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Paper Citation Record · LEDGER

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering

As of 19 August 2026, this Paper Citation Record lists 86 of 86 outbound references and 4 inbound Pith citation observations for arXiv:2504.14492.

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

pith.paper-citation-record.v1
2504.14492 v2

Coverage vector

measured 86 of 86 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:54:00.230462Z

measured 90 of 90 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:12:59.059412Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T05:36:40.383162Z

Reference resolution

86 of 86 outbound references displayed

  • verified exact4
  • verified fuzzy0
  • unresolved82
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bcdde4b1-3007-48c0-ba78-0b7861a0901e · outbound

This paper cites GPT-4 Technical Report.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering GPT-4 Technical Report

Reference 1

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source=arxiv_source observed=2026-08-16T11:53:59.137097Z digest=sha256:5ea8754a963e1096d9d3f944b53ba0fa5be4a9095fa57cdaa9c9e3c7a33e94df

Observation f5be6675-60db-4022-bcf5-54060a558f8f · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 2

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source=arxiv_source observed=2026-08-16T11:53:59.149422Z digest=sha256:90fbb19d37afcd6567f1aaf57e2f6c3f5aec0f01ff5f7468b341e2c7763708c1

Observation d671a6f3-3381-4a2c-8065-9a6742733a7c · outbound

This paper cites BiasDPO: Mitigating Bias in Language Models through Direct Preference Optimization.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering BiasDPO: Mitigating Bias in Language Models through Direct Preference Optimization

Reference 3

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source=arxiv_source observed=2026-08-16T11:53:59.158646Z digest=sha256:db0a8a2701b19bad4e411c7e5394e4bf52dcc601a3fa992a3f374c524baea3ec

Observation 6029b2e4-1c35-4e7c-ad99-340165e8664d · outbound

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

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Refusal in Language Models Is Mediated by a Single Direction

Reference 4

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source=arxiv_source observed=2026-08-16T11:53:59.168615Z digest=sha256:40331b9af98c68083c31480b45b88804b11762690fa5b4ea5b329f8aaaa265cc

Observation 364cbe21-0021-4d2f-bee2-9c2d9194ba23 · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 5

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source=arxiv_source observed=2026-08-16T11:53:59.179944Z digest=sha256:1e64450cf9ba2e76d6f074586ac5e58d0031e7c9e958649b4facee0c2eb7c00a

Observation b910985b-247d-4efa-9d68-1e124c9e0290 · outbound

This paper cites DiffPO: Diffusion-styled Preference Optimization for Efficient Inference-Time Alignment of Large Language Models.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering DiffPO: Diffusion-styled Preference Optimization for Efficient Inference-Time Alignment of Large Language Models

Reference 6

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source=arxiv_source observed=2026-08-16T11:53:59.193531Z digest=sha256:096981f4a8827ca0266b64fccc85bc948fde848316fcaeb1213eedc49d33ae0e

Observation 855ad296-cefe-4bda-92e3-67262794066e · outbound

This paper cites Learnable Privacy Neurons Localization in Language Models.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Learnable Privacy Neurons Localization in Language Models

Reference 7

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source=arxiv_source observed=2026-08-16T11:53:59.205574Z digest=sha256:74628c718695ce5f3a22dec4c166bb3c62471b902dcd865512f3c8673e7dec95

Observation 42a29f74-6bc7-4656-9525-e80357490ab5 · outbound

This paper cites Identifying and Mitigating Social Bias Knowledge in Language Models.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Identifying and Mitigating Social Bias Knowledge in Language Models

Reference 8

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source=arxiv_source observed=2026-08-16T11:53:59.220387Z digest=sha256:93ca73a10e47af2ba853c321dcd2ff455693b4424bad80dc2a6e8ed427d5081d

Observation a29f94d6-61c7-46a7-b74f-9d2dc64c41ce · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 9

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source=arxiv_source observed=2026-08-16T11:53:59.236138Z digest=sha256:376bcfb75aa1506d223c818d41265c01a7c88b5362d7073e3ac2d7fcf9b1ed87

Observation 9dee8169-00d8-489a-96ad-be445796a3d6 · outbound

This paper cites PAD: Personalized Alignment of LLMs at Decoding-Time.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering PAD: Personalized Alignment of LLMs at Decoding-Time

Reference 10

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source=arxiv_source observed=2026-08-16T11:53:59.243501Z digest=sha256:1bd8afaa347704d62eac773162dd02705b46818cdffb6c41dd4a41297922791c

Observation 87446892-17a4-4a21-add1-9547e49cf46c · outbound

This paper cites FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders

Reference 11

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source=arxiv_source observed=2026-08-16T11:53:59.256067Z digest=sha256:924f28074d7188c9377de8d65a0de03241937c39709d661cfae0acbd0c7985e0

Observation 265d5ee5-99db-4c42-b23a-07427147d15a · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 12

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source=arxiv_source observed=2026-08-16T11:53:59.265653Z digest=sha256:4976498604243ad2c31efd92377e419a44ac6929bd888f5cfae51b97216ff70c

Observation 93035524-3c2d-4e95-9f45-cfeb40ce6a99 · outbound

This paper cites Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions

Reference 13

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source=arxiv_source observed=2026-08-16T11:53:59.276264Z digest=sha256:60f6d210eff32f0b4d23ba3c24e8dff2bc00dfcc63f823ed9257b1aab2931baa

Observation 8ee2ea29-1285-41bf-ba1f-de745e7e8b68 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 14

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source=arxiv_source observed=2026-08-16T11:53:59.287532Z digest=sha256:56cbc4bc198690d42e17a20c9ab0b29ba473381502128daeb8785a1b856179bb

Observation 7eb61449-3a67-4d6a-ba4a-467908b7c9c7 · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 15

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source=arxiv_source observed=2026-08-16T11:53:59.298486Z digest=sha256:713f451f8103dbadd840a1cc5157ea265f6f3290ece88008683a5ce2f5183482

Observation e92810b9-c756-4617-adec-9bf11965c7e3 · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 16

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source=arxiv_source observed=2026-08-16T11:53:59.321448Z digest=sha256:d7f452d386062d98867ce8ff43d47af025fcd44f9d1100d6f268a05b4e9b58bb

Observation 71f2d8c8-d71f-4bb1-ab78-c18054c2e863 · outbound

This paper cites Co$^2$PT: Mitigating Bias in Pre-trained Language Models through Counterfactual Contrastive Prompt Tuning.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Co$^2$PT: Mitigating Bias in Pre-trained Language Models through Counterfactual Contrastive Prompt Tuning

Reference 17

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local_arxiv, observed 2026-08-16T11:54:02.830824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:53:59.342519Z digest=sha256:be141cd438ac2a28e81f1031fe584ae7c4274de8c5951f6b7429628d869c8933

Observation 5c04aba1-59bd-4fb5-a7ec-c356c95848ec · outbound

This paper cites Toy Models of Superposition.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Toy Models of Superposition

Reference 18

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source=arxiv_source observed=2026-08-16T11:53:59.361194Z digest=sha256:7b50730d6472cc411e4f374252eb826f87a789f96ee45ca66d0bd2c5ffc6f9e1

Observation 88b051bc-6481-4524-b445-30c5f33544d8 · outbound

This paper cites FairMT-Bench: Benchmarking Fairness for Multi-turn Dialogue in Conversational LLMs.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering FairMT-Bench: Benchmarking Fairness for Multi-turn Dialogue in Conversational LLMs

Reference 19

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source=arxiv_source observed=2026-08-16T11:53:59.372470Z digest=sha256:1b3a4c4e5282b63676b790f9af1efb1ed557b5d3d528d4f865c822bdcdd5f137

Observation 2329fd3d-c3f3-4ec0-8ae3-b3682ce40663 · outbound

This paper cites BiasAlert: A Plug-and-play Tool for Social Bias Detection in LLMs.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering BiasAlert: A Plug-and-play Tool for Social Bias Detection in LLMs

Reference 20

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source=arxiv_source observed=2026-08-16T11:53:59.393537Z digest=sha256:7bb4613ea257d24732dd055b7670ee0e7c3882beba1c92391cda8c120e337210

Observation d372cba0-8155-4795-b6ee-d1a7a5718349 · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:53:59.408996Z digest=sha256:ada332acae91e81636aeacf5488c07ca240fd861927d7cbf118b8f6d4265d609

Observation 3aeb11e7-56c1-4977-8039-5ce9990f1cf7 · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 22

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:53:59.428797Z digest=sha256:87af00907ea557047d233cecf01af4fb26cfb12650dae3a8daf75d06cb86acb7

Observation 4967e6da-b101-46a0-abe7-0deeb639efae · outbound

This paper cites Self-Debiasing Large Language Models: Zero-Shot Recognition and Reduction of Stereotypes.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Self-Debiasing Large Language Models: Zero-Shot Recognition and Reduction of Stereotypes

Reference 23

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source=arxiv_source observed=2026-08-16T11:53:59.437570Z digest=sha256:d62f426134eafa2e5e12c85c9a6bafb47147b2d92a6f31e72afdd3af950359fb

Observation 1627e8f8-9081-4419-a8f0-6c2a5e4599fb · outbound

This paper cites Detoxifying Text with MaRCo: Controllable Revision with Experts and Anti-Experts.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Detoxifying Text with MaRCo: Controllable Revision with Experts and Anti-Experts

Reference 24

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source=arxiv_source observed=2026-08-16T11:53:59.447640Z digest=sha256:824764292f1386d510bbe3e0e82c278f14c4186d4c827ce711a059da231255a3

Observation 2590f0d5-55d9-4c3c-862a-487d0bf58963 · outbound

This paper cites Diverse Adversaries for Mitigating Bias in Training.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Diverse Adversaries for Mitigating Bias in Training

Reference 25

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local_arxiv, observed 2026-08-16T11:54:02.517915Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:53:59.461032Z digest=sha256:16e0020c62405567bff75219f2b5c484559d68377d5a885c3880b6361bec7b5c

Observation 01545454-2b39-400c-9958-272a29ee5adb · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 26

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:53:59.473551Z digest=sha256:82bec5fbee61e9b29626132ccaf534ac9c7cf3d43bb9c09c419f23b340f43a89

Observation 7532c959-964d-4261-8b4c-f50f05cff7f2 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Measuring Massive Multitask Language Understanding

Reference 27

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source=arxiv_source observed=2026-08-16T11:53:59.485579Z digest=sha256:9c2817d84f8ba84a35a4cc62e1d998fa816be90bc296d56f2a02efe7d2d2231e

Observation 14c08e5b-c13a-454a-a42f-580ff8569332 · outbound

This paper cites Social Biases in NLP Models as Barriers for Persons with Disabilities.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Social Biases in NLP Models as Barriers for Persons with Disabilities

Reference 28

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source=arxiv_source observed=2026-08-16T11:53:59.495009Z digest=sha256:0be40bea0fb03f08e94dcdec537fe787c366aeaf3c827430b245c7e151d90688

Observation 08a5e698-4946-40ca-a3b3-c795f01c417d · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 29

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source=arxiv_source observed=2026-08-16T11:53:59.502376Z digest=sha256:4a4d80d0d5e8c134da87c0f5eed95a027623330cce2855fb16182e3b12eb3af8

Observation b1e742c3-2b47-4012-bc65-044efaa10634 · outbound

This paper cites Mistral 7B.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Mistral 7B

Reference 30

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source=arxiv_source observed=2026-08-16T11:53:59.513820Z digest=sha256:3fd1d1d8ea6b11a5107ceb7166a84801d32d651467bf668ad294532026ed4bb7

Observation cd82f866-0123-4595-a3e5-4b30f6f0f621 · outbound

This paper cites On the Origins of Linear Representations in Large Language Models.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering On the Origins of Linear Representations in Large Language Models

Reference 31

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source=arxiv_source observed=2026-08-16T11:53:59.525452Z digest=sha256:28b8ca07347f80a4465b377bdfddee86c5f42897c114513100063db253a7bbd0

Observation 165a27b6-d288-47a8-bd00-09e1feb1ee7e · outbound

This paper cites On Transferability of Bias Mitigation Effects in Language Model Fine-Tuning.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering On Transferability of Bias Mitigation Effects in Language Model Fine-Tuning

Reference 32

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local_arxiv, observed 2026-08-16T11:54:02.277389Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:53:59.534085Z digest=sha256:78968bbc73a9b291e5b5b00f06b52b3095275ba5f7b6c98f68bcb3c9151f195a

Observation 23aaf3b0-e127-4f5f-b931-3f19537920c4 · outbound

This paper cites Critic-Guided Decoding for Controlled Text Generation.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Critic-Guided Decoding for Controlled Text Generation

Reference 33

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source=arxiv_source observed=2026-08-16T11:53:59.548759Z digest=sha256:404ff97205e17fb16a90144fdddd2848a08c7361657c2bd54b80d436db3db491

Observation fe29ac95-d21b-4706-a90a-840984c2d467 · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 34

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source=arxiv_source observed=2026-08-16T11:53:59.559033Z digest=sha256:076d5b955331de242376ee4c3be8d9acc7c9c3e3416d0c7bb19bcd946fa5db93

Observation 406601f7-2d47-48c7-80f2-4a5dc287748b · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 35

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source=arxiv_source observed=2026-08-16T11:53:59.566437Z digest=sha256:9a02f9d53e04fdbdcd0addbca55988f0513566395e95fe81869d8c9fea63fd14

Observation 1b9a788b-c372-494d-9ae8-57c4d0f07923 · outbound

This paper cites UnQovering Stereotyping Biases via Underspecified Questions.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering UnQovering Stereotyping Biases via Underspecified Questions

Reference 36

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source=arxiv_source observed=2026-08-16T11:53:59.589444Z digest=sha256:99887a39cea2001f9f571b3df574cb6c6d825382e15ac94b03c9dac401ad99e2

Observation ceb0468c-ddf6-46d1-a898-2e8c1c84dae3 · outbound

This paper cites Towards Debiasing Sentence Representations.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Towards Debiasing Sentence Representations

Reference 37

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:53:59.603548Z digest=sha256:d60ad36e425dccf0529fa14d7f6d793df00917809fbd6efa872c92e85e04d843

Observation 6774030b-3d68-4452-a88f-6506404ef188 · outbound

This paper cites Debiasing Algorithm through Model Adaptation.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Debiasing Algorithm through Model Adaptation

Reference 38

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source=arxiv_source observed=2026-08-16T11:53:59.609648Z digest=sha256:407119d989fc939b1acdd134c484d8e3702f0210ebe0d1a95a430f67f912ea85

Observation 57fc15ea-ce3c-4c75-be07-8addd43b4c40 · outbound

This paper cites DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Experts.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Experts

Reference 39

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source=arxiv_source observed=2026-08-16T11:53:59.620618Z digest=sha256:9e661add67189475c5fc91f7ec1bd0e8a58765ad59856467e2a1bf79acd97c52

Observation 6a3abd41-a8c1-4f0c-900b-f55b94d36c40 · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 40

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:53:59.631537Z digest=sha256:d9e2935c89a4a2a18a75476e6d5c4ba236c4b1ed07c1695472e61c753cba7fc0

Observation 4071f3e8-4d22-4ed5-a70c-d370bde9a4a2 · outbound

This paper cites BOLT: Fast Energy-based Controlled Text Generation with Tunable Biases.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering BOLT: Fast Energy-based Controlled Text Generation with Tunable Biases

Reference 41

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source=arxiv_source observed=2026-08-16T11:53:59.658361Z digest=sha256:7be6233c4c395cb18304a155a471c4f4bcbd008522ae60d8872ae7a87c5f0098

Observation 8e49d3ec-9ee8-42a0-a078-982b5417ac33 · outbound

This paper cites The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Pre-trained Language Models.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Pre-trained Language Models

Reference 42

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source=arxiv_source observed=2026-08-16T11:53:59.672465Z digest=sha256:79e2d2e3269c6b4f2b0bedde6259a8c0a4a49ecf7d59c0617ca09425f50670f6

Observation c9876f04-7f08-4852-871b-e6775236e6be · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 43

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:53:59.699724Z digest=sha256:4ba49ffb6bac99cdc92efa451b72db315a1cda659f5f0d9f4ded8765bf5b8eab

Observation e92b0c4a-5698-4ccd-95de-2417fecc30a6 · outbound

This paper cites NeuroLogic Decoding: (Un)supervised Neural Text Generation with Predicate Logic Constraints.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering NeuroLogic Decoding: (Un)supervised Neural Text Generation with Predicate Logic Constraints

Reference 44

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source=arxiv_source observed=2026-08-16T11:53:59.719022Z digest=sha256:f35265061d9b8203d09b52d9bd33883b7429d7fee945ae1c035acd8367996504

Observation 9b725b2b-7864-4862-9cd0-7ca333bf1fe1 · outbound

This paper cites Language Models are Few-Shot Learners.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Language Models are Few-Shot Learners

Reference 45

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source=arxiv_source observed=2026-08-16T11:53:59.729267Z digest=sha256:15c4a52e58c69bdab22d6b1753a01f29502f580c51192596f7a1f488a4dac7c8

Observation 18b6c45c-0369-4ea3-bdbb-1c96966a1e90 · outbound

This paper cites It's All in the Name: Mitigating Gender Bias with Name-Based Counterfactual Data Substitution.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering It's All in the Name: Mitigating Gender Bias with Name-Based Counterfactual Data Substitution

Reference 46

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source=arxiv_source observed=2026-08-16T11:53:59.745926Z digest=sha256:98db875dfff5cfa57dc37cd6faeedeb2ade8391df3afded00132c7b6185da704

Observation 6fd70da0-0d97-4d86-ad5d-4f2b6f863995 · outbound

This paper cites Using In-Context Learning to Improve Dialogue Safety.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Using In-Context Learning to Improve Dialogue Safety

Reference 47

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source=arxiv_source observed=2026-08-16T11:53:59.753133Z digest=sha256:bf63dfa5af8a6ed1f79dad42a5148712469d4aff7f4e26fb3c21da2776a18c3e

Observation c514bb08-21e2-4619-a3d2-7af27ae00f37 · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 48

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:53:59.770323Z digest=sha256:e0e8eb9c7490dbd122912dc87007525e53bd457bccb7bdb478926c64fb4c6296

Observation 615ab022-3dd3-4248-b0bf-d4d7f5fddc4c · outbound

This paper cites Pointer Sentinel Mixture Models.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Pointer Sentinel Mixture Models

Reference 49

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source=arxiv_source observed=2026-08-16T11:53:59.778084Z digest=sha256:50f87f8cabc7614805e92359d4f30b53add7a2d75565313ef21ced0578fa7ab9

Observation 85be979d-254b-4d19-936d-48ba65bdfeea · outbound

This paper cites Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering

Reference 50

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source=arxiv_source observed=2026-08-16T11:53:59.789139Z digest=sha256:c07b4b714506bdefe12e3f40e773bc5c4d41ac4e6aad22241465c6e7eeede589

Observation 92136935-c3a2-494b-b0d8-867cc0137979 · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 51

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:53:59.802375Z digest=sha256:60d340cc4cddea4aa249329838fb3d212ed301544c0c63f0d42336b3b2bac579

Observation 8225761b-51d6-4fa0-a9f5-62022ac26cb3 · outbound

This paper cites CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models

Reference 52

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source=arxiv_source observed=2026-08-16T11:53:59.815517Z digest=sha256:16dcc5d08b9510e058466a574ab308989457e655ae8217f1d30271152fc28baa

Observation d3eb442f-f8a0-4a67-b2a6-8dbc43564d0c · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 53

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source=arxiv_source observed=2026-08-16T11:53:59.826343Z digest=sha256:415b6bd4dc4bb063ac9ae549396bf766e829d6e1f3135c5a411fbc17e719d11b

Observation 22dd4900-da96-49b3-b38a-360f026b1b54 · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 54

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:53:59.835884Z digest=sha256:57ebc78efbfe33a9e7a80234870ccf10e8a782fa34bbe566d2953c6d6c4a7672

Observation e4c27958-de40-41f7-a60c-202b9bd5dc5f · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 55

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:53:59.848722Z digest=sha256:5791b94338f74744505e2b6123e02dd52f2224076d63099aeb5d7fc506dc4928

Observation f522dd67-f386-4ddf-85d9-87f8a3f229a1 · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 56

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source=arxiv_source observed=2026-08-16T11:53:59.857921Z digest=sha256:aa9bee5625da85c957e41c656a802586c7bfc2d54de41a2b1437bf7b2085abba

Observation 512463f3-cb2c-4e9c-9f74-09aeb58ee387 · outbound

This paper cites Steering Llama 2 via Contrastive Activation Addition.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Steering Llama 2 via Contrastive Activation Addition

Reference 57

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source=arxiv_source observed=2026-08-16T11:53:59.872302Z digest=sha256:0e39a1ee4f54693f42b9cfb8e6ed9a4f360cb54e18c3e59f7a6ac9bb0deec2f1

Observation d4e09fe3-3331-42be-8b06-9027746e4b8f · outbound

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

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering The Linear Representation Hypothesis and the Geometry of Large Language Models

Reference 58

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source=arxiv_source observed=2026-08-16T11:53:59.879404Z digest=sha256:f7cc18a4c487bcb2f5c8d8600fc7d3899d3ef5288d6bf67bf618e7159694ec95

Observation 52fff505-8709-4a25-99d8-8367ad7dc94a · outbound

This paper cites BBQ: A Hand-Built Bias Benchmark for Question Answering.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering BBQ: A Hand-Built Bias Benchmark for Question Answering

Reference 59

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source=arxiv_source observed=2026-08-16T11:53:59.889404Z digest=sha256:9b4c713368fabb190240badf42edbf59c0fe4d9b23c608889d1d1852b2005fbb

Observation 6857142f-932b-430a-96db-d2a880acf9be · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 60

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:53:59.897721Z digest=sha256:e712647a9d8aea4c5050c009eb8f4c4bed0cb443da4c9432e14254682733e27a

Observation 480119d3-8f87-4cab-8b7a-4afa7fb54bd5 · outbound

This paper cites Null It Out: Guarding Protected Attributes by Iterative Nullspace Projection.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Null It Out: Guarding Protected Attributes by Iterative Nullspace Projection

Reference 61

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source=arxiv_source observed=2026-08-16T11:53:59.910681Z digest=sha256:c65b17bc9eef5237a06bdc6d2818069ca9834ca35af96c5be480dd335528d4ac

Observation 6a4588d3-f301-4007-abd4-445ff183dea2 · outbound

This paper cites First the worst: Finding better gender translations during beam search.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering First the worst: Finding better gender translations during beam search

Reference 62

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source=arxiv_source observed=2026-08-16T11:53:59.924376Z digest=sha256:28941793b16aba6675881bfe28b5ee7be44892d075007de56cb94fd173023dab

Observation 0b4d514b-51f7-4676-8900-f79500fae720 · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 63

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source=arxiv_source observed=2026-08-16T11:53:59.935631Z digest=sha256:9af002c03989407e04e5850ed61b54a794b0f1ecd8575c151b54136254e2a522

Observation b42cb274-03a6-45fc-9868-12635938e047 · outbound

This paper cites The Woman Worked as a Babysitter: On Biases in Language Generation.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering The Woman Worked as a Babysitter: On Biases in Language Generation

Reference 64

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source=arxiv_source observed=2026-08-16T11:53:59.941617Z digest=sha256:11199ebf253fca1aa7c6cde43e560615a492dd5d2759fddedb7d40b9395beb94

Observation bf17d77b-229f-496f-999c-6dec415d5554 · outbound

This paper cites "Nice Try, Kiddo": Investigating Ad Hominems in Dialogue Responses.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering "Nice Try, Kiddo": Investigating Ad Hominems in Dialogue Responses

Reference 65

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verified exact
local_arxiv, observed 2026-08-16T11:54:01.196847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:53:59.952284Z digest=sha256:119365caeaf11e471fdde69ab9fb2453fed3bedc444cad4cd8eebed16ecf8f24

Observation e2b36b66-9e59-4876-be22-4fb7cf2814be · outbound

This paper cites Societal Biases in Language Generation: Progress and Challenges.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Societal Biases in Language Generation: Progress and Challenges

Reference 66

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source=arxiv_source observed=2026-08-16T11:53:59.960310Z digest=sha256:55a88a7c40694924330f265b1c61ae5728616ee1f65fd745833aff7418e2e1f7

Observation 71175a39-9233-4dc5-99f8-e0f71ba2c155 · outbound

This paper cites Prompting GPT-3 To Be Reliable.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Prompting GPT-3 To Be Reliable

Reference 67

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source=arxiv_source observed=2026-08-16T11:53:59.970159Z digest=sha256:8d2bbfc5ae6c55bff41967531d1f7cc79fef59ac4244af233407d67683895c2e

Observation 88f146c5-9e2d-463c-8949-b92adc5805ba · outbound

This paper cites Does Representation Matter? Exploring Intermediate Layers in Large Language Models.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Does Representation Matter? Exploring Intermediate Layers in Large Language Models

Reference 68

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:53:59.982612Z digest=sha256:8dfd0af4c3d2a2937ee5db262a0584ef6b4cb0c2634108b52ff5cf6383bb7cd7

Observation 71a4601f-4497-4a9f-b69b-96758386f275 · outbound

This paper cites "I'm sorry to hear that": Finding New Biases in Language Models with a Holistic Descriptor Dataset.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering "I'm sorry to hear that": Finding New Biases in Language Models with a Holistic Descriptor Dataset

Reference 69

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:53:59.989339Z digest=sha256:b94b9b856c651df4db7bfd80b07afd708970f26b3a5cc92ca86030b0d742e9a7

Observation ddf510eb-e37b-4453-92cf-3eb158dd4a59 · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 70

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source=arxiv_source observed=2026-08-16T11:53:59.998714Z digest=sha256:bf2f8917f89e5553885aa51033445fe5c1a8851e1413fd312f7b8ba47ce3ec39

Observation 61307ccf-3422-4e3b-9746-df549be7287b · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 71

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raw_fallback, observed 2026-08-16T11:54:03.691353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T11:54:00.025326Z digest=sha256:87bbd8ce97c971aa15cdb9369e12217c9d86ca8a8cd5387fa38001047c87783e

Observation 412fc57b-34c0-4260-8d03-3a05a7ade03f · outbound

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

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Linear Representations of Sentiment in Large Language Models

Reference 72

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:54:00.039753Z digest=sha256:6435e5f7f0b3af4648f5bfcfcec91b2294d977c508f83e8da73f5232fc4b0194

Observation 3871eec4-db93-402d-83e1-915d141f07d2 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering LLaMA: Open and Efficient Foundation Language Models

Reference 73

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no resolver link, observed 2026-08-16T11:54:00.054825Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:54:00.054825Z digest=sha256:c6cb4322c85731366df2ac17188e96ebd0d00c567ee91669d3f69bc346d25e05

Observation ddd2a9ac-a4ad-43de-b616-e7dfa802dfe4 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 74

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:54:00.067711Z digest=sha256:d615f88d8736ea615b9b5aa4d232f1e251cefa1b49e844ba80f353bb58df0327

Observation 13fd75c9-2256-4d0b-80b1-0d12ba9f6319 · outbound

This paper cites A Language Model's Guide Through Latent Space.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering A Language Model's Guide Through Latent Space

Reference 75

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:54:00.078545Z digest=sha256:1343a37c4dc8096a4c28f6a83fba635963294323c5a2a7e61ffc46f0ed260d15

Observation b6f95930-2188-47c5-a9e1-80f52c1994a5 · outbound

This paper cites CEB: Compositional Evaluation Benchmark for Fairness in Large Language Models.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering CEB: Compositional Evaluation Benchmark for Fairness in Large Language Models

Reference 76

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Observation f1574066-9843-41e3-b5c3-a325a8a91506 · outbound

This paper cites Measuring and Reducing Gendered Correlations in Pre-trained Models.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Measuring and Reducing Gendered Correlations in Pre-trained Models

Reference 77

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Observation c2b15f66-1867-4f15-9254-6796506e70bd · outbound

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FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 78

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Observation e18352bd-9234-4d26-bdf2-564e1dd9e05b · outbound

This paper cites Unified Detoxifying and Debiasing in Language Generation via Inference-time Adaptive Optimization.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unified Detoxifying and Debiasing in Language Generation via Inference-time Adaptive Optimization

Reference 79

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Observation eda39a06-aa90-40b5-bdce-eb03a094fea9 · outbound

This paper cites an unresolved cited work.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 80

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Observation a1f0b380-6771-414d-b6d5-fab86889e57e · outbound

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FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Unresolved cited work

Reference 81

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Source-reported events for the cited work

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Observation f3c638d8-bc9b-442d-bf52-0f04026f3655 · outbound

This paper cites Gender Bias in Contextualized Word Embeddings.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Gender Bias in Contextualized Word Embeddings

Reference 82

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Observation 93cdae8c-1584-47dc-8930-a98efeba1d0d · outbound

This paper cites Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology

Reference 83

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Observation 873f273a-a332-486c-b375-86ca32f02518 · outbound

This paper cites Representation Engineering: A Top-Down Approach to AI Transparency.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering Representation Engineering: A Top-Down Approach to AI Transparency

Reference 84

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This paper cites online" 'onlinestring :=.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering online" 'onlinestring :=

Reference 85

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Observation 333a8d13-38a0-4667-836a-8395a7e506d5 · outbound

This paper cites write newline.

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering write newline

Reference 86

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Pith citing papers

Observation b0389be1-d2c8-4a46-8efb-dfe0389321ab · inbound

BiasGuard: A Reasoning-enhanced Bias Detection Tool For Large Language Models cites this paper.

BiasGuard: A Reasoning-enhanced Bias Detection Tool For Large Language Models FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering

Reference 2025

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Observation 285fd62e-05cf-450c-957e-e1a73c13d77d · inbound

BiasFilter: An Inference-Time Debiasing Framework for Large Language Models cites this paper.

BiasFilter: An Inference-Time Debiasing Framework for Large Language Models FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering

Reference 43

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Observation 6b200a2c-384b-49ae-89d0-0832808ec693 · inbound

Detection, Classification, and Mitigation of Gender Bias in Large Language Models cites this paper.

Detection, Classification, and Mitigation of Gender Bias in Large Language Models FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering

Reference 23

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Observation e9ec87f0-9921-47f9-8cec-c4297020a915 · inbound

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

Steered Generation via Gradient-Based Optimization on Sparse Query Features FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering

Reference 26

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