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Paper Citation Record · LEDGER

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits

As of 20 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 1 inbound Pith citation observation for arXiv:2505.10202.

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

pith.paper-citation-record.v1
2505.10202 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:18:24.529671Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:26:51.707959Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-16T12:16:17.039197Z

Reference resolution

30 of 30 outbound references displayed

  • verified exact0
  • verified fuzzy1
  • unresolved29
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 42cc6d94-4609-4d44-af61-e0f1d3a07d91 · outbound

This paper cites online" 'onlinestring :=.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits online" 'onlinestring :=

Reference 1

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unresolved
no resolver link, observed 2026-08-15T21:18:24.410534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.410534Z digest=sha256:37043401aebd3a506247d3d15f33cad3bd1c81bc0415e280a3e9cb939e8f675a

Observation 4eeca735-24d4-420f-aa88-e8839e4f4712 · outbound

This paper cites write newline.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits write newline

Reference 2

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unresolved
no resolver link, observed 2026-08-15T21:18:24.415315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.415315Z digest=sha256:c4dc943c02a3a709c86c8c3210ff28bd97103f3ac430db500459945e2efcb480

Observation 5affab7c-02f8-4359-9bdc-4d0389aafd3c · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 3

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no resolver link, observed 2026-08-15T21:18:24.419564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.419564Z digest=sha256:df2a4d615ea91cc7a47e6bb06f35ea7ece9d0bca06157cb51f32530833b3c9f8

Observation e6562826-835e-4420-b3f7-535d633cb34b · outbound

This paper cites Language Models are Few-Shot Learners.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Language Models are Few-Shot Learners

Reference 4

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no resolver link, observed 2026-08-15T21:18:24.423831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.423831Z digest=sha256:d80001de907131b942b3f92339774c61b21e147466bced1cddf951a15f4bb2a5

Observation b9d12b2d-6095-442b-8cf7-8dba9dd7b590 · outbound

This paper cites an unresolved cited work.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Unresolved cited work

Reference 5

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raw_fallback, observed 2026-08-15T21:18:24.955317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T21:18:24.428069Z digest=sha256:671b3f2d149148c852a41ace291f6b5d3b7148c9e63894b3a11b3a66f6d3a2e0

Observation f3898a5a-ab0e-4e79-b04a-9d1e78c971ce · outbound

This paper cites The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

Reference 6

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no resolver link, observed 2026-08-15T21:18:24.431797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.431797Z digest=sha256:caeccb75f54959ed11778f1ad03a758749561da6b1989d049c340804472db93b

Observation c4e643f3-a78c-4f89-a42b-3e4f38c817e1 · outbound

This paper cites an unresolved cited work.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Unresolved cited work

Reference 7

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raw_fallback, observed 2026-08-15T21:18:24.942743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T21:18:24.436209Z digest=sha256:05a6f5a76ee16a116d241d1e5d4db5a850a76ec6fcfdb7d461c31b9341f8b79e

Observation fd25c665-8c3c-4559-900f-b8fde3c5d6b5 · outbound

This paper cites Learning both Weights and Connections for Efficient Neural Networks.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Learning both Weights and Connections for Efficient Neural Networks

Reference 8

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no resolver link, observed 2026-08-15T21:18:24.440824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.440824Z digest=sha256:4994a11396c88313f5babd059002fca582fdbea2e50a2fc55f7122fff2d227a2

Observation 57d39289-d7b9-4761-bb0b-ea05bc7cba95 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Distilling the Knowledge in a Neural Network

Reference 9

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no resolver link, observed 2026-08-15T21:18:24.444996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.444996Z digest=sha256:27e6bb834f1d6e0a0c287b1b3b8f2a706819dd7aa4ece041d4004d17e96a61fc

Observation 03b2c2cd-262b-4044-88d7-579d2c4c31c7 · outbound

This paper cites Tying Word Vectors and Word Classifiers: A Loss Framework for Language Modeling.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Tying Word Vectors and Word Classifiers: A Loss Framework for Language Modeling

Reference 10

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no resolver link, observed 2026-08-15T21:18:24.448944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.448944Z digest=sha256:b2a37872d075faf8cda81781063e20c03d5963f679d960a66140044eb357acc5

Observation b2432bd2-474c-41da-98cd-e3de97385433 · outbound

This paper cites Categorical Reparameterization with Gumbel-Softmax.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Categorical Reparameterization with Gumbel-Softmax

Reference 11

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no resolver link, observed 2026-08-15T21:18:24.453654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.453654Z digest=sha256:378a28730c96151dcb9f82a2b17915038648a2e2cec577b453f048df9adf6232

Observation 82dc74e3-94ca-4ab0-b8dd-4c0868a54a75 · outbound

This paper cites On Using Very Large Target Vocabulary for Neural Machine Translation.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits On Using Very Large Target Vocabulary for Neural Machine Translation

Reference 12

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unresolved
no resolver link, observed 2026-08-15T21:18:24.457829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.457829Z digest=sha256:66bbfc15c861254a3c010a00bb55392fd2689deaf54becda47a6d12c1e7dc7ce

Observation b2ffcb63-6199-4ed6-b3eb-95f7d5245635 · outbound

This paper cites an unresolved cited work.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Unresolved cited work

Reference 13

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unresolved
no resolver link, observed 2026-08-15T21:18:24.461834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.461834Z digest=sha256:e03941fe8dfaf0f6131b435fc10d3dcbec65d7e459e2c927f6c9883e9e8ea52c

Observation 60dc7f77-d346-4827-9560-4340c40a6e82 · outbound

This paper cites an unresolved cited work.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Unresolved cited work

Reference 14

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unresolved
no resolver link, observed 2026-08-15T21:18:24.465579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.465579Z digest=sha256:199ee687168b8ea66e16a75d2f95f78ab7300aa821cc5d7a8585fc6cd8256c4b

Observation 68686b63-e9a9-4af6-93e3-535a579aab05 · outbound

This paper cites an unresolved cited work.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Unresolved cited work

Reference 15

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unresolved
raw_fallback, observed 2026-08-15T21:18:24.932374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T21:18:24.469322Z digest=sha256:0c75043706f15e2af2e90bf5be90a589a45c8579a1e6ee2dbec368d61e26c8fb

Observation b62d7131-15f7-4890-9233-fb87a7807033 · outbound

This paper cites an unresolved cited work.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Unresolved cited work

Reference 16

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unresolved
raw_fallback, observed 2026-08-15T21:18:24.920849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T21:18:24.473515Z digest=sha256:ca4672d13fb3dc6c01bd79c779cd3c372de459ac601e4f59c0ac375d1134aaba

Observation ce6043f8-3ae8-4bbd-8495-5b3be7817ab5 · outbound

This paper cites ALBERT: A Lite BERT for Self-supervised Learning of Language Representations.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-15T21:18:24.477241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.477241Z digest=sha256:c329461ffaf8f2f862a8c034e0957d2e9620fddc5e4e077c097900afc8a02a3c

Observation 3fdaf91a-7873-4863-8bd6-1a85aa345b39 · outbound

This paper cites Decoupled Weight Decay Regularization.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Decoupled Weight Decay Regularization

Reference 18

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unresolved
no resolver link, observed 2026-08-15T21:18:24.481301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.481301Z digest=sha256:8733d62f0030748c9b1cc0c66b7961ca41c43107f6046035d73aec4b049341db

Observation e1acafc8-4602-485c-8b85-d75248acf651 · outbound

This paper cites Marcus, Mary Ann Marcinkiewicz, and Beatrice Santorini.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Marcus, Mary Ann Marcinkiewicz, and Beatrice Santorini

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-15T21:18:24.909476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T21:18:24.486003Z digest=sha256:111224035f8a41f1e114580ea54d7a85bb91746754d93943459e7ae13599a7c6

Observation c71c33e3-32b2-4ba7-8552-6f3ce7570207 · outbound

This paper cites an unresolved cited work.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Unresolved cited work

Reference 20

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unresolved
raw_fallback, observed 2026-08-15T21:18:24.897468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T21:18:24.489731Z digest=sha256:e36d62860f7f1ce08f97fa76563901fbf966aa8a42831ab0cd66554282bbd6cd

Observation 206e5a89-8bec-49b8-9322-739afc69e249 · outbound

This paper cites an unresolved cited work.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Unresolved cited work

Reference 21

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unresolved
raw_fallback, observed 2026-08-15T21:18:24.886287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T21:18:24.493252Z digest=sha256:1474b50e080a84290d34a1f61c93d1b61a572c534f52463973ee264dc9942634

Observation ade839bf-7dc1-4e10-a3de-b69a70a8379b · outbound

This paper cites an unresolved cited work.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Unresolved cited work

Reference 22

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unresolved
raw_fallback, observed 2026-08-15T21:18:24.874564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T21:18:24.497089Z digest=sha256:aa5a3912c48d40c3cdd9366e5e7acf200f6ef39786c61108f0a80fe29dbda1f2

Observation 46fd6e34-9419-4b17-babe-e9de3a422573 · outbound

This paper cites an unresolved cited work.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Unresolved cited work

Reference 23

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raw_fallback, observed 2026-08-15T21:18:24.862645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T21:18:24.501028Z digest=sha256:8f2a8aa40b837448af6ca6a50384bdd5f6cb49fc7634d49343a12e7a233b4529

Observation 21f0a68b-5512-4002-a069-a285804686f2 · outbound

This paper cites GPT-4 Technical Report.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits GPT-4 Technical Report

Reference 24

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no resolver link, observed 2026-08-15T21:18:24.505437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.505437Z digest=sha256:bd219b8c85f50fcfa103f9faa6819b07126ad49e5d0edef7e87df5280af4ce5f

Observation 31439218-63a7-420d-878b-96dc8ae91ca7 · outbound

This paper cites Using the Output Embedding to Improve Language Models.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Using the Output Embedding to Improve Language Models

Reference 25

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unresolved
no resolver link, observed 2026-08-15T21:18:24.509783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.509783Z digest=sha256:67c4707b765eaaf53daf9b485aca0da7f59ee1548da58982e4357edcad11156a

Observation 1e902cf1-78ba-458b-bd1f-4390ab8179d8 · outbound

This paper cites an unresolved cited work.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Unresolved cited work

Reference 26

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unresolved
no resolver link, observed 2026-08-15T21:18:24.514648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.514648Z digest=sha256:7f6ada775caf45f48e346af0fb369bb2f8dacdf3894761b7f69c6c992238379c

Observation 36d1912d-5019-41e7-9cd4-5853cb9d1492 · outbound

This paper cites an unresolved cited work.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Unresolved cited work

Reference 27

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unresolved
no resolver link, observed 2026-08-15T21:18:24.518967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.518967Z digest=sha256:ac0fba0c7a0106cb863db13c51faf6183840bfc5e222a6f419f74086ff139a7b

Observation 90fe15cc-ea6c-4dab-af39-bd0805568e17 · outbound

This paper cites Sainath, Brian Kingsbury, Bhuvana Ramabhadran, Petr Fousek, Petr Novak, and Abdel - rahman Mohamed.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Sainath, Brian Kingsbury, Bhuvana Ramabhadran, Petr Fousek, Petr Novak, and Abdel - rahman Mohamed

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-15T21:18:24.522661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.522661Z digest=sha256:a5a3a3d5bb0638cf7d7eec658e9e12486c16d3064ac8615786017764a86a7d7f

Observation b2d0dcd4-94a0-4d09-af79-1cfad88b2e17 · outbound

This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 29

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unresolved
no resolver link, observed 2026-08-15T21:18:24.526083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.526083Z digest=sha256:32f614a06310c20a6fc60a06523001412c67a58ad4ad1cd3c46447bef7000a42

Observation c73622d5-412a-4697-9a0e-302c54b3f22d · outbound

This paper cites Neural Discrete Representation Learning.

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits Neural Discrete Representation Learning

Reference 30

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unresolved
no resolver link, observed 2026-08-15T21:18:24.529671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:18:24.529671Z digest=sha256:3efa4197832a9d09ff878de5c839c9d55e051c589540c3ea5dc79b0a75b58da2

Pith citing papers

Observation 985d0610-4d2d-4a68-92e6-acb10f7dc5cf · inbound

SoftWater: Class-Aware Rate Allocation for Softmax Quantization cites this paper.

SoftWater: Class-Aware Rate Allocation for Softmax Quantization VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits

Reference 52

Resolution
metadata mismatch
local_arxiv, observed 2026-08-16T00:26:52.160396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T00:26:51.707959Z digest=sha256:cdb0d4677c03e41ae986f2b12e2f26d6db3c32fb98251fea88a612d6b92c8460