This paper cites Improved techniques for training gans.

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization Improved techniques for training gans

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T12:27:38.338484Z

Source-reported events for the cited work

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Observation 41b89af6-576e-4f00-868f-08eb6a10fdcd · outbound

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

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T12:27:38.342956Z

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Observation 157e45b5-4266-4ee3-b6d7-ed1382d5e1d4 · outbound

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

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T12:27:38.347423Z

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Observation b44ddffc-3369-407f-b8ae-886a21c4a84d · outbound

This paper cites Smoothquant: Accurate and efficient post-training quantization for large language models.

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization Smoothquant: Accurate and efficient post-training quantization for large language models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T12:27:38.352321Z

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Observation b4900ad0-1138-4919-8643-ec0e9d002d18 · outbound

This paper cites Efficient Streaming Language Models with Attention Sinks.

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization Efficient Streaming Language Models with Attention Sinks

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T12:27:38.356886Z

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Observation 4ada4d06-108b-4152-ac66-a4a5253807f0 · outbound

This paper cites Imagereward: Learning and evaluating human preferences for text-to-image generation.

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization Imagereward: Learning and evaluating human preferences for text-to-image generation

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-12T12:27:38.361829Z

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Observation 13a0010e-7f87-43ca-8758-24e53bcb01d6 · outbound

This paper cites Zeroquant: Efficient and affordable post-training quantization for large-scale transformers.

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization Zeroquant: Efficient and affordable post-training quantization for large-scale transformers

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T12:27:38.366389Z

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Observation 9af6dfac-95fa-45a2-b83c-cad7bb29b150 · outbound

This paper cites DiTFastAttn: Attention Compression for Diffusion Transformer Models.

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization DiTFastAttn: Attention Compression for Diffusion Transformer Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T12:27:38.371373Z

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Observation 54c5249d-3aff-420b-85d9-fddb19127758 · outbound

This paper cites Ptq4vit: Post-training quantization for vision transformers with twin uniform quantization.

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization Ptq4vit: Post-training quantization for vision transformers with twin uniform quantization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T12:27:38.377125Z

Source-reported events for the cited work

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Observation 50989f4c-1518-4633-a718-ae97940248c5 · outbound

This paper cites ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation.

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T12:27:38.382219Z

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Observation 746fc683-b0d1-4e3c-8bdd-a271cab45169 · outbound

This paper cites Atom: Low-bit quantization for efficient and accurate llm serving.

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization Atom: Low-bit quantization for efficient and accurate llm serving

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:27:38.602877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9875c7d1-2215-4ba2-b8df-3be5445940b0 · outbound

This paper cites Lumina-Next: Making Lumina-T2X Stronger and Faster with Next-DiT.

LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization Lumina-Next: Making Lumina-T2X Stronger and Faster with Next-DiT

Reference 21

Resolution: malformed identifier; no resolver link, observed 2026-08-12T12:27:38.392725Z

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Pith citing papers

Observation 55003728-22df-4ba0-afaa-6ace648c0a4f · inbound

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design cites this paper.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:18.268294Z

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Observation f56e95aa-f6be-4e5f-994b-a7f82c45c05c · 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 LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:19.250138Z

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Observation 2d859106-d2a3-4cda-aa56-ffffc724c76d · inbound

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

SkipVAR: Accelerating Visual Autoregressive Modeling via Adaptive Frequency-Aware Skipping LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:00.334284Z

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Observation c36b438b-8ecc-4a04-82cc-d6552f9a305d · inbound

FasterVAR: Plug-and-Play Acceleration for Visual Autoregressive Models cites this paper.

FasterVAR: Plug-and-Play Acceleration for Visual Autoregressive Models LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T15:36:51.983813Z

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Observation 857db1d2-21ad-4df5-8dff-83089ee1ad18 · inbound

Adaptive Visual Autoregressive Acceleration via Dual-Linkage Entropy Analysis cites this paper.

Adaptive Visual Autoregressive Acceleration via Dual-Linkage Entropy Analysis LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T05:49:25.599257Z

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Observation 41aa78f3-5c34-438a-b143-974bb08ed898 · 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 LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:27:24.402192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4f1b115e-33ff-41ca-85bf-7bf23481944b · inbound

Token Radius Attention for Efficient Video Generation cites this paper.

Token Radius Attention for Efficient Video Generation LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-04T06:03:03.290924Z

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