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Paper Citation Record · LEDGER

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization

As of 15 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2608.13538.

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

pith.paper-citation-record.v1
2608.13538 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:41:55.529803Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

38 of 38 outbound references displayed

  • verified exact3
  • verified fuzzy13
  • unresolved21
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6e2699d7-d022-4a0c-9256-1567f0871051 · outbound

This paper cites Transformer Circuits Thread , note=.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Transformer Circuits Thread , note=

Reference 1

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T04:41:54.317294Z digest=sha256:383665032d0905ee228e826481135de05331badec6c57255061e4efff3fd5ab4

Observation 1affec27-f2d8-4ffa-8886-f18b1f4584a3 · outbound

This paper cites an unresolved cited work.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Unresolved cited work

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 31efe1f0-cfcb-4432-b791-9c682c3e44ad · outbound

This paper cites an unresolved cited work.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Unresolved cited work

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation fe654b2c-fd05-4cd5-8c53-063003ef5072 · outbound

This paper cites an unresolved cited work.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Unresolved cited work

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T04:41:54.426789Z digest=sha256:61cd10f9b3bdc4e2a1ed1699e92b6a1771d365d56e28c7c9f8aed6160aabf576

Observation d10f1e15-9cc8-41c6-9ff3-5bc1c983db4d · outbound

This paper cites Daniel and Sumers, Theodore R.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Daniel and Sumers, Theodore R

Reference 5

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T04:41:54.449148Z digest=sha256:3055a679aeaea6d65bbfe3985ea8b44f5f50251efd121bde8b4b5080e56f5eb7

Observation 76cdc4d1-e523-4d5a-92cb-1bcc510b49e9 · outbound

This paper cites 2025 , type =.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization 2025 , type =

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 476cb9b7-4c4d-48f9-962b-2a22011bb5fe · outbound

This paper cites Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T04:41:54.498329Z digest=sha256:2c10ab31c6f931cce17bc4bf742ca9e6ba927cdebca5b2836955356f19f921b8

Observation f5dcfbaf-a696-493b-97f1-ce8c3dd3259e · outbound

This paper cites 2023 , howpublished =.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization 2023 , howpublished =

Reference 8

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source=arxiv_source observed=2026-08-14T04:41:54.531167Z digest=sha256:3080b96e13fe4a5ace7726bce503c49a80bae880bb5b998dad7132e1d163b8a7

Observation 6320742b-d41c-416e-8efa-1b6bc5dbe3fd · outbound

This paper cites 2023 , url =.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization 2023 , url =

Reference 9

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 4195e83d-ec77-4e8f-b3d8-7c9158a57434 · outbound

This paper cites Proceedings of the 42nd International Conference on Machine Learning , pages =.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Proceedings of the 42nd International Conference on Machine Learning , pages =

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 588180b6-85bd-47bd-a90e-7ba7e7ffcb39 · outbound

This paper cites SAGE : An Agentic Explainer Framework for Interpreting SAE Features in Language Models.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization SAGE : An Agentic Explainer Framework for Interpreting SAE Features in Language Models

Reference 11

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Observation 7a9298e2-36de-45d9-adea-a808c1cdcd89 · outbound

This paper cites Enhancing Automated Interpretability with Output-Centric Feature Descriptions.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Enhancing Automated Interpretability with Output-Centric Feature Descriptions

Reference 12

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no resolver link, observed 2026-08-14T04:41:54.664754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 01c8ff22-c725-456e-8a1b-5e3031bed973 · outbound

This paper cites an unresolved cited work.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Unresolved cited work

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 5ac950da-78f3-4999-a59a-66216a8c8d77 · outbound

This paper cites FADE : Why Bad Descriptions Happen to Good Features.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization FADE : Why Bad Descriptions Happen to Good Features

Reference 14

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verified exact
doi, observed 2026-08-14T04:41:56.224849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T04:41:54.724441Z digest=sha256:5c1d6b8780a1892477ba85c5562100d10012440da37b508974da0878fbc06afc

Observation c760b2cc-4024-4c82-8aef-3cffbda132df · outbound

This paper cites Descriptive Collision in Sparse Autoencoder Auto-Interpretability: When One Explanation Describes Many Features.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Descriptive Collision in Sparse Autoencoder Auto-Interpretability: When One Explanation Describes Many Features

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-08-14T04:41:57.114752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T04:41:54.754751Z digest=sha256:30830af3ab4bb3eb1f4d2a4955a9a47a2c19fa676a4dc5bfd93c4a41efbde250

Observation d43e5a3f-9a00-40d9-a347-601dbbbf691a · outbound

This paper cites 2018 , editor =.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization 2018 , editor =

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 768b4613-b216-46da-901a-a87a4a4cb232 · outbound

This paper cites Unveiling L anguage- S pecific F eatures in L arge L anguage M odels via S parse A utoencoders.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Unveiling L anguage- S pecific F eatures in L arge L anguage M odels via S parse A utoencoders

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c2eeceb1-1ba3-4953-9fda-5afef2b1cf1e · outbound

This paper cites L ingua L ens: Towards Interpreting Linguistic Mechanisms of Large Language Models via Sparse Auto-Encoder.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization L ingua L ens: Towards Interpreting Linguistic Mechanisms of Large Language Models via Sparse Auto-Encoder

Reference 18

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no resolver link, observed 2026-08-14T04:41:54.845527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b83570eb-2eae-48dd-97b3-cd47d49aeeb1 · outbound

This paper cites Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering

Reference 19

Resolution
verified exact
doi, observed 2026-08-14T04:41:55.945074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation d255b05a-e7cc-4558-a109-79af584feea0 · outbound

This paper cites Self-explaining.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Self-explaining

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 2238c825-2094-43ce-95ac-c69dbd42d4c5 · outbound

This paper cites SAEExplainer: Interpreting SAE Features with Activation-Guided Preference Optimization.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization SAEExplainer: Interpreting SAE Features with Activation-Guided Preference Optimization

Reference 21

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local_arxiv, observed 2026-08-14T04:41:56.954831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 3f6c9d8c-333c-4211-a6a5-9788c7e19745 · outbound

This paper cites 2024 , editor =.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization 2024 , editor =

Reference 22

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 39574116-ec61-47b0-b09d-b20d87a03b61 · outbound

This paper cites 2024 , editor =.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization 2024 , editor =

Reference 23

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 4a4f8d2e-c8d3-4581-b4a5-fe8802221e59 · outbound

This paper cites Transformer Circuits Thread , year=.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Transformer Circuits Thread , year=

Reference 24

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Unavailable: canonical work link unavailable.

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Observation 5092462b-565f-4b91-8cec-2d76fb38ec55 · outbound

This paper cites an unresolved cited work.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Unresolved cited work

Reference 25

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 569f25b6-c647-47f0-bead-2d38d5e60ca3 · outbound

This paper cites CoRR , volume =.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization CoRR , volume =

Reference 26

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Unavailable: canonical work link unavailable.

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Observation 483cb5e1-4ead-4d12-a16e-c0d63c2cf6be · outbound

This paper cites Li and Zifan Carl Guo and Vincent Huang and Jacob Steinhardt and Jacob Andreas , year=.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Li and Zifan Carl Guo and Vincent Huang and Jacob Steinhardt and Jacob Andreas , year=

Reference 27

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Unavailable: canonical work link unavailable.

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Observation 5fb3e48c-4a56-42a0-a9c9-1cb9e7d8781f · outbound

This paper cites and Ameisen, Emmanuel and Chen, James and Kishylau, Dzmitry and Pearce, Adam and Tarng, Julius and Wu, Alex and Wu, Jeff and Zhang, Yang and Ziegler, Daniel M.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization and Ameisen, Emmanuel and Chen, James and Kishylau, Dzmitry and Pearce, Adam and Tarng, Julius and Wu, Alex and Wu, Jeff and Zhang, Yang and Ziegler, Daniel M

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3b62a1a8-7413-4acc-8cb4-be4dda11dbcf · outbound

This paper cites 2025 , url=.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization 2025 , url=

Reference 29

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 6950fd78-e937-44d4-9594-e8bb29e2a411 · outbound

This paper cites Quantifying Feature Space Universality Across Large Language Models via Sparse Autoencoders.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Quantifying Feature Space Universality Across Large Language Models via Sparse Autoencoders

Reference 30

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 40d07c89-e7e8-4d27-b8c2-1cad1c56d298 · outbound

This paper cites Transferring.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Transferring

Reference 31

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T04:41:55.313112Z digest=sha256:8ff6f31c40a2487d240d87ef2b733bd9bde8cc2c3d2cc4cabd3ce1cf8ec9997f

Observation 1f0df701-05fd-44c8-80f0-bef1d7d961e0 · outbound

This paper cites Word Embeddings Are Steers for Language Models.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Word Embeddings Are Steers for Language Models

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T04:41:55.355133Z digest=sha256:bd0ae2e41be92f0ec47c88a0e1de2f72cc9f12453d6af4d68e8b1ec23841ee41

Observation 0badedf2-48a6-4666-af8b-62f3fe087213 · outbound

This paper cites Multi-property Steering of Large Language Models with Dynamic Activation Composition.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Multi-property Steering of Large Language Models with Dynamic Activation Composition

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 11649a84-4892-4c31-8d8b-9fa9d73ca408 · outbound

This paper cites an unresolved cited work.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Unresolved cited work

Reference 34

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raw_fallback, observed 2026-08-14T04:41:57.539429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 6860f190-db55-4042-b9d6-27f1e10bdf22 · outbound

This paper cites Proceedings of the 29th Symposium on Operating Systems Principles , pages =.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Proceedings of the 29th Symposium on Operating Systems Principles , pages =

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-14T04:41:55.427984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T04:41:55.427984Z digest=sha256:899fbde3c3f99714241cf11766af40e4468e09bd736f6976061380e27b547b87

Observation 4a2a25fc-9faa-4dac-8447-e5f6830c4ac8 · outbound

This paper cites Advances in Neural Information Processing Systems , doi =.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Advances in Neural Information Processing Systems , doi =

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:41:57.432174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T04:41:55.464759Z digest=sha256:a9b6b3fc06574ab07c1b46c685b7d4be4aa45861c609dd57a58d18a7f26be838

Observation 028c7dd3-d9e7-49e5-af20-f43d3aafdf4c · outbound

This paper cites Transformers: State-of-the-Art Natural Language Processing.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Transformers: State-of-the-Art Natural Language Processing

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-14T04:41:55.502463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T04:41:55.502463Z digest=sha256:06d5f181d35dabdaa21eb60f11cd0bd69ecc59c7fef7e2b4c18b0bd6ec0be739

Observation 17c671e0-815d-43c9-9287-5e322ed73ae3 · outbound

This paper cites Learning.

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization Learning

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:41:57.274749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T04:41:55.529803Z digest=sha256:f07943def8800f791440c656695e6d4152f94759e42b46fcc1354a9106d9fc0e

Pith citing papers

No inbound Pith citation observations are available.