Paper Citation Record · LEDGER

Think Sparse, Predict Dense: Continuous Thought Machines for Image Super-Resolution

As of 23 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 0 inbound Pith citation observations for arXiv:2607.18856.

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

pith.paper-citation-record.v1
2607.18856 v1

Coverage vector

measured 11 of 11 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T14:10:48.579536Z

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

11 of 11 outbound references displayed

verified exact0
verified fuzzy0
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ce3d6b69-95c7-498d-b7c2-96c6632369a3 · outbound

This paper cites Fast, accurate, and lightweight super-resolution with cascading residual network.

Think Sparse, Predict Dense: Continuous Thought Machines for Image Super-Resolution Fast, accurate, and lightweight super-resolution with cascading residual network

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T14:10:48.166203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d659e00-7168-4412-a76a-6c9c2339e476 · outbound

This paper cites Continuous thought machines.arXiv preprint arXiv:2505.05522, 2025.

Think Sparse, Predict Dense: Continuous Thought Machines for Image Super-Resolution Continuous thought machines.arXiv preprint arXiv:2505.05522, 2025

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T14:10:48.219806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee0ae432-6b03-48f3-824b-4cdd61cf3575 · outbound

This paper cites MambaIRv2: Attentive state space restoration.

Think Sparse, Predict Dense: Continuous Thought Machines for Image Super-Resolution MambaIRv2: Attentive state space restoration

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T14:10:48.257959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 072a04df-be49-4df9-87ac-5767b69f32f3 · outbound

This paper cites Lightweight image super-resolution with information multi- distillation network.

Think Sparse, Predict Dense: Continuous Thought Machines for Image Super-Resolution Lightweight image super-resolution with information multi- distillation network

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T14:10:48.299118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ada7f28-67e1-4121-903c-15c61de6f31a · outbound

This paper cites Deeply- recursive convolutional network for image super-resolution.

Think Sparse, Predict Dense: Continuous Thought Machines for Image Super-Resolution Deeply- recursive convolutional network for image super-resolution

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T14:10:48.342691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56748235-362c-484a-aeba-474d807f5743 · outbound

This paper cites SwinIR: Image restoration using swin transformer.

Think Sparse, Predict Dense: Continuous Thought Machines for Image Super-Resolution SwinIR: Image restoration using swin transformer

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T14:10:48.383773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 724a961e-f71c-4c79-ad5c-585a1d7409bb · outbound

This paper cites Enhanced deep residual networks for single image super-resolution.

Think Sparse, Predict Dense: Continuous Thought Machines for Image Super-Resolution Enhanced deep residual networks for single image super-resolution

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T14:10:48.424981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cd027c8-1102-410a-b3f1-67852bdc1c67 · outbound

This paper cites Residual Feature Distillation Network for Lightweight Image Super-Resolution.

Think Sparse, Predict Dense: Continuous Thought Machines for Image Super-Resolution Residual Feature Distillation Network for Lightweight Image Super-Resolution

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T14:10:48.485039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b4a19d4-d5c5-4a39-b45d-25372876e65f · outbound

This paper cites CATANet: Efficient content-aware token aggregation for lightweight image super-resolution.

Think Sparse, Predict Dense: Continuous Thought Machines for Image Super-Resolution CATANet: Efficient content-aware token aggregation for lightweight image super-resolution

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T14:10:48.527941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b609cf1c-4fa2-4dd5-9b86-05e770eaa487 · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

Think Sparse, Predict Dense: Continuous Thought Machines for Image Super-Resolution Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T14:10:48.550936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 876e93fe-4015-45dc-a186-7125faa7a163 · outbound

This paper cites SRFormer: Permuted self-attention for single image super-resolution.

Think Sparse, Predict Dense: Continuous Thought Machines for Image Super-Resolution SRFormer: Permuted self-attention for single image super-resolution

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T14:10:48.579536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.