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Paper Citation Record · LEDGER

Transformers need glasses! Information over-squashing in language tasks

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2406.04267.

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

pith.paper-citation-record.v1
2406.04267 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:55:30.206042Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T19:25:03.712684Z

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 d5466dec-9b0e-4b49-a49d-2647be1c8bb5 · inbound

Provably Overwhelming Transformer Models with Designed Inputs cites this paper.

Provably Overwhelming Transformer Models with Designed Inputs Transformers need glasses! Information over-squashing in language tasks

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-08T17:08:17.091434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:08:17.091434Z digest=sha256:f5730761ef30280d564c13d5bef738eebd1261dd128ec167c48cb5d7c3b468cb

Observation 4db36c97-849e-496b-a3db-ce69159bb1f2 · inbound

What makes a good feedforward computational graph? cites this paper.

What makes a good feedforward computational graph? Transformers need glasses! Information over-squashing in language tasks

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-08T14:33:15.914184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T14:33:15.914184Z digest=sha256:5e79bb80e9eb277165f72c30f3aea108380e6ad0fc52081c2278bd3720df76e9

Observation 1b1d5bd0-d54f-47a9-bdd1-3d3b4f9288be · inbound

You Do Not Fully Utilize Transformer's Representation Capacity cites this paper.

You Do Not Fully Utilize Transformer's Representation Capacity Transformers need glasses! Information over-squashing in language tasks

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T22:19:19.341069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T22:19:19.341069Z digest=sha256:cbe5463d30656b4dd1034922092c23fd00958535451526987e08c8f39f3e9522

Observation d29b7163-eb24-44aa-99a0-f3e072683d07 · inbound

Adaptive Long-term Embedding with Denoising and Augmentation for Recommendation cites this paper.

Adaptive Long-term Embedding with Denoising and Augmentation for Recommendation Transformers need glasses! Information over-squashing in language tasks

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-22T19:25:03.714531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-22T19:24:48.300461Z digest=sha256:be815ef32a4be2cbd5dae392a39da62b89ce4e09dec4cd791e9af35d97c8804e

Observation a733924c-106f-4655-8e8c-71c98e1a739e · inbound

Probability Consistency in Large Language Models: Theoretical Foundations Meet Empirical Discrepancies cites this paper.

Probability Consistency in Large Language Models: Theoretical Foundations Meet Empirical Discrepancies Transformers need glasses! Information over-squashing in language tasks

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-15T21:55:30.206042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:55:30.206042Z digest=sha256:2e883af5b46dfbcbab7b4a8f9cb6258d938afd2c760ba91d5264639f3af77d9f

Observation 0a2b9e0d-8771-4b9e-87c2-871505264879 · inbound

Position: The Future of Bayesian Prediction Is Prior-Fitted cites this paper.

Position: The Future of Bayesian Prediction Is Prior-Fitted Transformers need glasses! Information over-squashing in language tasks

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T12:40:34.259965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:40:34.259965Z digest=sha256:2f28fdf3732ac20c0ad0fa7df17879898605ba9e4cd14f32282da8d905b9f50a

Observation e02a4989-ff5e-4b02-ad09-3f3d19d5cc95 · inbound

From Dispersion to Attraction: Spectral Dynamics of Hallucination Across Whisper Model Scales cites this paper.

From Dispersion to Attraction: Spectral Dynamics of Hallucination Across Whisper Model Scales Transformers need glasses! Information over-squashing in language tasks

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-11T22:56:13.809349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-08T02:17:33.191479Z digest=sha256:b36340d59d455372f52585bded1db34d5de139e80de17ce6c1bea8b14903019a