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Paper Citation Record · LEDGER

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data

As of 9 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2607.20970.

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

pith.paper-citation-record.v1
2607.20970 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T08:57:44.341137Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

45 of 45 outbound references displayed

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  • verified fuzzy0
  • unresolved37
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fba9191c-dbba-40ef-8153-994ca2c51819 · outbound

This paper cites Ainsworth, O.

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Ainsworth, O

Reference 1

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This paper cites BallesterRipoll, P.

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data BallesterRipoll, P

Reference 2

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Observation c2c7a0b5-02c5-441c-abf4-0d19a87d3eb5 · outbound

This paper cites Ben-Shabat, C.

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Ben-Shabat, C

Reference 3

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This paper cites DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data.

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data

Reference 4

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This paper cites Gadirov, Q.

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Gadirov, Q

Reference 5

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This paper cites Gobbetti, J.

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Gobbetti, J

Reference 6

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From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Unresolved cited work

Reference 7

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This paper cites Han and C.

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Han and C

Reference 8

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This paper cites Han and C.

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Han and C

Reference 9

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This paper cites Han and C.

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Han and C

Reference 10

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This paper cites Han and C.

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Han and C

Reference 11

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This paper cites Han and F.

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Han and F

Reference 12

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From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Unresolved cited work

Reference 13

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From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Unresolved cited work

Reference 14

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From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Hoang, B

Reference 15

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From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data LoRA: Low-Rank Adaptation of Large Language Models

Reference 16

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Observation 9ba86aab-1bd4-4b7a-ad8e-0c5e17de22b7 · outbound

This paper cites Krizhevsky, I.

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Krizhevsky, I

Reference 17

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This paper cites SZ3: A Modular Framework for Composing Prediction-Based Error-Bounded Lossy Compressors.

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data SZ3: A Modular Framework for Composing Prediction-Based Error-Bounded Lossy Compressors

Reference 18

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From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Lindstrom

Reference 19

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From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Müller, A

Reference 23

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From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Nowlan and G

Reference 24

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From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Learning Transferable Visual Models From Natural Language Supervision

Reference 25

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From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs

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From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Sahoo, Y

Reference 27

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Reference 28

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From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Sitzmann, E

Reference 29

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Reference 30

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From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Tang and C

Reference 32

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From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Weiss, M

Reference 33

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From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Weiss, M

Reference 34

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Reference 35

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From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Y ang, K

Reference 39

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This paper cites Zhang, P.

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Zhang, P

Reference 40

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This paper cites Kimi Linear: An Expressive, Efficient Attention Architecture.

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Kimi Linear: An Expressive, Efficient Attention Architecture

Reference 41

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This paper cites Zhao, C.-C.

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Zhao, C.-C

Reference 42

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This paper cites Zhenxing and D.

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Zhenxing and D

Reference 43

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Reference 44

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This paper cites an unresolved cited work.

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data Unresolved cited work

Reference 2025

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