Paper Citation Record · LEDGER

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark

As of 18 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 4 inbound Pith citation observations for arXiv:2412.04307.

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

pith.paper-citation-record.v1
2412.04307 v4

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:35:18.613716Z

measured 56 of 56 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:29:42.169335Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T00:47:53.340867Z

Reference resolution

52 of 52 outbound references displayed

verified exact1
verified fuzzy33
unresolved18
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 99487b15-c6fe-4ea8-8d67-95c6a660c7bd · outbound

This paper cites Variational image compression with a scale hyperprior.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Variational image compression with a scale hyperprior

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32cab4a8-ef7b-4a67-ba94-e1b4e6799e7c · outbound

This paper cites Sullivan, and Jens-Rainer Ohm.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Sullivan, and Jens-Rainer Ohm

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.722215Z

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Observation 3027d47b-9b4c-42d1-b51d-079474c5287d · outbound

This paper cites High efficient 3D convolution feature compression.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark High efficient 3D convolution feature compression

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.706481Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d8e0c3dc-e149-4acf-92a2-a0e5fbdfa2ed · outbound

This paper cites When federated learning meets privacy- preserving computation.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark When federated learning meets privacy- preserving computation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.689652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e133e5b0-c530-44d7-bef0-2adae5aa9ea5 · outbound

This paper cites End-to-end learned scalable multilayer feature compression for machine vision tasks.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark End-to-end learned scalable multilayer feature compression for machine vision tasks

Reference 5

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Source-reported events for the cited work

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Observation e4c84828-083d-497a-8358-185ad5cb6cee · outbound

This paper cites Toward intelligent sensing: Inter- mediate deep feature compression.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Toward intelligent sensing: Inter- mediate deep feature compression

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.651079Z

Source-reported events for the cited work

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Observation 13baf8ea-f96b-479e-b792-5d196c317e0c · outbound

This paper cites an unresolved cited work.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Unresolved cited work

Reference 7

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Observation fa7d2122-959d-422d-a3aa-16926db30ea6 · outbound

This paper cites ImageNet: a large-scale hierarchical image database.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark ImageNet: a large-scale hierarchical image database

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.619235Z

Source-reported events for the cited work

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Observation 657682d1-132f-4d1c-97fa-9a8db120a33b · outbound

This paper cites Upsampling DINOv2 features for unsupervised vision tasks and weakly supervised materials segmentation.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Upsampling DINOv2 features for unsupervised vision tasks and weakly supervised materials segmentation

Reference 9

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Source-reported events for the cited work

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Observation 5f891cc7-7635-417f-a9f7-270443e906ca · outbound

This paper cites Video coding for machines: A paradigm of collab- orative compression and intelligent analytics.IEEE Transac- tions on Image Processing, 29:8680–8695, 2020.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Video coding for machines: A paradigm of collab- orative compression and intelligent analytics.IEEE Transac- tions on Image Processing, 29:8680–8695, 2020

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.602963Z

Source-reported events for the cited work

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Observation 2ddf5411-4f61-4fb2-8388-d6d81d4a0cb5 · outbound

This paper cites The Llama 3 Herd of Models.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark The Llama 3 Herd of Models

Reference 11

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Source-reported events for the cited work

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Observation 8c86a9a8-83f1-44d4-9418-3546f255f588 · outbound

This paper cites Scaling recti- fied flow transformers for high-resolution image synthesis.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Scaling recti- fied flow transformers for high-resolution image synthesis

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.587303Z

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Observation 3cd24b9f-4927-4663-86f1-b988b762fcb8 · outbound

This paper cites Image coding for machines with omnipotent feature learn- ing.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Image coding for machines with omnipotent feature learn- ing

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.571230Z

Source-reported events for the cited work

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Observation 23e70fe8-a20f-4ec5-9828-f1385f3cbeb9 · outbound

This paper cites LLM-based edge intelligence: A comprehensive survey on architectures, applications, security and trustworthiness.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark LLM-based edge intelligence: A comprehensive survey on architectures, applications, security and trustworthiness

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.552343Z

Source-reported events for the cited work

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Observation 5eecdd70-20f5-47a4-b5ad-a85fd3e57093 · outbound

This paper cites Towards task-generic image compression: A study of semantics- oriented metrics.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Towards task-generic image compression: A study of semantics- oriented metrics

Reference 15

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Source-reported events for the cited work

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Observation e513e774-52e9-44d0-a900-19d016d1aab1 · outbound

This paper cites DMOFC: discrimination metric-optimized feature com- pression.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark DMOFC: discrimination metric-optimized feature com- pression

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.520181Z

Source-reported events for the cited work

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Observation 3aadc8ff-5a4d-4590-a9a4-360e06ed887c · outbound

This paper cites Rethinking the joint optimization in video coding for machines: A case study.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Rethinking the joint optimization in video coding for machines: A case study

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.503321Z

Source-reported events for the cited work

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Observation 8b33e129-4650-4615-b91d-dfeba398981f · outbound

This paper cites IMOFC: identity-level metric optimized fea- ture compression for identification tasks.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark IMOFC: identity-level metric optimized fea- ture compression for identification tasks

Reference 18

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Source-reported events for the cited work

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Observation 71406baa-9c09-4e46-91e4-0d4c975429d0 · outbound

This paper cites Challenges and Applications of Large Language Models.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Challenges and Applications of Large Language Models

Reference 19

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Source-reported events for the cited work

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Observation 652000b9-2845-4945-b882-34adcae3130e · outbound

This paper cites Bridging Compressed Image Latents and Multimodal Large Language Models.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Bridging Compressed Image Latents and Multimodal Large Language Models

Reference 20

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Source-reported events for the cited work

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Observation 4c194054-61d9-4520-8b79-babb70fd103b · outbound

This paper cites End-to-end learnable multi-scale feature compression for VCM.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark End-to-end learnable multi-scale feature compression for VCM

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.467665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2460614b-f65a-42e7-98cc-58d6d7ef9e82 · outbound

This paper cites From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f9cd648-ab54-4582-a62b-06e935128c74 · outbound

This paper cites GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding

Reference 23

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Source-reported events for the cited work

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Observation bb83025b-f64d-410d-84c5-c32b4019d31f · outbound

This paper cites Attention-based variable-size feature compression module for edge inference.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Attention-based variable-size feature compression module for edge inference

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.451610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 79119655-497b-428d-b072-b04790f28e19 · outbound

This paper cites USTC-TD: A Test Dataset and Benchmark for Image and Video Coding in 2020s.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark USTC-TD: A Test Dataset and Benchmark for Image and Video Coding in 2020s

Reference 25

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Source-reported events for the cited work

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Observation e4ac328c-9a18-45fe-80a4-4e066c6abe30 · outbound

This paper cites Object segmentation-assisted inter prediction for versatile video coding.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Object segmentation-assisted inter prediction for versatile video coding

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.435860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 65d77563-c5fe-424b-8b5a-9ecf870dfd36 · outbound

This paper cites Learnt mutual feature compression for machine vision.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Learnt mutual feature compression for machine vision

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.419054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9ed152ec-a9fe-492a-b143-2c4604c51af0 · outbound

This paper cites Preprocessing enhanced image compression for ma- chine vision.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Preprocessing enhanced image compression for ma- chine vision

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.401042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f9662900-9549-4541-bbbb-e8b4349ad21a · outbound

This paper cites an unresolved cited work.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Unresolved cited work

Reference 29

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Source-reported events for the cited work

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Observation 21690aa1-ce98-488c-87c8-e739aff32c05 · outbound

This paper cites Feature compression with 3d sparse con- volution.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Feature compression with 3d sparse con- volution

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.367027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c4cce007-b889-406c-bf44-0963b5d140c9 · outbound

This paper cites Perceptual image compression with con- ditional diffusion transformers.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Perceptual image compression with con- ditional diffusion transformers

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.350247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 58b68250-f0a4-4bec-88fd-01ab21dac0f2 · outbound

This paper cites Video feature compression for machine tasks.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Video feature compression for machine tasks

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.331484Z

Source-reported events for the cited work

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Observation ef2fdf8e-b4c0-4ced-9418-b5add2537cbf · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark DINOv2: Learning Robust Visual Features without Supervision

Reference 33

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Source-reported events for the cited work

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Observation 5da21e00-ef04-4a8f-8250-b07c1e43086c · outbound

This paper cites Learn- ing transferable visual models from natural language super- vision.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Learn- ing transferable visual models from natural language super- vision

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-11T21:35:18.525940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 544f4252-0e2e-4607-a139-4ee2bfd80a71 · outbound

This paper cites Vnvc: A versatile neural video coding framework for efficient human- machine vision.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Vnvc: A versatile neural video coding framework for efficient human- machine vision

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.304410Z

Source-reported events for the cited work

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Observation adde24bf-ae11-437a-a1e3-2ef7d3cb2aaa · outbound

This paper cites EVA-CLIP: Improved Training Techniques for CLIP at Scale.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark EVA-CLIP: Improved Training Techniques for CLIP at Scale

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36693ca7-b02b-4933-827e-2ed1c842d27b · outbound

This paper cites Deep feature compression using spatio-temporal arrangement toward col- laborative intelligent world.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Deep feature compression using spatio-temporal arrangement toward col- laborative intelligent world

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.287256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0f6419bc-1130-4d03-a3ae-b581c08ee2db · outbound

This paper cites FedBERT: when federated learning meets pre-training.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark FedBERT: when federated learning meets pre-training

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.265506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9211fb04-248a-4100-96ff-5820370817af · outbound

This paper cites Non- semantics suppressed mask learning for unsupervised video semantic compression.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Non- semantics suppressed mask learning for unsupervised video semantic compression

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.247620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bbef0549-ff8b-482c-a97d-aacd2eebb858 · outbound

This paper cites SMC++: masked learning of unsupervised video semantic compression.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark SMC++: masked learning of unsupervised video semantic compression

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-11T21:35:18.554637Z

Source-reported events for the cited work

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Observation 7371f485-d2d1-431f-9954-0ea147cde79a · outbound

This paper cites Free-VSC: free semantics from visual foundation models for unsupervised video semantic compression.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Free-VSC: free semantics from visual foundation models for unsupervised video semantic compression

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.231392Z

Source-reported events for the cited work

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Observation 38947c6c-4682-4d64-b8ba-e839e3178d82 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark LLaMA: Open and Efficient Foundation Language Models

Reference 42

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Source-reported events for the cited work

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Observation 4a1c0f70-b1c6-4ca3-94af-cd2c8af82a59 · outbound

This paper cites Split learning for health: Distributed deep learning without sharing raw patient data.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Split learning for health: Distributed deep learning without sharing raw patient data

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-11T21:35:18.569442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da51212f-f06e-46af-93ba-526bc4dc1e14 · outbound

This paper cites Towards analysis- friendly face representation with scalable feature and texture compression.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Towards analysis- friendly face representation with scalable feature and texture compression

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.215250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cacb124f-f7ed-4fa9-b60c-ead2c7b59276 · outbound

This paper cites NExT-GPT: Any-to-any multimodal LLM.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark NExT-GPT: Any-to-any multimodal LLM

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.193958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f737fd03-f90b-41c6-a697-d360daa64c00 · outbound

This paper cites On Protecting the Data Privacy of Large Language Models (LLMs): A Survey.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark On Protecting the Data Privacy of Large Language Models (LLMs): A Survey

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-11T21:35:18.584227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d586331-b01d-4fc1-993b-822478be20a3 · outbound

This paper cites SSSIC: Semantics-to-signal scalable image coding with learned structural representations.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark SSSIC: Semantics-to-signal scalable image coding with learned structural representations

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.176219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 604c9c4f-433b-4b78-a078-e9c433f4f74a · outbound

This paper cites Video coding for machines: Compact vi- sual representation compression for intelligent collaborative analytics.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Video coding for machines: Compact vi- sual representation compression for intelligent collaborative analytics

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.158452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1e49bf37-9a9b-4688-a850-c5c51cfaca26 · outbound

This paper cites Open- FedLLM: Training large language models on decentralized private data via federated learning.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Open- FedLLM: Training large language models on decentralized private data via federated learning

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.141377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 48f523cd-3651-4804-a8ab-3680459f06b7 · outbound

This paper cites All-in-One Image Coding for Joint Human-Machine Vision with Multi-Path Aggregation.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark All-in-One Image Coding for Joint Human-Machine Vision with Multi-Path Aggregation

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-08-11T21:35:18.680184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 97cddd22-723c-4197-9dde-d43fcee2815b · outbound

This paper cites MSFC: Deep feature compression in multi-task network.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark MSFC: Deep feature compression in multi-task network

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:35:19.122631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d8a27910-f0f6-4e67-922e-a959fd8db579 · outbound

This paper cites Safely Learning with Private Data: A Federated Learning Framework for Large Language Model.

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark Safely Learning with Private Data: A Federated Learning Framework for Large Language Model

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-11T21:35:18.613716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation eded7399-e123-41fd-b622-61fe4d44e953 · inbound

Compressed Feature Quality Assessment: Dataset and Baselines cites this paper.

Compressed Feature Quality Assessment: Dataset and Baselines Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T05:39:11.838893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 795e52ae-b18f-41e3-892f-437a221b8c3f · inbound

Cross-architecture universal feature coding via distribution alignment cites this paper.

Cross-architecture universal feature coding via distribution alignment Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:47:53.347796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fdff1977-a93c-492c-bde2-fa3c9260f00e · inbound

DT-UFC: Universal Large Model Feature Coding via Peaky-to-Balanced Distribution Transformation cites this paper.

DT-UFC: Universal Large Model Feature Coding via Peaky-to-Balanced Distribution Transformation Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-15T19:29:42.169335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 939425c4-6526-47c3-9d9f-523d5baae060 · inbound

Visual Token Codec: Unleashing Spatial Redundancy for ViT Feature Coding cites this paper.

Visual Token Codec: Unleashing Spatial Redundancy for ViT Feature Coding Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-14T04:28:16.862213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.