Pith. sign in

Paper Citation Record · LEDGER

Polysemanticity and Capacity in Neural Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 27 inbound Pith citation observations for arXiv:2210.01892.

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

pith.paper-citation-record.v1
2210.01892 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 27 of 27 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 27 of 27 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:13:50.629906Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

4
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 70091f74-4373-4c53-8546-f2e5d3bb1072 · inbound

Towards Best Practices of Activation Patching in Language Models: Metrics and Methods cites this paper.

Towards Best Practices of Activation Patching in Language Models: Metrics and Methods Polysemanticity and Capacity in Neural Networks

Reference 110

Resolution
verified exact
arxiv_id, observed 2026-05-17T11:56:11.139782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-17T11:56:11.053897Z digest=sha256:a7ba89df10fffa8d83dea841132d1a3857f940307a989fcd0483163d1c20ba7d

Observation f6c6890b-db6f-4ef9-b548-0490b1be17a4 · inbound

A Closer Look at Multimodal Representation Collapse cites this paper.

A Closer Look at Multimodal Representation Collapse Polysemanticity and Capacity in Neural Networks

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-07T13:13:50.629906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:13:50.629906Z digest=sha256:044bde88a9827b40954bdb69774473cb1544e1d981dc5da1a5462257fbc73c8d

Observation e645ddab-5db0-4af7-bacd-bae307667907 · inbound

Localizing Persona Representations in LLMs cites this paper.

Localizing Persona Representations in LLMs Polysemanticity and Capacity in Neural Networks

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T12:25:33.728567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:25:33.728567Z digest=sha256:b9d9bfe5cc0e6d8184151c6493cdbbd447279a4fd0b40daeda4473162f7a3453

Observation b4c88b24-1836-475f-afd1-59566a50a3d1 · inbound

DCN^2: Interplay of Implicit Collision Weights and Explicit Cross Layers for Large-Scale Recommendation cites this paper.

DCN^2: Interplay of Implicit Collision Weights and Explicit Cross Layers for Large-Scale Recommendation Polysemanticity and Capacity in Neural Networks

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T23:10:38.959206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:10:38.959206Z digest=sha256:b86bc65fc0e31784c4076bce3686043a63dbdcd15f8c0ac4c770cea8a6a8a7cd

Observation 881f5796-2c70-4e7c-8395-272972d4f4c1 · inbound

Compressed Computation: Dense Circuits in a Toy Model of the Universal-AND Problem cites this paper.

Compressed Computation: Dense Circuits in a Toy Model of the Universal-AND Problem Polysemanticity and Capacity in Neural Networks

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T17:53:55.368683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:53:55.368683Z digest=sha256:6fc3dc28c87847ea25a7a81f06de57111b905fca457ead7fc8bd0ad530d588b2

Observation cc129477-c43d-4248-a8a0-a744e98057ff · inbound

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning cites this paper.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Polysemanticity and Capacity in Neural Networks

Reference 134

Resolution
unresolved
no resolver link, observed 2026-08-06T14:06:51.246973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:06:51.246973Z digest=sha256:2b861457fd14f631b42484a4eb75fb0ad54139cbe4e0c6c8a0fe85156c31959d

Observation 9906b6d2-217a-4617-a6bc-79b3c55b5978 · inbound

How Causal Abstraction Underpins Computational Explanation cites this paper.

How Causal Abstraction Underpins Computational Explanation Polysemanticity and Capacity in Neural Networks

Reference 93

Resolution
unresolved
no resolver link, observed 2026-08-05T20:08:42.380315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T20:08:42.380315Z digest=sha256:cf3773d07ddd6747b7ef57763fbeae0de93128a20341495c04efa82243cc1fcd

Observation dd19aae6-2d35-4514-88d1-a725bd6b083a · inbound

Expand Neurons, Not Parameters cites this paper.

Expand Neurons, Not Parameters Polysemanticity and Capacity in Neural Networks

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-04T11:33:16.977876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T11:33:16.977876Z digest=sha256:c00ee313886f94a970af5c9608227674d15a5350efeb8c0e410c49a193c68b15

Observation c0f8b374-d813-46a4-a3ac-c97ae9ac619c · inbound

Adversarial Attacks Leverage Interference Between Features in Superposition cites this paper.

Adversarial Attacks Leverage Interference Between Features in Superposition Polysemanticity and Capacity in Neural Networks

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-04T10:08:54.764366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:08:54.764366Z digest=sha256:6d54cfb5cc4f7bbc88feee9368e8d118bdf66c1e5b32b03ccad3a4c6795a8b6a

Observation 2e18cf29-c553-4e2f-8fe1-d860bb82aa99 · inbound

Explainability of Large Language Models: Opportunities and Challenges toward Generating Trustworthy Explanations cites this paper.

Explainability of Large Language Models: Opportunities and Challenges toward Generating Trustworthy Explanations Polysemanticity and Capacity in Neural Networks

Reference 99

Resolution
unresolved
no resolver link, observed 2026-08-04T09:08:58.319230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T09:08:58.319230Z digest=sha256:24be523cfd2a7a0c245fe95f5ea1b927fd82416a420e929bfde6cbb0dad77fc8

Observation 7de981cb-c30e-4e39-ac2a-3cb0bcf792e4 · inbound

CHiQPM: Calibrated Hierarchical Interpretable Image Classification cites this paper.

CHiQPM: Calibrated Hierarchical Interpretable Image Classification Polysemanticity and Capacity in Neural Networks

Reference 54

Resolution
metadata mismatch
arxiv_id, observed 2026-05-17T04:29:02.011975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-17T04:24:33.101394Z digest=sha256:e913c7b0e05cfe7edff145f45e95cfa91f7880bcb25a7b2c7aec2413188cb01f

Observation a9b5c050-3d04-40bb-9bbe-bd49d12e7344 · inbound

Geometric Limits of Knowledge Distillation: A Minimum-Width Theorem via Superposition Theory cites this paper.

Geometric Limits of Knowledge Distillation: A Minimum-Width Theorem via Superposition Theory Polysemanticity and Capacity in Neural Networks

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-13T17:08:01.740854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T16:54:55.296405Z digest=sha256:05706e431622c22ebe16c1a192ba3188e060247431eba89e7cecdaa558cdc6f5

Observation 107f1817-b263-4c77-9a76-f13b61a56e11 · inbound

Concepts Whisper While Syntax Shouts: Spectral Anti-Concentration and the Dual Geometry of Transformer Representations cites this paper.

Concepts Whisper While Syntax Shouts: Spectral Anti-Concentration and the Dual Geometry of Transformer Representations Polysemanticity and Capacity in Neural Networks

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-05-11T16:51:08.315210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-09T14:42:36.036836Z digest=sha256:8fff5479dc5cea2bdaaa34569ec8a072681122de4d83df5f0b97085a90dea50c

Observation d4e892b7-542f-4bf1-84c9-66543efa069d · inbound

Bucketing the Good Apples: A Method for Diagnosing and Improving Causal Abstraction cites this paper.

Bucketing the Good Apples: A Method for Diagnosing and Improving Causal Abstraction Polysemanticity and Capacity in Neural Networks

Reference 19

Resolution
metadata mismatch
arxiv_id, observed 2026-05-09T06:00:36.284977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-08T19:12:30.627633Z digest=sha256:febb095d5b88d7d0c58bc2fb7ca69b15cd8bed16c8a36de1e9c1320fbd0f4154

Observation 63b3f8a4-c1a1-4501-a48c-92815d12865b · inbound

Structural Instability of Feature Composition cites this paper.

Structural Instability of Feature Composition Polysemanticity and Capacity in Neural Networks

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-10T06:41:36.514882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T06:40:00.507484Z digest=sha256:ad1cad526dbdd917a130812c9cf73ed57551822cabd8dec920132e8efdac230b

Observation 1408ede1-6a37-4ddf-8f02-11c9c6a18260 · inbound

WriteSAE: Sparse Autoencoders for Recurrent State cites this paper.

WriteSAE: Sparse Autoencoders for Recurrent State Polysemanticity and Capacity in Neural Networks

Reference 91

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T20:59:28.770938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-14T20:53:40.666929Z digest=sha256:c01f0458fd6dca335d91233ec37e4c22a5b321634b2b54f59e42df4bc3ed5154

Observation 0e954b29-044e-4143-af3e-9a6f1bcb6f15 · inbound

WriteSAE: Sparse Autoencoders for Recurrent State cites this paper.

WriteSAE: Sparse Autoencoders for Recurrent State Polysemanticity and Capacity in Neural Networks

Reference 91

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T04:59:45.283028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-15T04:59:11.877068Z digest=sha256:77ff3a040ab413a062266dd921b47d2b7f096e2c32dfe61023cd3778ddc532a3

Observation 4be3aa81-0e14-4e56-b76c-9c565556ced6 · inbound

WriteSAE: Sparse Autoencoders for Recurrent State cites this paper.

WriteSAE: Sparse Autoencoders for Recurrent State Polysemanticity and Capacity in Neural Networks

Reference 91

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T21:53:47.258320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-20T21:49:47.934339Z digest=sha256:694d1d7750cd07d9898f55333795d549fd6f3eb03c6cbb89918dd21c77a78334

Observation d0078605-1601-4ced-85d8-c2a0e669e333 · inbound

WriteSAE: Sparse Autoencoders for Recurrent State cites this paper.

WriteSAE: Sparse Autoencoders for Recurrent State Polysemanticity and Capacity in Neural Networks

Reference 37

Resolution
metadata mismatch
arxiv_id, observed 2026-05-21T07:49:50.197144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-21T07:46:41.159688Z digest=sha256:807fef537234191d7fc0bd41d9e0248c550ee314f18455bb3ef24c4bb9493d51

Observation e6764dd1-faba-45e4-a7b2-dff545638db2 · inbound

Correcting Influence: Unboxing LLM Outputs with Orthogonal Latent Spaces cites this paper.

Correcting Influence: Unboxing LLM Outputs with Orthogonal Latent Spaces Polysemanticity and Capacity in Neural Networks

Reference 157

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T20:17:55.347084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-14T20:17:01.224864Z digest=sha256:b85e06561f8faa4bde9bc204c9bd26621092986adc30763544c51171f2dc66ea

Observation 94f10e37-3a19-4534-8432-9103f2593762 · inbound

Steered Generation via Gradient-Based Optimization on Sparse Query Features cites this paper.

Steered Generation via Gradient-Based Optimization on Sparse Query Features Polysemanticity and Capacity in Neural Networks

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:36:40.325635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-25T05:31:29.510639Z digest=sha256:17b863a06f0673e8312e58a8990b8dba6bd50b1a0fae744bd233ed1eb441b92d

Observation ae5147c2-b29c-420b-a62d-7a9bbc0918a5 · inbound

Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet cites this paper.

Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet Polysemanticity and Capacity in Neural Networks

Reference 65

Resolution
verified exact
arxiv_id, observed 2026-06-29T07:53:13.500422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T07:50:04.813379Z digest=sha256:1f36c9287ec0f77b4ba28ad57f8ee055f8730f843617e6826b26198756b05891

Observation 4ca6bb2d-7386-43f8-baaf-d0a74c342e07 · inbound

Interpretability Without Tradeoffs: Disentangling Polysemanticity At Equal Predictive Performance cites this paper.

Interpretability Without Tradeoffs: Disentangling Polysemanticity At Equal Predictive Performance Polysemanticity and Capacity in Neural Networks

Reference 56

Resolution
verified exact
arxiv_id, observed 2026-06-29T00:12:50.630036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T23:13:11.313837Z digest=sha256:4f956fff42c9f13a2dc9c2b3d48347478738b0fd3887f422788df9eb0eb856d4

Observation 5e341244-26b1-4e8f-898b-c750cac4c92e · inbound

Neuron Populations Exhibit Divergent Selectivity with Scale cites this paper.

Neuron Populations Exhibit Divergent Selectivity with Scale Polysemanticity and Capacity in Neural Networks

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-07-02T02:36:26.811006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T10:49:48.975614Z digest=sha256:50a88ad0c69bd9a7aa4000787cf113d88f6ff425616e43ec99c0c6e3eec427f1

Observation dd20fc33-f153-46f2-a4fc-6192ebc63e4a · inbound

SAERec: Constructing Fine-grained Interpretable Intents Priors via Sparse Autoencoders for Recommendation cites this paper.

SAERec: Constructing Fine-grained Interpretable Intents Priors via Sparse Autoencoders for Recommendation Polysemanticity and Capacity in Neural Networks

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-07-04T02:39:25.093980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T19:29:52.132997Z digest=sha256:35fdc675dc604c3659ca053b53c35fb9b9572897b76d5f3097d61c961c76b2ed

Observation 1f7c149d-6347-42e6-afe3-e08f9ee48b99 · inbound

From Weights to Features: SAE-Guided Activation Regularization for LLM Continual Learning cites this paper.

From Weights to Features: SAE-Guided Activation Regularization for LLM Continual Learning Polysemanticity and Capacity in Neural Networks

Reference 29

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T13:09:50.223505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-26T05:31:36.501753Z digest=sha256:57d8f2262647075c85a4451b2da7a21a9e2db6182bf18c28c4094d7bcaa6ac1a

Observation 12c45481-cde0-4def-98ca-5709dfeab55d · inbound

PairSAE: Mechanistic Interpretability from Pair Representations in Protein Co-Folding cites this paper.

PairSAE: Mechanistic Interpretability from Pair Representations in Protein Co-Folding Polysemanticity and Capacity in Neural Networks

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-07-01T18:55:58.719403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T01:24:01.833060Z digest=sha256:a95423261457dfac9226f227dd7c43730a4ca073e5cc7665929ad57351beed11