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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.

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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=sha256:830f28272cd0a7180f0f69452813f90212d64cf4ef1d60c86e214e9c65b1af84

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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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 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:c9e239152af8571108e790b824e259b98cb93456c3549b8325255bbd0bf6ad39

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T04:41:54.531167Z digest=sha256:62475268974b1068c534e0fb5c27c277c415c9c533d2cea5aef34d9e841e4894

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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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=2026-08-14T04:41:54.574775Z digest=sha256:fb0820221804044d314ece11ebe671a7da9700dde6e2cfb4152eef552358a5e3

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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Unavailable: canonical work link unavailable.

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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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T04:41:54.664754Z digest=sha256:f2016bf799299d993bb37817d5db107b2335c18ff1315b35b618b6c79a5ac772

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.

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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:e56e6a794282cc8cf92112658a7099255383114e803e362844b6895e7d15e1db

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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raw_fallback, observed 2026-08-14T04:41:58.228237Z

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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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 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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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 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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unresolved
no resolver link, observed 2026-08-14T04:41:55.174777Z

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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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no resolver link, observed 2026-08-14T04:41:55.205025Z

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.

source=arxiv_source observed=2026-08-14T04:41:55.226660Z digest=sha256:1aee3f3ea937d7bc3c80d0e175f51c888ceacaa4641fd0a266861c00f3560c71

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.

source=arxiv_source observed=2026-08-14T04:41:55.264881Z digest=sha256:7064adabdc690339968281f01495a7d000ce9e39a8d45636235f528173a67a59

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
raw_fallback, observed 2026-08-14T04:41:57.631585Z

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=sha256:8043c0b3bcb3d21a937ac191e4e1d8b9b948bb05abfcd079ce986e8bcaecd710

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=sha256:29ad4f28a16ef5a1b0f65721fc8f034e371fb17c8feb91160c79e81decaa30c6

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.

source=arxiv_source observed=2026-08-14T04:41:55.381830Z digest=sha256:3c5edd9237765c50b75ae363d146316f3848b81ee1c41f010dbebfd50e77d961

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.

source=arxiv_source observed=2026-08-14T04:41:55.399697Z digest=sha256:6732be4bc43ad830f1b15f90592ecc00c70f6590bea9f84cef82a5dde02fa857

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:d55419f9e8a923b60a625e720dd1901e23bb7bd261690137c6874189aa8284de

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=sha256:5962ca218867a24a281e6a1e9b4789f6c05318b102d254b7a8a464636adb75fd

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=sha256:7c2f50126cf7aa7f47249f8af86138d48ece1e98f416a55ab745d710e5cd85af

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=sha256:4c87e35c76153640ece19c58e002a2ee9ae226bad89b4c68d97c1b955178afc5

Pith citing papers

No inbound Pith citation observations are available.