Paper Citation Record · LEDGER

You Do Not Fully Utilize Transformer's Representation Capacity

As of 21 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2502.09245.

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

pith.paper-citation-record.v1
2502.09245 v2

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T22:19:19.455902Z

measured 27 of 27 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

27 of 27 outbound references displayed

verified exact0
verified fuzzy5
unresolved22
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2061c500-51aa-4dd9-9ab5-ed7ac74b1772 · outbound

This paper cites Transformer math 101.

You Do Not Fully Utilize Transformer's Representation Capacity Transformer math 101

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:19:19.962767Z

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.

Observation 81d8eaf0-dc23-4ec8-aed1-48e9f08d6cb9 · outbound

This paper cites Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning.

You Do Not Fully Utilize Transformer's Representation Capacity Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T22:19:19.329231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68bfd8d5-120c-483e-b1f6-8457b7942daf · outbound

This paper cites Training Deeper Neural Machine Translation Models with Transparent Attention.

You Do Not Fully Utilize Transformer's Representation Capacity Training Deeper Neural Machine Translation Models with Transparent Attention

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T22:19:19.335520Z

Source-reported events for the cited work

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

This paper cites Transformers need glasses! Information over-squashing in language tasks.

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

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Unavailable: canonical work link unavailable.

Observation 33fd3f29-44e9-4d41-b06e-a3a20510b22c · outbound

This paper cites Flash A ttention-2: Faster attention with better parallelism and work partitioning.

You Do Not Fully Utilize Transformer's Representation Capacity Flash A ttention-2: Faster attention with better parallelism and work partitioning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T22:19:19.346494Z

Source-reported events for the cited work

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Observation 00e310b6-3e27-4074-b52c-906ae8674f8a · outbound

This paper cites DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model.

You Do Not Fully Utilize Transformer's Representation Capacity DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T22:19:19.351787Z

Source-reported events for the cited work

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Observation f5e28eae-97cd-44e2-b0dd-d2dc482954c0 · outbound

This paper cites Cross-layer retrospective retrieving via layer attention.

You Do Not Fully Utilize Transformer's Representation Capacity Cross-layer retrospective retrieving via layer attention

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:19:19.937741Z

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.

Observation 184f420e-92ae-4194-8dea-899d54591397 · outbound

This paper cites Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective.

You Do Not Fully Utilize Transformer's Representation Capacity Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T22:19:19.363191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4895227a-d591-434a-91f7-b5720c62755f · outbound

This paper cites The Llama 3 Herd of Models.

You Do Not Fully Utilize Transformer's Representation Capacity The Llama 3 Herd of Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T22:19:19.368162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56a92559-7797-4607-98ec-c52b3d043920 · outbound

This paper cites an unresolved cited work.

You Do Not Fully Utilize Transformer's Representation Capacity Unresolved cited work

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T22:19:19.373196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a68f642-fa77-4e73-a65b-5f07056c2f1a · outbound

This paper cites Training Large Language Models to Reason in a Continuous Latent Space.

You Do Not Fully Utilize Transformer's Representation Capacity Training Large Language Models to Reason in a Continuous Latent Space

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T22:19:19.377584Z

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Unavailable: canonical work link unavailable.

Observation c137ac98-8cf8-4623-a0c1-b6523233af9b · outbound

This paper cites Deep Residual Learning for Image Recognition.

You Do Not Fully Utilize Transformer's Representation Capacity Deep Residual Learning for Image Recognition

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T22:19:19.383023Z

Source-reported events for the cited work

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Observation eaa5c77f-73dc-4ea7-bbd7-97ec9f8671af · outbound

This paper cites Densely Connected Convolutional Networks.

You Do Not Fully Utilize Transformer's Representation Capacity Densely Connected Convolutional Networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T22:19:19.387575Z

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Observation a4f8e83e-eb62-40d6-943b-39d6fb03b7f3 · outbound

This paper cites Mistral 7B.

You Do Not Fully Utilize Transformer's Representation Capacity Mistral 7B

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T22:19:19.392673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebdd62fe-3068-4f68-8286-a9f14a22b54f · outbound

This paper cites The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale.

You Do Not Fully Utilize Transformer's Representation Capacity The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T22:19:19.397606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fcbae81a-9a72-417d-9bed-31996a5d7bfb · outbound

This paper cites Qwen2.5 Technical Report.

You Do Not Fully Utilize Transformer's Representation Capacity Qwen2.5 Technical Report

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T22:19:19.402657Z

Source-reported events for the cited work

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Observation 02f2f10a-b574-4513-af88-8137025dbf9d · outbound

This paper cites Mixture-of-Depths: Dynamically allocating compute in transformer-based language models.

You Do Not Fully Utilize Transformer's Representation Capacity Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T22:19:19.407408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbb996fa-0f7e-4f7b-829a-9b1bd4b4016e · outbound

This paper cites Brown, Adam Santoro, Aditya Gupta, Adri \` a Garriga - Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W.

You Do Not Fully Utilize Transformer's Representation Capacity Brown, Adam Santoro, Aditya Gupta, Adri \` a Garriga - Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:19:19.922131Z

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.

Observation 49476ed6-7d97-43f4-bdb1-2837a818e3aa · outbound

This paper cites Highway Networks.

You Do Not Fully Utilize Transformer's Representation Capacity Highway Networks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T22:19:19.417270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5620c4a7-b5ef-42be-92cc-80a91626fe52 · outbound

This paper cites BERT rediscovers the classical NLP pipeline.

You Do Not Fully Utilize Transformer's Representation Capacity BERT rediscovers the classical NLP pipeline

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T22:19:19.422329Z

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Unavailable: canonical work link unavailable.

Observation b1f71636-f643-4ec9-8c73-0a6b125f8c80 · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

You Do Not Fully Utilize Transformer's Representation Capacity Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:19:19.905922Z

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.

Observation bfc2dddb-eaa3-48d8-9035-c6750cdef67c · outbound

This paper cites The bottom-up evolution of representations in the transformer: A study with machine translation and language modeling objectives.

You Do Not Fully Utilize Transformer's Representation Capacity The bottom-up evolution of representations in the transformer: A study with machine translation and language modeling objectives

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T22:19:19.432329Z

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Unavailable: canonical work link unavailable.

Observation e724aa8b-db05-4c0e-88af-fa56537303e9 · outbound

This paper cites an unresolved cited work.

You Do Not Fully Utilize Transformer's Representation Capacity Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-08-07T22:19:19.879645Z

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.

Observation 456470ef-0104-4e56-a218-7e05bed154ea · outbound

This paper cites an unresolved cited work.

You Do Not Fully Utilize Transformer's Representation Capacity Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-07T22:19:19.863424Z

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.

Observation 556b6f27-066e-4195-b6c1-28719019440b · outbound

This paper cites Chi, Quoc V.

You Do Not Fully Utilize Transformer's Representation Capacity Chi, Quoc V

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:19:19.847809Z

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.

Observation 7bafff4d-b797-4683-859c-0af3c6726097 · outbound

This paper cites Hiformer: Sequence modeling networks with hierarchical attention mechanisms.

You Do Not Fully Utilize Transformer's Representation Capacity Hiformer: Sequence modeling networks with hierarchical attention mechanisms

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T22:19:19.450438Z

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Observation 94ae3df3-92cc-4e9f-8f58-fb68f51ecd91 · outbound

This paper cites Hyper-Connections.

You Do Not Fully Utilize Transformer's Representation Capacity Hyper-Connections

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T22:19:19.455902Z

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Pith citing papers

No inbound Pith citation observations are available.