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Paper Citation Record · LEDGER

On the Binding Problem in Artificial Neural Networks

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 35 inbound Pith citation observations for arXiv:2012.05208.

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

pith.paper-citation-record.v1
2012.05208 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 35 of 35 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 35 of 35 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:12:33.261612Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T10:47:02.144352Z

Reference resolution

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External citation measurements

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Outbound references

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Pith citing papers

Observation b26e6d97-12de-45fa-ba6a-f3e240ee7941 · inbound

Efficient Object-centric Representation Learning with Pre-trained Geometric Prior cites this paper.

Efficient Object-centric Representation Learning with Pre-trained Geometric Prior On the Binding Problem in Artificial Neural Networks

Reference 1

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source=pdf_text observed=2026-08-11T14:14:48.222524Z digest=sha256:c127d0230a3daf992f4c02a6a884cca5dfae751750c8b8a8f4084f3619a1f625

Observation 4a44bd1c-88cb-46bb-8d40-209e5926a676 · inbound

Temporally Consistent Object-Centric Learning by Contrasting Slots cites this paper.

Temporally Consistent Object-Centric Learning by Contrasting Slots On the Binding Problem in Artificial Neural Networks

Reference 15

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source=pdf_text observed=2026-08-11T12:25:09.992634Z digest=sha256:fbcc1e8861b53efd53f8cfa9d747717b75c5432584d6f7aa220a14ceace3c7b0

Observation 88fd49af-6822-4a3a-a53e-a5b098593b5a · inbound

Leveraging Color Channel Independence for Improved Unsupervised Object Detection cites this paper.

Leveraging Color Channel Independence for Improved Unsupervised Object Detection On the Binding Problem in Artificial Neural Networks

Reference 29

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source=arxiv_source observed=2026-08-11T11:38:15.924350Z digest=sha256:e4443efdc07919d0f4a99dc8b8c4d1fe2e98cd5838ce0acdabe1293fb72df07b

Observation fc04ac6f-ade1-48f7-9796-d129c8baf5ad · inbound

Dreamweaver: Learning Compositional World Models from Pixels cites this paper.

Dreamweaver: Learning Compositional World Models from Pixels On the Binding Problem in Artificial Neural Networks

Reference 11

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source=pdf_text observed=2026-08-10T15:23:54.878969Z digest=sha256:1e02cb2c69f08117836a9a4764949de066e85d3217775a45641f64c709d01c44

Observation 4fe57114-30c0-438b-a687-69ec2034d1be · inbound

Towards Conscious Service Robots cites this paper.

Towards Conscious Service Robots On the Binding Problem in Artificial Neural Networks

Reference 36

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source=pdf_text observed=2026-08-10T14:33:14.310464Z digest=sha256:74d6f6558e02a3a0088a8a7edc4bef4d8d92c45096f9747ba21edd7344e6d16c

Observation e2065596-b1ed-4559-ab4b-85a10bbaff67 · inbound

Slot-Guided Adaptation of Pre-trained Diffusion Models for Object-Centric Learning and Compositional Generation cites this paper.

Slot-Guided Adaptation of Pre-trained Diffusion Models for Object-Centric Learning and Compositional Generation On the Binding Problem in Artificial Neural Networks

Reference 4

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source=pdf_text observed=2026-08-10T13:56:51.010376Z digest=sha256:27bd8ee14cc3936f325fc0d2fd8da3b00d07aeb12776c1a1f6116a19f870cb6c

Observation 7b44e9c7-4e26-46b0-b1fa-80597824ccb5 · inbound

PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning cites this paper.

PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning On the Binding Problem in Artificial Neural Networks

Reference 3

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source=pdf_text observed=2026-08-08T12:16:28.641413Z digest=sha256:3cea807a24d56a18e8967f80f64200d5557e887e158b416abba8b42e4df460b2

Observation c26f73dc-fac5-4a37-a6f0-9c944ce8e50f · inbound

Object Learning and Robust 3D Reconstruction cites this paper.

Object Learning and Robust 3D Reconstruction On the Binding Problem in Artificial Neural Networks

Reference 57

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source=arxiv_source observed=2026-08-16T11:12:33.261612Z digest=sha256:d672cc0ce835c4da2551a45fd82c95cab303080d4ed9048942ed808df46f97b7

Observation 0e5564dc-a98e-4c07-ade8-ff7a63deebf9 · inbound

Hierarchical Compact Clustering Attention (COCA) for Unsupervised Object-Centric Learning cites this paper.

Hierarchical Compact Clustering Attention (COCA) for Unsupervised Object-Centric Learning On the Binding Problem in Artificial Neural Networks

Reference 22

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source=pdf_text observed=2026-08-16T01:08:23.880136Z digest=sha256:38d23f1677a7e5dd944c779d991154b455899134de8e2a7a389d5b31a762fe5b

Observation b47851a0-3144-4bcb-ad55-f4551a35427b · inbound

Efficient Sensorimotor Learning for Open-world Robot Manipulation cites this paper.

Efficient Sensorimotor Learning for Open-world Robot Manipulation On the Binding Problem in Artificial Neural Networks

Reference 10

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source=pdf_text observed=2026-08-15T23:27:51.292611Z digest=sha256:74bf8727d1ba6a7b5e7390810efa412ea7ffbeab66207e84727719169140205f

Observation 3055c856-1ccc-4b15-b0d3-ec42e806b51b · inbound

Object-Centric Representations Improve Policy Generalization in Robot Manipulation cites this paper.

Object-Centric Representations Improve Policy Generalization in Robot Manipulation On the Binding Problem in Artificial Neural Networks

Reference 14

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source=pdf_text observed=2026-08-15T21:03:27.389037Z digest=sha256:cffd29e418f26a57486717e3d143d73a761c988def6a60b5447254bdb93c03df

Observation e3776150-f756-4d3b-a373-1d873a4e8f5f · inbound

Compositional Scene Understanding through Inverse Generative Modeling cites this paper.

Compositional Scene Understanding through Inverse Generative Modeling On the Binding Problem in Artificial Neural Networks

Reference 28

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source=arxiv_source observed=2026-08-07T13:31:05.704461Z digest=sha256:3e253db8b810ac2b24f7444e6cff775819c289113715644078dc5564c28383bb

Observation 0309a523-9316-4d98-ab63-e4b51466e575 · inbound

Behavioural vs. Representational Systematicity in End-to-End Models: An Opinionated Survey cites this paper.

Behavioural vs. Representational Systematicity in End-to-End Models: An Opinionated Survey On the Binding Problem in Artificial Neural Networks

Reference 35

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source=arxiv_source observed=2026-08-07T10:46:20.015823Z digest=sha256:4bc77f70dca29e39433317428aa58b8581731fd2232b36323eab2809d4743222

Observation 18a7467b-ee84-450f-baab-cd770899d3de · inbound

Identifiable Object Representations under Spatial Ambiguities cites this paper.

Identifiable Object Representations under Spatial Ambiguities On the Binding Problem in Artificial Neural Networks

Reference 25

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source=arxiv_source observed=2026-08-07T05:32:52.732009Z digest=sha256:743e707a46d77eb4592faf04ee4cb2dc8684765f7a7f58f57591900b9b1d883c

Observation 4d67c275-52cb-48ca-a144-105acd32f5ce · inbound

Bound by semanticity: universal laws governing the generalization-identification tradeoff cites this paper.

Bound by semanticity: universal laws governing the generalization-identification tradeoff On the Binding Problem in Artificial Neural Networks

Reference 6

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source=arxiv_source observed=2026-08-07T11:57:35.420456Z digest=sha256:3c0080c6c02fdce893cdcaa85212dff42a7724d2e5b711b5a540ab26acc1e10c

Observation 58c9c3fa-53e4-411f-a45c-a0f2267e8589 · inbound

Compositional Video Synthesis by Temporal Object-Centric Learning cites this paper.

Compositional Video Synthesis by Temporal Object-Centric Learning On the Binding Problem in Artificial Neural Networks

Reference 22

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source=pdf_text observed=2026-08-06T13:16:44.091002Z digest=sha256:d4d119ce3c926cdca842ba98dee92f1c9a542966f3b89e36fb5c4f6b6d671536

Observation ff378eb1-8f90-4946-899c-8b3a68a068f3 · inbound

Mechanistic Independence: A Principle for Identifiable Disentangled Representations cites this paper.

Mechanistic Independence: A Principle for Identifiable Disentangled Representations On the Binding Problem in Artificial Neural Networks

Reference 7

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arxiv_id, observed 2026-05-18T13:32:37.829929Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-18T13:31:41.141199Z digest=sha256:381f2fe7cdcb6cb2632179d2e950fbd0bfe7a07dd4f98a34c761ac515d4b8970

Observation 1039267a-fc1c-459c-9b2d-8ce685f1be25 · inbound

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis cites this paper.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis On the Binding Problem in Artificial Neural Networks

Reference 3

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arxiv_id, observed 2026-05-17T02:18:52.550941Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-17T02:17:15.595874Z digest=sha256:585b4a6877fc41e8b5be4be51c60a1275a19c51a9bce8c83d37947f7447062af

Observation 2438309f-3db9-48ab-bdb7-beee62627073 · inbound

Dynamics Reveals Structure: Challenging the Linear Propagation Assumption cites this paper.

Dynamics Reveals Structure: Challenging the Linear Propagation Assumption On the Binding Problem in Artificial Neural Networks

Reference 446

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source=pdf_text observed=2026-08-03T07:01:22.893979Z digest=sha256:fcb9ecc957c347726b9739e2f4323eb0cafca5d8d7f9c057061174d0614f49c9

Observation 4c141525-a713-4599-9513-90f9d508c917 · inbound

ORGAN: Object-Centric Representation Learning using Cycle Consistent Generative Adversarial Networks cites this paper.

ORGAN: Object-Centric Representation Learning using Cycle Consistent Generative Adversarial Networks On the Binding Problem in Artificial Neural Networks

Reference 2022

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source=pdf_text observed=2026-08-02T19:30:49.121270Z digest=sha256:25a31672bb6c6d140ba07fbfd5c6342cd59eb56f6726d25044c8383f9fdc2b86

Observation 75c87af2-1d6a-485c-b76b-36250db3c1fb · inbound

Human-like Object Grouping in Self-supervised Vision Transformers cites this paper.

Human-like Object Grouping in Self-supervised Vision Transformers On the Binding Problem in Artificial Neural Networks

Reference 17

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source=pdf_text observed=2026-07-14T21:34:48.709465Z digest=sha256:88bd9990533be93e7c2d5d2c2f7e87ffc90ab4e383dcce7a48716af9ff18e091

Observation aac22bac-874f-4156-9d01-7c72e9980ef8 · inbound

ActionParty: Multi-Subject Action Binding in Generative Video Games cites this paper.

ActionParty: Multi-Subject Action Binding in Generative Video Games On the Binding Problem in Artificial Neural Networks

Reference 23

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source=pdf_text observed=2026-08-03T00:56:26.582606Z digest=sha256:6176eb802c0c445602acf6491e530171cec3dac6ea754821a0069c0d9970c4bd

Observation 8cfd29d0-6f6a-47f4-82c4-d64af4f9bc0b · inbound

Kuramoto Oscillatory Phase Encoding: Neuro-inspired Synchronization for Improved Learning Efficiency cites this paper.

Kuramoto Oscillatory Phase Encoding: Neuro-inspired Synchronization for Improved Learning Efficiency On the Binding Problem in Artificial Neural Networks

Reference 5

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arxiv_id, observed 2026-05-11T07:55:59.173494Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-10T16:55:00.887859Z digest=sha256:15915de57a6650d00876ddc6b8632a336a0b447945e53a8ec2147cb68cdb0d8b

Observation 2e82f48f-3a03-426d-9e96-d4a5a0b45236 · inbound

I Walk the Line: Examining the Role of Gestalt Continuity in Object Binding for Vision Transformers cites this paper.

I Walk the Line: Examining the Role of Gestalt Continuity in Object Binding for Vision Transformers On the Binding Problem in Artificial Neural Networks

Reference 8

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arxiv_id, observed 2026-05-11T07:56:01.415432Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-10T16:53:04.513790Z digest=sha256:7033ef0fc12aa84bd2d64b2555ebef45725e912728bead99a751e930bb01492e

Observation 3b727658-97af-41d4-80c9-bfbe628a0e07 · inbound

Deep Sprite-based Image Models: An Analysis cites this paper.

Deep Sprite-based Image Models: An Analysis On the Binding Problem in Artificial Neural Networks

Reference 4

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arxiv_id, observed 2026-05-11T12:51:05.429031Z

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Observation 3720b665-fa1a-430a-9438-59f1e5151deb · inbound

From Cortical Synchronous Rhythm to Brain Inspired Learning Mechanism: An Oscillatory Spiking Neural Network with Time-Delayed Coordination cites this paper.

From Cortical Synchronous Rhythm to Brain Inspired Learning Mechanism: An Oscillatory Spiking Neural Network with Time-Delayed Coordination On the Binding Problem in Artificial Neural Networks

Reference 14

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arxiv_id, observed 2026-05-11T16:26:06.404441Z

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source=arxiv_source observed=2026-05-09T17:07:13.068152Z digest=sha256:0be3c77bbcfe13693213e160c5bb24aeab7c663009ca815caa1618ab24851665

Observation e49b4746-1763-438b-b033-8c455794c4ab · inbound

Learning to Theorize the World from Observation cites this paper.

Learning to Theorize the World from Observation On the Binding Problem in Artificial Neural Networks

Reference 273

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arxiv_id, observed 2026-05-11T23:21:37.951382Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-07T17:15:43.429602Z digest=sha256:785f3a5c0b4edcaab82f6edcca2052a828725535fb161541182a17fa5ff7c0ce

Observation c3006028-a669-4575-bb59-4705168d0895 · inbound

SYNCR: A Cross-Video Reasoning Benchmark with Synthetic Grounding cites this paper.

SYNCR: A Cross-Video Reasoning Benchmark with Synthetic Grounding On the Binding Problem in Artificial Neural Networks

Reference 7

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arxiv_id, observed 2026-05-12T08:36:26.498759Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-12T00:53:35.188721Z digest=sha256:717130d6d4a20fa29d44accc7c11636fe26f036056020d8cf9ed10ef7d29c023

Observation 587fc147-d28f-40c7-a90e-f9b8f94a985d · inbound

Slot-MPC: Goal-Conditioned Model Predictive Control with Object-Centric Representations cites this paper.

Slot-MPC: Goal-Conditioned Model Predictive Control with Object-Centric Representations On the Binding Problem in Artificial Neural Networks

Reference 2

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arxiv_id, observed 2026-06-30T21:05:04.484379Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-30T20:59:27.332992Z digest=sha256:2131633fb8259a1fdb9523f81f49348eb2b845d78ccb18b65725454096dab3df

Observation 79c5897d-b7b3-4ea6-a925-258d25434fbf · inbound

No Epoch Like the Present: Robust Climate Emulation Requires Out-of-Distribution Generalisation cites this paper.

No Epoch Like the Present: Robust Climate Emulation Requires Out-of-Distribution Generalisation On the Binding Problem in Artificial Neural Networks

Reference 72

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verified exact
arxiv_id, observed 2026-05-22T08:21:16.919226Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-22T08:19:18.319910Z digest=sha256:589b3a15287f932260234de359fde33e87c029ad9433ae6cf8012a6f148f5855

Observation 5de74b33-d227-42e6-b19e-043da01eae95 · inbound

How can embedding models bind concepts? cites this paper.

How can embedding models bind concepts? On the Binding Problem in Artificial Neural Networks

Reference 2

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arxiv_id, observed 2026-07-01T19:16:00.009076Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-28T23:05:16.132396Z digest=sha256:6e0ebd2f091ff552f54a08fd60c999077d8424457d2a249416869e9d272ecba7

Observation 29a7e6b2-ccc6-4370-b80a-11c6c724e13a · inbound

Dual-State Slot Attention: Decoupling Appearance and Identity for Video Object-Centric Learning cites this paper.

Dual-State Slot Attention: Decoupling Appearance and Identity for Video Object-Centric Learning On the Binding Problem in Artificial Neural Networks

Reference 43

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arxiv_id, observed 2026-07-03T10:48:02.773669Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-27T09:49:52.527042Z digest=sha256:54cdd537117a87ce2632d4191ff58aead72afae28bad3b092baf99cb75c095a4

Observation 501717e0-0d6e-4ded-9145-3f7b4c729afd · inbound

Input Pathways Shape Few-Shot, Not Zero-Shot, Binding in Tiny Transformers: A Fully-Enumerable Study cites this paper.

Input Pathways Shape Few-Shot, Not Zero-Shot, Binding in Tiny Transformers: A Fully-Enumerable Study On the Binding Problem in Artificial Neural Networks

Reference 6

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source=pdf_text observed=2026-07-11T11:22:48.469230Z digest=sha256:628a0ccc94baca592c7f2b7a0a6a7a4b62d3a751689fec67f5d321dcff4ba066

Observation de4de2e9-623f-4af9-b67f-756fba9baa7f · inbound

HSA: Hierarchical Slot Attention for Multi-granularity Scene-Decomposition cites this paper.

HSA: Hierarchical Slot Attention for Multi-granularity Scene-Decomposition On the Binding Problem in Artificial Neural Networks

Reference 15

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local_arxiv, observed 2026-07-10T10:47:02.145498Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-07-10T10:40:18.020182Z digest=sha256:74d1be0cfdad7dc41d77e75c5b78c778ae3635ba6e94b58275c52d0996956dc6

Observation ae2a48cb-f7cd-47bf-bf3c-d1e202652443 · inbound

EditCLEVR: A Paired-Scene Intervention Benchmark for Compositional Faithfulness of Object-Centric Representations cites this paper.

EditCLEVR: A Paired-Scene Intervention Benchmark for Compositional Faithfulness of Object-Centric Representations On the Binding Problem in Artificial Neural Networks

Reference 6

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no resolver link, observed 2026-08-01T18:25:36.769948Z

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source=arxiv_source observed=2026-08-01T18:25:36.769948Z digest=sha256:c5419357de7e47e7492422406113886a36d9f09c3da8bfcc7af383e145e7a79c