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Paper Citation Record · LEDGER

Designing a Dashboard for Transparency and Control of Conversational AI

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:2406.07882.

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

pith.paper-citation-record.v1
2406.07882 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:53:47.355644Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T09:07:47.902310Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation dcf5387b-fd12-4489-aeac-4e22d6570019 · inbound

A Survey of Theory of Mind in Large Language Models: Evaluations, Representations, and Safety Risks cites this paper.

A Survey of Theory of Mind in Large Language Models: Evaluations, Representations, and Safety Risks Designing a Dashboard for Transparency and Control of Conversational AI

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-08T15:22:44.817749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T15:22:44.817749Z digest=sha256:bc839f101137ac378d22b67843f735234ef44a06b5934bbe8e1c6a202f2bf7ed

Observation a01dac76-b5c6-44b1-854c-40ce431965a4 · inbound

The Geometry of Self-Verification in a Task-Specific Reasoning Model cites this paper.

The Geometry of Self-Verification in a Task-Specific Reasoning Model Designing a Dashboard for Transparency and Control of Conversational AI

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-16T11:53:47.355644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:53:47.355644Z digest=sha256:14f5323145ca4fd1b29802778fca091248d2f0cc04953265f424825740236241

Observation a379e216-c00b-4411-a89b-ee4dfd9bee2b · inbound

Clones in the Machine: A Feminist Critique of Agency in Digital Cloning cites this paper.

Clones in the Machine: A Feminist Critique of Agency in Digital Cloning Designing a Dashboard for Transparency and Control of Conversational AI

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-16T10:11:58.820225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:11:58.820225Z digest=sha256:e730848691d3859ec78f230119974939f2f89354f108758d1d5de1da8a4598bc

Observation 1882d3a5-a3cb-48dd-8294-f3b59f8a8415 · inbound

Fine-Grained Interpretation of Political Opinions in Large Language Models cites this paper.

Fine-Grained Interpretation of Political Opinions in Large Language Models Designing a Dashboard for Transparency and Control of Conversational AI

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T10:40:12.431538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:40:12.431538Z digest=sha256:106bfc33a30a63dc303edebb4f4ae9cb8e40cc238b31006f1936bc259a71cfe7

Observation b9afb0f9-c4cc-4efd-afd8-86a0355162a3 · inbound

Robustly Improving LLM Fairness in Realistic Settings via Interpretability cites this paper.

Robustly Improving LLM Fairness in Realistic Settings via Interpretability Designing a Dashboard for Transparency and Control of Conversational AI

Reference 9203

Resolution
unresolved
no resolver link, observed 2026-08-07T04:18:33.646142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:18:33.646142Z digest=sha256:7669d0171e60db7aac0343f2d1ca13165b7d860196fa560c9eb896b04f630d3c

Observation a2856cf9-3960-4f23-8784-086a987b8959 · inbound

Because we have LLMs, we Can and Should Pursue Agentic Interpretability cites this paper.

Because we have LLMs, we Can and Should Pursue Agentic Interpretability Designing a Dashboard for Transparency and Control of Conversational AI

Reference 1993

Resolution
unresolved
no resolver link, observed 2026-08-07T01:03:20.611033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T01:03:20.611033Z digest=sha256:f30200eb120d9ad632dd6c3e796905979c1b0b6d8c954c9316b13a934e53a5d5

Observation a4da091a-128d-4e59-8d6f-64f6a01b3135 · inbound

Web-Browsing LLMs Can Access Social Media Profiles and Infer User Demographics cites this paper.

Web-Browsing LLMs Can Access Social Media Profiles and Infer User Demographics Designing a Dashboard for Transparency and Control of Conversational AI

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T16:51:35.360915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:51:35.360915Z digest=sha256:5740370f7d03523e17d349d358bff15bd765380f2608a0692be6369bce9f6804

Observation 9be0636b-6433-4cde-8256-02fe01c65091 · inbound

Emotion Concepts and their Function in a Large Language Model cites this paper.

Emotion Concepts and their Function in a Large Language Model Designing a Dashboard for Transparency and Control of Conversational AI

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:35:57.979368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-10T18:03:52.210931Z digest=sha256:f4fe379f4f030a985a7d8e0d0252aebfe324da6272e377ce871e4d9d5a5054ae

Observation dc8a1dd6-8af8-4940-9dd4-974b8f5e1d87 · inbound

Tensor Product Representation Probes Reveal Shared Structure Across Linear Directions cites this paper.

Tensor Product Representation Probes Reveal Shared Structure Across Linear Directions Designing a Dashboard for Transparency and Control of Conversational AI

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:16:30.293335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-12T03:31:40.195348Z digest=sha256:f469bf46c4083f1ca65bafe5796ea4596b26237941f7d600f03e99ac5db88fc4

Observation aa831e21-9440-495f-9c76-309c9904f71e · inbound

Stories in Space: In-Context Learning Trajectories in Conceptual Belief Space cites this paper.

Stories in Space: In-Context Learning Trajectories in Conceptual Belief Space Designing a Dashboard for Transparency and Control of Conversational AI

Reference 28

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T05:27:19.221019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-13T05:17:34.283917Z digest=sha256:148930d9fdc90a87c4ad079933ea062ff4267e9dfd61fb5258eaa733d0809156

Observation b2fb3c0f-9b29-420d-b3d2-da4ae10fccce · inbound

Tracing Persona Vectors Through LLM Pretraining cites this paper.

Tracing Persona Vectors Through LLM Pretraining Designing a Dashboard for Transparency and Control of Conversational AI

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-14T20:29:27.893927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-14T20:28:17.086117Z digest=sha256:b507f62721e1a829391d30204f26510ca9eb013ccf9b02791c620da2c7fbd417

Observation 36615d5d-2def-414b-aef9-8ccf905a6fb6 · inbound

Multi-Turn Neural Transparency: Surfacing Neural Activations Improves User Calibration to LLM Behavioral Drift cites this paper.

Multi-Turn Neural Transparency: Surfacing Neural Activations Improves User Calibration to LLM Behavioral Drift Designing a Dashboard for Transparency and Control of Conversational AI

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-19T14:42:37.630781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-19T14:37:45.304949Z digest=sha256:c196b4ca2bc4f940c3cc8884b135344b745c436b5406e85f23bed71f18950b6a

Observation 8880b414-b77a-4edf-9437-40494437a710 · inbound

Position: Anthropomorphic Misalignment Research Needs Stronger Evidence cites this paper.

Position: Anthropomorphic Misalignment Research Needs Stronger Evidence Designing a Dashboard for Transparency and Control of Conversational AI

Reference 128

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T20:22:37.256893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-28T20:13:53.972585Z digest=sha256:8408c0f58e3e9ff4f0d4883d0fcdfd1a26d1c39c20fc1ff97a218cc608e63e6d

Observation a506beb9-a1b1-4d1b-8b7f-ef96217bf91d · inbound

The Amplifying Mirror: Locating and Steering the Partisan Direction inside a Large Language Model cites this paper.

The Amplifying Mirror: Locating and Steering the Partisan Direction inside a Large Language Model Designing a Dashboard for Transparency and Control of Conversational AI

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-07-02T23:07:26.669659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-27T18:30:14.923773Z digest=sha256:3c521c6325ff1a352c232b87e9e1c089bb571e358864820d27291f571a8ad98e

Observation 5243fc6d-874a-41d1-acc2-460990cd63bd · inbound

Anatomy of Post-Training: Using Interpretability to Characterize Data and Shape the Learning Signal cites this paper.

Anatomy of Post-Training: Using Interpretability to Characterize Data and Shape the Learning Signal Designing a Dashboard for Transparency and Control of Conversational AI

Reference 282

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T09:07:47.905013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-27T10:32:57.295159Z digest=sha256:6d3ca481239dc4059f978ac52419f9d92829e93305a2e4868960d926bfad0091

Observation 0992d90c-e0c0-43f9-9e27-bb39e556c745 · inbound

Breaking the Solver Bottleneck: Training Task Generators at the Learnable Frontier cites this paper.

Breaking the Solver Bottleneck: Training Task Generators at the Learnable Frontier Designing a Dashboard for Transparency and Control of Conversational AI

Reference 126

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T08:57:48.052233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-27T10:36:09.211639Z digest=sha256:06171e49743b66aae04e9087a2e54e6db12db10478cd33dff4b3130c7de3de7a

Observation 60eef402-cbe9-466d-a814-4571c2316af2 · inbound

HELP: Human-Efficient Large-Scale Robot Post-Training with Rollout Segmentation cites this paper.

HELP: Human-Efficient Large-Scale Robot Post-Training with Rollout Segmentation Designing a Dashboard for Transparency and Control of Conversational AI

Reference 24

Resolution
unresolved
no resolver link, observed 2026-07-14T15:55:25.318583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T15:55:25.318583Z digest=sha256:c4d220e96d83eeca42b035d93997e3555354551f9ea2b7fd3b70b1c0fae63bc3

Observation 93da67a7-f59f-409b-a32e-ef8ce0cffbe9 · inbound

HELP: Human-Efficient Large-Scale Robot Post-Training with Rollout Segmentation cites this paper.

HELP: Human-Efficient Large-Scale Robot Post-Training with Rollout Segmentation Designing a Dashboard for Transparency and Control of Conversational AI

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-02T08:13:05.261454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T08:13:05.261454Z digest=sha256:2055bc374aa0d03f09508a2beb76c18440ae5cbeeddf133794f20f20382016f7

Observation c8706016-1a67-475e-8c14-aa5d5052e18c · inbound

Position: It's Time to Optimize LLMs for Self-Consistency cites this paper.

Position: It's Time to Optimize LLMs for Self-Consistency Designing a Dashboard for Transparency and Control of Conversational AI

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-07T01:00:03.431188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:00:03.431188Z digest=sha256:3520f05e95fda9cb89ba5af4e3af15d9831c5437d6826810cd83a19f512f9a4b

Observation 0e9cc15f-4b5d-468d-9478-d107b9d29919 · inbound

Locating and Controlling Implicit Personalization in Large Language Models cites this paper.

Locating and Controlling Implicit Personalization in Large Language Models Designing a Dashboard for Transparency and Control of Conversational AI

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-16T00:35:39.979948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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