Paper Citation Record · LEDGER

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation

As of 18 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2607.23997.

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

pith.paper-citation-record.v1
2607.23997 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T23:23:04.616285Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

30 of 30 outbound references displayed

verified exact0
verified fuzzy0
unresolved30
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 89299c68-a38a-4cfa-9611-4fd19c25ab18 · outbound

This paper cites Revisiting ResNets: Improved Training and Scaling Strategies.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Revisiting ResNets: Improved Training and Scaling Strategies

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:02.555835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf51f667-d91c-4dda-8ea9-f64e00087d2e · outbound

This paper cites Adaptive neural networks for efficient inference.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Adaptive neural networks for efficient inference

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:02.624045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 760ad54d-feeb-448f-a25f-fb6e9290ea35 · outbound

This paper cites Lan- guage models are few-shot learners.Advances in neural in- formation processing systems, 33:1877–1901, 2020.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Lan- guage models are few-shot learners.Advances in neural in- formation processing systems, 33:1877–1901, 2020

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:02.700376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ad154a1-229d-45ff-9499-ff978f73ce9b · outbound

This paper cites Functional map of the world.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Functional map of the world

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:02.793552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87a64854-c79e-4fb7-a02c-35be0738866a · outbound

This paper cites Spatially adaptive computation time for residual networks.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Spatially adaptive computation time for residual networks

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:02.874065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81de5a27-f48b-4a0d-a639-2294bf409ce2 · outbound

This paper cites Dynamic Channel Pruning: Feature Boosting and Suppression.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Dynamic Channel Pruning: Feature Boosting and Suppression

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:02.929979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2bffeaa8-6cb3-4754-b395-7621d4f32bfd · outbound

This paper cites Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:02.984897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ed3b826-b07f-48a7-aa9b-bfe321ebba03 · outbound

This paper cites Adaptive Computation Time for Recurrent Neural Networks.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Adaptive Computation Time for Recurrent Neural Networks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:03.049633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0548e2af-2c55-441c-aa68-69279be6b472 · outbound

This paper cites Searching for mo- bilenetv3.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Searching for mo- bilenetv3

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:03.168743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36447690-d25c-46cd-b954-a78701480ef4 · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:03.244327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a29ec23-a06c-4c3c-bd4b-b61df7df8238 · outbound

This paper cites Multi-Scale Dense Networks for Resource Efficient Image Classification.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Multi-Scale Dense Networks for Resource Efficient Image Classification

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:03.329121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b13748f-25b8-41ea-af21-fad7132b3ce7 · outbound

This paper cites Improved techniques for training adaptive deep net- works.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Improved techniques for training adaptive deep net- works

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:03.368593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3fba6903-42d0-4649-b202-e97048a24dd2 · outbound

This paper cites Dynamic computational time for visual attention.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Dynamic computational time for visual attention

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:03.429609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75105a6c-46d9-4ade-a207-30219bed1b4d · outbound

This paper cites Changing Model Behavior at Test-Time Using Reinforcement Learning.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Changing Model Behavior at Test-Time Using Reinforcement Learning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:03.498444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1efd801c-a95b-4a8d-bd08-7e9ac82704bd · outbound

This paper cites Hard-attention for scalable image classification.Advances in Neural Information Processing Systems, 34:14694–14707,.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Hard-attention for scalable image classification.Advances in Neural Information Processing Systems, 34:14694–14707,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:03.572217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6afe82fe-ce3c-49b8-bb5f-cdd45b941630 · outbound

This paper cites Adaptative inference cost with convolutional neural mixture models.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Adaptative inference cost with convolutional neural mixture models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:03.644695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43821f9d-1f99-428a-b873-7638f39d41e5 · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:03.692312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a82df328-b4fd-40e9-ba94-3ed81f892b91 · outbound

This paper cites Energy and Policy Considerations for Deep Learning in NLP.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Energy and Policy Considerations for Deep Learning in NLP

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:03.788467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 553fa447-f5d9-4729-bf6c-9ecebd3e2c5b · outbound

This paper cites Efficientnet: Rethinking model scaling for convolutional neural networks.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Efficientnet: Rethinking model scaling for convolutional neural networks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:03.849511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 367d3818-69a3-4202-8faa-b7bb21c85f0d · outbound

This paper cites EfficientNetV2: Smaller Models and Faster Training.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation EfficientNetV2: Smaller Models and Faster Training

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:03.934926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b2ce6fc-b7f6-485c-a2dd-44eb74ffcab2 · outbound

This paper cites Branchynet: Fast inference via early exiting from deep neural networks.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Branchynet: Fast inference via early exiting from deep neural networks

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:03.998627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7506c1e5-0f83-4b73-ac99-2ad2484abf3a · outbound

This paper cites Training data-efficient image transformers & distillation through at- tention.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Training data-efficient image transformers & distillation through at- tention

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:04.084973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e81f97e9-0a1f-4432-a721-6866a9bf80bc · outbound

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

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation LLaMA: Open and Efficient Foundation Language Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:04.153359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d8ae9c9-479a-45cf-967a-82cb4520cdb7 · outbound

This paper cites Convolutional networks with adaptive inference graphs.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Convolutional networks with adaptive inference graphs

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:04.237999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b6254ee-346b-4ef4-9947-d07b66f0380b · outbound

This paper cites Dynamic convolu- tions: Exploiting spatial sparsity for faster inference.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Dynamic convolu- tions: Exploiting spatial sparsity for faster inference

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:04.310806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f14b116a-07c6-433d-b155-8fc2c2356ec1 · outbound

This paper cites Skipnet: Learning dynamic routing in convolutional networks.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Skipnet: Learning dynamic routing in convolutional networks

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:04.376669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c6ccd34-0474-4220-bcc3-1212eeb3648a · outbound

This paper cites Glance and Focus: a Dynamic Approach to Reducing Spatial Redundancy in Image Classification.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Glance and Focus: a Dynamic Approach to Reducing Spatial Redundancy in Image Classification

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:04.434341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bea6f0f0-ddd9-48ff-95aa-3953c5d2d661 · outbound

This paper cites Not All Images are Worth 16x16 Words: Dynamic Transformers for Efficient Image Recognition.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Not All Images are Worth 16x16 Words: Dynamic Transformers for Efficient Image Recognition

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:04.494677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19112c2b-9fd6-441f-85f7-fe2b62012909 · outbound

This paper cites Resolution adaptive networks for efficient infer- ence.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Resolution adaptive networks for efficient infer- ence

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:04.556327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75e715e6-197a-4e7b-b50d-2dd3e4040765 · outbound

This paper cites Slimmable Neural Networks.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Slimmable Neural Networks

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-31T23:23:04.616285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.