Pith. sign in

Paper Citation Record · LEDGER

No Training Wheels: Steering Vectors for Bias Correction at Inference Time

As of 19 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2506.18598.

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

pith.paper-citation-record.v1
2506.18598 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:21:34.209768Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

18 of 18 outbound references displayed

  • verified exact0
  • verified fuzzy3
  • unresolved15
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6bb22b6f-f293-480d-ad29-ea262464c857 · outbound

This paper cites write newline.

No Training Wheels: Steering Vectors for Bias Correction at Inference Time write newline

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T23:21:31.526768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:21:31.526768Z digest=sha256:a0bc5535d5bbb048a174b0b462d54811caa8704de6ae8ca5bdce013b5b95f145

Observation 750da7db-c23a-4cc0-a153-d6dec16b6cb6 · outbound

This paper cites Refusal in Language Models Is Mediated by a Single Direction.

No Training Wheels: Steering Vectors for Bias Correction at Inference Time Refusal in Language Models Is Mediated by a Single Direction

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T23:21:31.594561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:21:31.594561Z digest=sha256:633791a689038661432065819ca2cd3c614a86fbd8ec9eadabb1f84b84bbce16

Observation f6be58ab-47f8-4018-852f-6e24d53b5972 · outbound

This paper cites Diff-in-means concept editing is worst-case optimal: Explaining a result by Sam Marks and Max Tegmark , 2023.

No Training Wheels: Steering Vectors for Bias Correction at Inference Time Diff-in-means concept editing is worst-case optimal: Explaining a result by Sam Marks and Max Tegmark , 2023

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:21:36.134891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T23:21:31.695188Z digest=sha256:a8e5d060fdb5868ae74684458f331aaf4c7e0c6ca7732df6cd212666a973bbb9

Observation e51c783d-a696-4e2a-8646-e9bd02b31344 · outbound

This paper cites Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings.

No Training Wheels: Steering Vectors for Bias Correction at Inference Time Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T23:21:31.805998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:21:31.805998Z digest=sha256:4a13e5d5b6e939db7fa93e43a89c86100e55c92d7cb43b1643454dac1b9a0a85

Observation 8ef136b9-5a83-4e4f-9c3a-e02393032f3b · outbound

This paper cites Discovering Latent Knowledge in Language Models Without Supervision.

No Training Wheels: Steering Vectors for Bias Correction at Inference Time Discovering Latent Knowledge in Language Models Without Supervision

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T23:21:31.897028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:21:31.897028Z digest=sha256:37adac228f752f14c55291265008fb146b8e7d461f9c7ec366857ab44979564a

Observation 0d4f3c4b-ca06-46ea-8d79-35eeef30ae6c · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

No Training Wheels: Steering Vectors for Bias Correction at Inference Time Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T23:21:32.027162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:21:32.027162Z digest=sha256:ba6730cf3ab88ce1f65471aa1fb64ef3f6fc032c732bf42854ff44c4fd136580

Observation 21692e02-2426-43be-bfb2-d141b6a0e081 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

No Training Wheels: Steering Vectors for Bias Correction at Inference Time An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T23:21:32.139438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:21:32.139438Z digest=sha256:bb66066aa58cf4963ca1b6327d5dc5384ff48e05f4ce4c6b8af8930769356144

Observation c6594076-7e59-4f43-80cf-5b5b66326cdb · outbound

This paper cites an unresolved cited work.

No Training Wheels: Steering Vectors for Bias Correction at Inference Time Unresolved cited work

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T23:21:32.254237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:21:32.254237Z digest=sha256:44be86a9608188ba72856e5867e4d86d5c49be86678dd1142a098df0e2d92520

Observation cccf4a5c-917c-4033-a81b-f228edaa361d · outbound

This paper cites an unresolved cited work.

No Training Wheels: Steering Vectors for Bias Correction at Inference Time Unresolved cited work

Reference 9

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:21:35.849917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T23:21:32.443795Z digest=sha256:12e78fecbaacea341b304c752df2dabb694769261fb207337e2f2d8b870a0816

Observation 88b4c6a2-0167-467f-8fa3-6f2b45fa171f · outbound

This paper cites Steering Llama 2 via Contrastive Activation Addition.

No Training Wheels: Steering Vectors for Bias Correction at Inference Time Steering Llama 2 via Contrastive Activation Addition

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T23:21:32.700490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:21:32.700490Z digest=sha256:196d1050ecbecb09a91555a718c5bb16d27f24c7de824de5777d54b660b7611f

Observation a99bbaf2-b613-418e-8b4b-5b07e448e292 · outbound

This paper cites The Linear Representation Hypothesis and the Geometry of Large Language Models.

No Training Wheels: Steering Vectors for Bias Correction at Inference Time The Linear Representation Hypothesis and the Geometry of Large Language Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T23:21:32.928349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:21:32.928349Z digest=sha256:a70627cd95924bf78ca63e1f9f658cbbefab8e3bbcb3fea7afdc572b78addbff

Observation c6ba4781-4a6f-4e0e-b0e8-780ac0769177 · outbound

This paper cites From Fake to Real: Pretraining on Balanced Synthetic Images to Prevent Spurious Correlations in Image Recognition.

No Training Wheels: Steering Vectors for Bias Correction at Inference Time From Fake to Real: Pretraining on Balanced Synthetic Images to Prevent Spurious Correlations in Image Recognition

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T23:21:33.015705Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:21:33.015705Z digest=sha256:75d88d58644c7f0b18274b5f6e06fa86f4ef6ca4146b67e18453e18548a091d7

Observation d6535be0-21a5-4a35-8d35-fb100bb06428 · outbound

This paper cites Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization.

No Training Wheels: Steering Vectors for Bias Correction at Inference Time Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T23:21:33.126785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:21:33.126785Z digest=sha256:d0042d8e7dfc5bc7954791a0d7406646c220ae89452dff3dd8ab90b9a33ca27e

Observation 064f7a2d-a50f-4859-bb29-97c6008226f7 · outbound

This paper cites Linear Representations of Sentiment in Large Language Models.

No Training Wheels: Steering Vectors for Bias Correction at Inference Time Linear Representations of Sentiment in Large Language Models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T23:21:33.261035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:21:33.261035Z digest=sha256:02f486ae95d0266a62a5e4b8d26470b7a027f5eda5bc7babf0709bdebadf9aa8

Observation f0e6c457-a029-44cf-b5d1-37c81bbbc7a5 · outbound

This paper cites N., Kaiser, ., and Polosukhin, I.

No Training Wheels: Steering Vectors for Bias Correction at Inference Time N., Kaiser, ., and Polosukhin, I

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T23:21:33.375837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:21:33.375837Z digest=sha256:d953f05b2ca855d77bc3500119effc899ae4bd70a72441e0b9e8ce1a7f0ac27e

Observation 1b2b3c6f-eb35-4ef4-aa9c-d3a0760d7426 · outbound

This paper cites A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference.

No Training Wheels: Steering Vectors for Bias Correction at Inference Time A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T23:21:33.504146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:21:33.504146Z digest=sha256:a148991b58931a85a56f0f5bcb1b32be07b99f62745eb2e8397c7981778433ae

Observation 64650258-e2ee-4a14-8a20-86574bb2893b · outbound

This paper cites Celeba-spoof: Large-scale face anti-spoofing dataset with rich annotations.

No Training Wheels: Steering Vectors for Bias Correction at Inference Time Celeba-spoof: Large-scale face anti-spoofing dataset with rich annotations

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:21:35.621101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T23:21:34.094924Z digest=sha256:4ef0141ca2beca7b0eb78e2d8d885c77389713aed062e00c13f80a3184ab5fc6

Observation cfa245c7-ee74-48a2-ba12-af6976313a18 · outbound

This paper cites Age progression/regression by conditional adversarial autoencoder.

No Training Wheels: Steering Vectors for Bias Correction at Inference Time Age progression/regression by conditional adversarial autoencoder

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:21:35.473703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T23:21:34.209768Z digest=sha256:3a3c8a9f080f6503dcc71fd6170b02d89741b2c8773b70fb2075408bf2ac5272

Pith citing papers

No inbound Pith citation observations are available.