Paper Citation Record · LEDGER

Cross-Model Semantics in Representation Learning

As of 7 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 2 inbound Pith citation observations for arXiv:2508.03649.

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

pith.paper-citation-record.v1
2508.03649 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T04:22:17.756075Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T04:22:29.079282Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T06:29:37.789296Z

Reference resolution

32 of 32 outbound references displayed

verified exact5
verified fuzzy19
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b18cb7cc-8d0e-4b71-b125-8d9ab408dc96 · outbound

This paper cites Teasing Apart Architecture and Initial Weights as Sources of Inductive Bias in Neural Networks.

Cross-Model Semantics in Representation Learning Teasing Apart Architecture and Initial Weights as Sources of Inductive Bias in Neural Networks

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T04:22:15.003712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1487c88a-9b13-475a-935f-71395a8646bb · outbound

This paper cites Controlling the inductive bias of wide neural networks by modifying the kernel’s spectrum,.

Cross-Model Semantics in Representation Learning Controlling the inductive bias of wide neural networks by modifying the kernel’s spectrum,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:22:22.260685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b5bd25ba-526f-4266-a69f-265af3cf9748 · outbound

This paper cites Expressive Monotonic Neural Networks.

Cross-Model Semantics in Representation Learning Expressive Monotonic Neural Networks

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-06T04:22:19.093997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation a9b8217f-3b0f-4428-8c2c-acb5ea854cd5 · outbound

This paper cites Towards Exact Computation of Inductive Bias.

Cross-Model Semantics in Representation Learning Towards Exact Computation of Inductive Bias

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T04:22:15.233882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 125f7d68-abbc-497f-a761-6eddc3f384fd · outbound

This paper cites Optimizers Qualitatively Alter Solutions And We Should Leverage This.

Cross-Model Semantics in Representation Learning Optimizers Qualitatively Alter Solutions And We Should Leverage This

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T04:22:15.304977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d461b5d-1c0d-417a-b403-7f64070e81a0 · outbound

This paper cites Structured Transformations for Stable and Interpretable Neural Computation.

Cross-Model Semantics in Representation Learning Structured Transformations for Stable and Interpretable Neural Computation

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-06T04:22:18.959432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d8bc25a6-4e52-41e1-8212-a722553867c2 · outbound

This paper cites Understanding Learning Dynamics Through Structured Representations.

Cross-Model Semantics in Representation Learning Understanding Learning Dynamics Through Structured Representations

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-06T04:22:18.833220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 94c742c5-2f20-439e-8906-96ea55f5830b · outbound

This paper cites When representations align: Universality in represen- tation learning dynamics,.

Cross-Model Semantics in Representation Learning When representations align: Universality in represen- tation learning dynamics,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:22:22.132752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6e57b299-6423-44e8-8baf-4ec1e8a05998 · outbound

This paper cites Chemotactic motility-induced phase separation.

Cross-Model Semantics in Representation Learning Chemotactic motility-induced phase separation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T04:22:15.614382Z

Source-reported events for the cited work

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Observation 11843770-5446-470b-a0fc-595a16bded72 · outbound

This paper cites On the symmetries of deep learning models and their internal representations,.

Cross-Model Semantics in Representation Learning On the symmetries of deep learning models and their internal representations,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:22:22.031120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 3a49f9c2-83b7-40d9-8713-50c5d58cd270 · outbound

This paper cites Human alignment of neural network representations,.

Cross-Model Semantics in Representation Learning Human alignment of neural network representations,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:22:21.874234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation bcecd2e8-813c-4492-9cb7-b159958f2957 · outbound

This paper cites Towards a learning theory of representation alignment,.

Cross-Model Semantics in Representation Learning Towards a learning theory of representation alignment,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:22:21.758893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation be4b1e2c-3dd7-458e-98cd-2e27b800523c · outbound

This paper cites Connecting neural models’ latent geometries with relative geodesic representations,.

Cross-Model Semantics in Representation Learning Connecting neural models’ latent geometries with relative geodesic representations,

Reference 13

Resolution: verified exact; raw_fallback, observed 2026-08-06T04:22:18.640327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 534c3e0d-123e-4bc3-8c6b-59b872ce0dbb · outbound

This paper cites Latent space translation via semantic alignment,.

Cross-Model Semantics in Representation Learning Latent space translation via semantic alignment,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:22:21.590242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7038155d-cc5b-42da-85f5-244999836edf · outbound

This paper cites The doubly librating Plutinos.

Cross-Model Semantics in Representation Learning The doubly librating Plutinos

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T04:22:16.174692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7667fcc2-1278-48ed-a2a6-436ceb728add · outbound

This paper cites Tracing representation progression: Analyzing and enhanc- ing layer-wise similarity,.

Cross-Model Semantics in Representation Learning Tracing representation progression: Analyzing and enhanc- ing layer-wise similarity,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:22:21.469652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7670c4b3-a7cf-4f6e-9825-e61c61733c95 · outbound

This paper cites Aligning machine and human visual representations across abstraction levels,.

Cross-Model Semantics in Representation Learning Aligning machine and human visual representations across abstraction levels,

Reference 17

Resolution: verified exact; raw_fallback, observed 2026-08-06T04:22:18.328285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e8adf811-6473-42f9-ba2d-4e4118e8827a · outbound

This paper cites The neural race reduction: Dynamics of abstraction in gated networks,.

Cross-Model Semantics in Representation Learning The neural race reduction: Dynamics of abstraction in gated networks,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:22:21.308074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4d5e0db8-8c9c-4a41-b57b-a96009b3575b · outbound

This paper cites The platonic representation hypothesis,.

Cross-Model Semantics in Representation Learning The platonic representation hypothesis,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:22:21.084702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 2a044c06-b8a1-43d0-b856-3cb392f29479 · outbound

This paper cites Universal sparse autoencoders: Interpretable cross- model concept alignment,.

Cross-Model Semantics in Representation Learning Universal sparse autoencoders: Interpretable cross- model concept alignment,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T04:22:16.604665Z

Source-reported events for the cited work

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Observation 5e5fee92-59ca-480e-b59b-66d8443b1559 · outbound

This paper cites On the direct alignment of latent spaces.

Cross-Model Semantics in Representation Learning On the direct alignment of latent spaces

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:22:20.811358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ab46314f-96fa-4ead-8504-0e5c9f009dcc · outbound

This paper cites Similarity of neural network models: A survey of functional and representational measures,.

Cross-Model Semantics in Representation Learning Similarity of neural network models: A survey of functional and representational measures,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:22:20.654380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 60d9f198-788c-49fe-a9e3-077fef66b9ab · outbound

This paper cites Understanding the emergence of multimodal representation alignment,.

Cross-Model Semantics in Representation Learning Understanding the emergence of multimodal representation alignment,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T04:22:16.869825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82a53fe7-1c95-4add-b810-dd5204ca879e · outbound

This paper cites From bricks to bridges: Product of invariances to enhance latent space communication,.

Cross-Model Semantics in Representation Learning From bricks to bridges: Product of invariances to enhance latent space communication,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:22:20.461018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4b844151-1a3d-4a31-8b72-6494ffca89a9 · outbound

This paper cites Rosetta neurons: Mining the common units in a model zoo,.

Cross-Model Semantics in Representation Learning Rosetta neurons: Mining the common units in a model zoo,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:22:20.203347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7f78e153-b146-4f3b-949f-970c1407c410 · outbound

This paper cites Relative representations enable zero-shot latent space communication,.

Cross-Model Semantics in Representation Learning Relative representations enable zero-shot latent space communication,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:22:20.003561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation be5944a8-d989-445b-9f2e-5d261edae577 · outbound

This paper cites Text-to-concept (and back) via cross-model alignment,.

Cross-Model Semantics in Representation Learning Text-to-concept (and back) via cross-model alignment,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:22:19.794349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 95f17125-9871-4208-8373-fbd1602b6880 · outbound

This paper cites Equivariant deep weight space alignment,.

Cross-Model Semantics in Representation Learning Equivariant deep weight space alignment,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:22:19.588637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b64afc5f-459c-4cf1-9d75-c7df2d778d7c · outbound

This paper cites General Table Question Answering via Answer-Formula Joint Generation.

Cross-Model Semantics in Representation Learning General Table Question Answering via Answer-Formula Joint Generation

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T04:22:17.451676Z

Source-reported events for the cited work

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Observation 1e62a43e-033e-460f-9992-987aaddd3150 · outbound

This paper cites Latent functional maps,.

Cross-Model Semantics in Representation Learning Latent functional maps,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:22:19.448632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e02e974d-be4b-43c0-8fb6-b968a66df1e1 · outbound

This paper cites How do transformers learn topic structure: Towards a mechanis- tic understanding,.

Cross-Model Semantics in Representation Learning How do transformers learn topic structure: Towards a mechanis- tic understanding,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:22:19.338678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d78ac824-fe29-4aa0-909e-6b6195a82bf0 · outbound

This paper cites Git re-basin: Merging models modulo permutation symmetries,.

Cross-Model Semantics in Representation Learning Git re-basin: Merging models modulo permutation symmetries,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:22:19.221255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Pith citing papers

Observation 6ffa5912-0703-493f-9498-e0206b27f184 · inbound

Improving Q-Learning for Real-World Control: A Case Study in Series Hybrid Agricultural Tractors cites this paper.

Improving Q-Learning for Real-World Control: A Case Study in Series Hybrid Agricultural Tractors Cross-Model Semantics in Representation Learning

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T04:22:29.079282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40d5edfd-73d6-4529-a6d7-7b1a1c927d7b · inbound

A Stitch in Time Saves Nine: Preserving Policy Compatibility Under Perception Updates in End-to-End Autonomous Driving cites this paper.

A Stitch in Time Saves Nine: Preserving Policy Compatibility Under Perception Updates in End-to-End Autonomous Driving Cross-Model Semantics in Representation Learning

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-07-04T06:29:37.790899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.