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Paper Citation Record · LEDGER

Steering Large Language Models using Conceptors: Improving Addition-Based Activation Engineering

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2410.16314.

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

pith.paper-citation-record.v1
2410.16314 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T13:56:49.249741Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 89612e84-0213-40b0-be31-b78f3e720efa · inbound

Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models cites this paper.

Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models Steering Large Language Models using Conceptors: Improving Addition-Based Activation Engineering

Reference 242

Resolution
verified exact
arxiv_id, observed 2026-05-16T12:40:54.788507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T12:39:57.398423Z digest=sha256:7e481eea9d799bc64304a13e496a291ac920cc8849f9ad941204e3668f24fe98

Observation 46859ec1-d99c-4a09-830f-c010e8766f11 · inbound

How Do Answer Tokens Read Reasoning Traces? Self-Reading Patterns in Thinking LLMs for Quantitative Reasoning cites this paper.

How Do Answer Tokens Read Reasoning Traces? Self-Reading Patterns in Thinking LLMs for Quantitative Reasoning Steering Large Language Models using Conceptors: Improving Addition-Based Activation Engineering

Reference 25

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T02:43:24.290608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-10T02:40:28.718556Z digest=sha256:9e57ac953d7c34585947b2366ef66af540c4cc4aa70eb2eaba76a80554571c72

Observation ece9a8cb-c645-415e-a2e9-973aedb4f8b8 · inbound

Prompt-Activation Duality: Improving Activation Steering via Attention-Level Interventions cites this paper.

Prompt-Activation Duality: Improving Activation Steering via Attention-Level Interventions Steering Large Language Models using Conceptors: Improving Addition-Based Activation Engineering

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:16:26.086032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-12T04:27:15.490694Z digest=sha256:5f43019c4e342bf84cf92f8fd259c01d9e5b9350134cf4628520c1ef21777c3c

Observation a64375d0-503f-416b-9231-fb1105357add · inbound

Prompt-Activation Duality: Improving Activation Steering via Attention-Level Interventions cites this paper.

Prompt-Activation Duality: Improving Activation Steering via Attention-Level Interventions Steering Large Language Models using Conceptors: Improving Addition-Based Activation Engineering

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-15T05:29:47.031337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T05:27:59.011749Z digest=sha256:e3c7b2c2977dd41295a4eb7def8e840683c316111e392bb5337c2d03da2d4d47

Observation 08dfd40a-f066-49d2-b7dd-c0a4761a9bc1 · inbound

$\alpha$-TCAV: A Unified Framework for Testing with Concept Activation Vectors cites this paper.

$\alpha$-TCAV: A Unified Framework for Testing with Concept Activation Vectors Steering Large Language Models using Conceptors: Improving Addition-Based Activation Engineering

Reference 131

Resolution
verified exact
arxiv_id, observed 2026-05-19T19:52:44.709195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-19T19:47:59.664096Z digest=sha256:67e2619925f857a004fa27e38cdb07399480bfa6aab386f3af0e2ec88e843771

Observation 40efe201-57fd-4cb2-9c00-304b3f31650f · inbound

Decomposing how prompting steers behavior cites this paper.

Decomposing how prompting steers behavior Steering Large Language Models using Conceptors: Improving Addition-Based Activation Engineering

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-07-02T02:46:28.541690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-28T10:39:58.885284Z digest=sha256:148c66498479b949fd4c4abd7467e0775a871ef845e6a8290f42b187c49529cc

Observation bb07d6db-e778-495a-a288-bb68f19796d2 · inbound

Temporal Preference Concepts and their Functions in a Large Language Model cites this paper.

Temporal Preference Concepts and their Functions in a Large Language Model Steering Large Language Models using Conceptors: Improving Addition-Based Activation Engineering

Reference 89

Resolution
verified exact
arxiv_id, observed 2026-07-01T14:05:47.189968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-30T22:16:47.743387Z digest=sha256:2d8b205903e51e106ae1d5ed9690ba0f79b1c843989282749993b6d1ae260966

Observation a20c3392-d86a-4cb4-a46d-4498d71301b5 · inbound

Temporal Preference Concepts and their Functions in a Large Language Model cites this paper.

Temporal Preference Concepts and their Functions in a Large Language Model Steering Large Language Models using Conceptors: Improving Addition-Based Activation Engineering

Reference 89

Resolution
unresolved
no resolver link, observed 2026-07-12T17:03:44.315006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T17:03:44.315006Z digest=sha256:99290ed92daf6cff235e8b201314698706e4e256ff6076fd6f894f9a78154824

Observation 49889d5e-40a8-47fd-827a-50701475574a · inbound

Probabilistic Concept-Aware Steering for Trustworthy LLM Inference cites this paper.

Probabilistic Concept-Aware Steering for Trustworthy LLM Inference Steering Large Language Models using Conceptors: Improving Addition-Based Activation Engineering

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-02T13:56:49.249741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T13:56:49.249741Z digest=sha256:9fba767b93468ee3d080c944aecf6d2c205ecf7d32af562cad44cf389759c138

Observation 2c9965ac-060e-42a0-9db0-4acdfd9d2ca7 · inbound

Where Steering Signals Come From: Activation Source Selection in Activation Steering cites this paper.

Where Steering Signals Come From: Activation Source Selection in Activation Steering Steering Large Language Models using Conceptors: Improving Addition-Based Activation Engineering

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-01T03:00:44.918837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:00:44.918837Z digest=sha256:961046f66361033be815878adeb63e46f642401e8d2026d84405428e68436764

Observation d2c82c05-5d54-4281-b11b-6f229ae5ffac · inbound

Latent-IM: Latent Interaction Management for Speech LLMs cites this paper.

Latent-IM: Latent Interaction Management for Speech LLMs Steering Large Language Models using Conceptors: Improving Addition-Based Activation Engineering

Reference 11

Resolution
unresolved
no resolver link, observed 2026-07-30T16:46:07.357247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T16:46:07.357247Z digest=sha256:f886778a3e759d393c7c7b404bdce225e4feef9434136264775c6b1b491672dd