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Paper Citation Record · LEDGER

All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2109.04404.

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

pith.paper-citation-record.v1
2109.04404 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T18:21:44.351378Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:59:20.516644Z

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 8a786ea9-17e9-4fb0-9379-41e4f378d389 · inbound

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale cites this paper.

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality

Reference 163

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T13:35:36.162383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-13T13:35:35.972596Z digest=sha256:937b95aaca00047b3b9243ce2641f56f928b44a57ae9f42ba7cc1ea6ea5e8c16

Observation e9b3e850-3216-4943-b654-adad5f725e24 · inbound

Eliciting Latent Predictions from Transformers with the Tuned Lens cites this paper.

Eliciting Latent Predictions from Transformers with the Tuned Lens All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality

Reference 85

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T16:54:37.525672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-12T16:54:37.382049Z digest=sha256:ae6ec410da4ec5d12d1343f9edc885039f91d0affd9f96c7ff00a42909e97f14

Observation 5557f1e0-0335-4c6f-9341-a2b4e341f9fb · inbound

Massive Activations in Large Language Models cites this paper.

Massive Activations in Large Language Models All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality

Reference 150

Resolution
verified exact
arxiv_id, observed 2026-05-16T07:02:54.053751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-16T07:02:53.740597Z digest=sha256:2960b8e78b9b7e4adc23f13ee683c2d02e150ff206cfa8b064434281adc4b384

Observation 96e0d664-60ec-4190-b371-349bb4dbb13b · inbound

Rethinking Word Similarity: Semantic Similarity through Classification Confusion cites this paper.

Rethinking Word Similarity: Semantic Similarity through Classification Confusion All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-08T18:21:44.351378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T18:21:44.351378Z digest=sha256:1b9ca4499ac0556d40dad494144d9decb9baffa42f9a58e1cbc9b1206b6fef72

Observation 9e75083c-fe7b-4fb3-b552-3f3259d7abca · inbound

HyperLens: Quantifying Cognitive Effort in LLMs with Fine-grained Confidence Trajectory cites this paper.

HyperLens: Quantifying Cognitive Effort in LLMs with Fine-grained Confidence Trajectory All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality

Reference 29

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T19:36:09.869144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-08T11:38:49.630171Z digest=sha256:3600e5255540693dd03f2c5a6ea6d5bbea92f78d3f14690f94e25a208e27b502

Observation cc03183a-90b6-4f7c-a025-67d02084cc76 · inbound

A Single Layer to Explain Them All:Understanding Massive Activations in Large Language Models cites this paper.

A Single Layer to Explain Them All:Understanding Massive Activations in Large Language Models All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality

Reference 24

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T07:36:43.109379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-12T02:29:20.796512Z digest=sha256:a2c6693c9a63ea97ca528962bfa4a1f5d825389409706640f9b097d535f76535

Observation 9e9ea9ce-bdb4-4d1e-b55e-88fed69116df · inbound

A Single Layer to Explain Them All:Understanding Massive Activations in Large Language Models cites this paper.

A Single Layer to Explain Them All:Understanding Massive Activations in Large Language Models All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality

Reference 24

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T21:19:29.131868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-14T21:03:25.624300Z digest=sha256:81d7ccd1c58284b469d8762b84e66f72e0671f9810c7ca327c83dcd9fc83adac

Observation 6770713a-e23c-45c3-80ed-4cfed1e272dc · inbound

Size Doesn't Matter: Cosine-Scored Sparse Autoencoders cites this paper.

Size Doesn't Matter: Cosine-Scored Sparse Autoencoders All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-07-01T07:15:29.645191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-07-01T07:15:16.674714Z digest=sha256:4e39258c4e17e1eae3c0e5bb426f66aae39079112403308d0ba5491e8595446a

Observation fa7797c1-3e7b-4219-bff6-7634f5edfa14 · inbound

Massive Activations Are Architecturally Robust: A Controlled Scratch/Commitment Residual Stream Test cites this paper.

Massive Activations Are Architecturally Robust: A Controlled Scratch/Commitment Residual Stream Test All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-07-04T00:59:20.519308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T20:47:54.133087Z digest=sha256:2887d536f6207b341f0ff015ebc27d75ead70cdf7f4e21f97cf18966b370aa00

Observation dee5b13f-7326-4bb9-a742-9a0e250b63b4 · inbound

MXSens: Sensitivity-Aware Mixed-Precision Quantization for Efficient LLM Inference cites this paper.

MXSens: Sensitivity-Aware Mixed-Precision Quantization for Efficient LLM Inference All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-01T17:12:27.357886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T17:12:27.357886Z digest=sha256:21190a7d4942fb6bdeaa89c46c5e80531923e6e7c2596de5820dceb394930c7a

Observation 59411b51-d31a-434b-a786-2e787c3c21bd · inbound

Metaphor Tracer: A Theory-Informed Analysis of Hidden States cites this paper.

Metaphor Tracer: A Theory-Informed Analysis of Hidden States All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality

Reference 18

Resolution
unresolved
no resolver link, observed 2026-07-31T07:30:05.520280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T07:30:05.520280Z digest=sha256:39e6de63a1c2917cb2fd5196acf9bf6a8431575f1d328909490a41bbf77c8d4c

Observation 0285da40-5e7c-4ad3-8057-36ee2fd2ae64 · inbound

Divergent large language model predictions from convergent representations in ambiguous word pairs cites this paper.

Divergent large language model predictions from convergent representations in ambiguous word pairs All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-04T20:22:23.028058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T20:22:23.028058Z digest=sha256:90cc1aec8152c43874476a77a6d6172d63d0200a5bc6d2f16a8606e941a28bd8