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Paper Citation Record · LEDGER

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs

As of 9 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 2 inbound Pith citation observations for arXiv:2507.07145.

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

pith.paper-citation-record.v1
2507.07145 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:09:17.207868Z

measured 41 of 41 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-02T22:47:05.759610Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:57:38.330281Z

Reference resolution

39 of 39 outbound references displayed

  • verified exact0
  • verified fuzzy1
  • unresolved38
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 14b63c20-00ee-4719-9f00-1a837274a196 · outbound

This paper cites an unresolved cited work.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Unresolved cited work

Reference 1

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unresolved
raw_fallback, observed 2026-08-06T19:09:19.374333Z

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=2026-08-06T19:09:12.742665Z digest=sha256:54347d3ca086b18e21e1e49bc860852f7a735de64bbed284684405baad93a242

Observation c4ec0cbd-798c-498b-9a9a-b60a85129b25 · outbound

This paper cites an unresolved cited work.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Unresolved cited work

Reference 2

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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=2026-08-06T19:09:12.845505Z digest=sha256:3fc5b49f16a148aebb942944cd1346c79f12ade0eb69dde5041fa6ed770861c4

Observation 9deb25dd-c87a-4468-a777-d463f2602396 · outbound

This paper cites an unresolved cited work.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Unresolved cited work

Reference 3

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raw_fallback, observed 2026-08-06T19:09:19.030469Z

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=2026-08-06T19:09:13.011037Z digest=sha256:4eb9849644e9d381dde4aa46c81dffec3e56656b9f821a77029f8c1d7b03eede

Observation 51b50d50-42dc-4982-911c-f53c11778c88 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Training Verifiers to Solve Math Word Problems

Reference 4

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no resolver link, observed 2026-08-06T19:09:13.128489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:13.128489Z digest=sha256:f07422955b431dda3ddbee35e0d9967ec8e09b4439181da2645cd4fc9cc1f7f5

Observation 708ae7b6-e54f-4805-ba43-fc947daad4e2 · outbound

This paper cites DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs

Reference 6

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no resolver link, observed 2026-08-06T19:09:13.415886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:13.415886Z digest=sha256:890f8b3b687476af26a75325d8480df832c34f612ce17b431896e0887301a4be

Observation e2441ab2-3498-49a2-b5ac-13ea8d13180f · outbound

This paper cites Extreme Compression of Large Language Models via Additive Quantization.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Extreme Compression of Large Language Models via Additive Quantization

Reference 7

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no resolver link, observed 2026-08-06T19:09:13.539493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:13.539493Z digest=sha256:cd6f234b014b96c9b11b4f15f934b4c43e2614669161aeb26d812ff8402273b3

Observation 6b4d9949-42b7-4f61-9706-af9bd82a2ff2 · outbound

This paper cites GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 8

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no resolver link, observed 2026-08-06T19:09:13.658735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:13.658735Z digest=sha256:24838b86a9514512230da1abdb8d9351b785f5080ab4790b77f27be7013217d1

Observation d207383a-1172-4363-8e37-6310c3210b93 · outbound

This paper cites The Llama 3 Herd of Models.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs The Llama 3 Herd of Models

Reference 9

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no resolver link, observed 2026-08-06T19:09:13.805539Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:13.805539Z digest=sha256:ebbf3b68b526a2d250aa2d900bca499dc5657bb195135d4c6b569e01391b537d

Observation d1e03642-63cd-48bf-aba6-a0a668cfca47 · outbound

This paper cites an unresolved cited work.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Unresolved cited work

Reference 10

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raw_fallback, observed 2026-08-06T19:09:18.903159Z

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=2026-08-06T19:09:13.964109Z digest=sha256:44d5ba154c4236fa9c6233991c2b6f729b0735b70b1db73bf23a1f57406d48ad

Observation 2cd9f988-21cb-4584-b7ac-5f968dd601fd · outbound

This paper cites Gray and David L.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Gray and David L

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:09:18.735412Z

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=2026-08-06T19:09:14.095610Z digest=sha256:ac5287368f5600de1cc80a2e207f9673526b8a59d80d83999675da6f4240f63f

Observation 52336b97-b442-4e3b-a8df-ad39e59ec8fd · outbound

This paper cites an unresolved cited work.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Unresolved cited work

Reference 12

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no resolver link, observed 2026-08-06T19:09:14.221511Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:14.221511Z digest=sha256:c291bf3d04a3659064e54e6aea329ec3753da88eeaa4b75ad12b6c22f3068402

Observation 4829414d-7be9-47b4-9846-b91a138d227f · outbound

This paper cites an unresolved cited work.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Unresolved cited work

Reference 13

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raw_fallback, observed 2026-08-06T19:09:18.562284Z

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=2026-08-06T19:09:14.323753Z digest=sha256:6848cbde4457c9be7914ca16ee59b1b70ebcad3629b80da0d473f6eab9ff8915

Observation 7075158b-0617-43fb-8979-bba0aa4ed09d · outbound

This paper cites an unresolved cited work.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Unresolved cited work

Reference 14

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no resolver link, observed 2026-08-06T19:09:14.456598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:14.456598Z digest=sha256:4e1e285aa0057a3a2aac8e1ffe6f4089f5fd73b86dad2c67fdd22243f7e0d538

Observation 14813428-cb77-415d-9713-4f4d6f3f670b · outbound

This paper cites SqueezeLLM: Dense-and-Sparse Quantization.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs SqueezeLLM: Dense-and-Sparse Quantization

Reference 15

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no resolver link, observed 2026-08-06T19:09:14.550295Z

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source=arxiv_source observed=2026-08-06T19:09:14.550295Z digest=sha256:15e0064a78a2e83c250f3a50f3d57b7751c18e045d8514b708419ab45647c855

Observation c2c64683-0130-4245-89f9-f009653aa16d · outbound

This paper cites Gonzalez, Hao Zhang, and Ion Stoica.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Gonzalez, Hao Zhang, and Ion Stoica

Reference 16

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no resolver link, observed 2026-08-06T19:09:14.678988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:14.678988Z digest=sha256:d995c7b5084b35dd3a8ea29f24c25e2eab12d808cfcd7cf05a9e2009b9fa709d

Observation 6c9c9144-1e9a-43b3-b9f8-ead152f424c8 · outbound

This paper cites an unresolved cited work.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Unresolved cited work

Reference 17

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no resolver link, observed 2026-08-06T19:09:14.783425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:14.783425Z digest=sha256:958cb7de51a668113cb4b76c151392e90875c120dcba35f5f21cf05ea7669b2e

Observation 28ec7371-2137-4ba6-ab17-ce307adb0be9 · outbound

This paper cites GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration

Reference 18

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no resolver link, observed 2026-08-06T19:09:14.944813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:14.944813Z digest=sha256:6a66cf14a9797d2ff08228fae9d69941b3c7c8c3e4feece4757e975032092cfa

Observation 8d718d62-d47f-437b-9ca0-44fc2781f93c · outbound

This paper cites an unresolved cited work.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Unresolved cited work

Reference 19

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-06T19:09:15.072225Z digest=sha256:86baa9d02c88b389dfb8b06d9aa70cca81af6007238532bd696915ef2ba6c31e

Observation bf2de7b2-bf61-48df-87a1-4fbdc27bd79b · outbound

This paper cites DeepSeek-V3 Technical Report.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs DeepSeek-V3 Technical Report

Reference 20

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no resolver link, observed 2026-08-06T19:09:15.202439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:15.202439Z digest=sha256:b04be239486a0641ec1d6322c9908a73f91fd4dfe426427fe5b48d06280327ee

Observation 651510c7-f053-4b8d-a861-bca739c13eaa · outbound

This paper cites VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language Models.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language Models

Reference 21

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no resolver link, observed 2026-08-06T19:09:15.339967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:15.339967Z digest=sha256:5404b1f46231418c073887fde597780d5bde0a0d760cc28a2db200bb7d9eb7d6

Observation e4e182b3-3f62-43ad-a85b-9b4b60d23d5c · outbound

This paper cites LLM-QAT: Data-Free Quantization Aware Training for Large Language Models.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 22

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no resolver link, observed 2026-08-06T19:09:15.456220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:15.456220Z digest=sha256:58de0e4a5212b08b216e877f61114c5f682816197d3eded9eb040f46a075da3c

Observation e11d7ebf-ad35-46e8-b83b-6e6e0e7afb57 · outbound

This paper cites KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache

Reference 23

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no resolver link, observed 2026-08-06T19:09:15.612246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:15.612246Z digest=sha256:a5d64f23a01e078f2b3f319a1bedb668ff070fa7db3c1a0d836ab21d05371a9e

Observation 3e152096-429f-407e-a889-11a15f1decf7 · outbound

This paper cites PV-Tuning: Beyond Straight-Through Estimation for Extreme LLM Compression.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs PV-Tuning: Beyond Straight-Through Estimation for Extreme LLM Compression

Reference 24

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no resolver link, observed 2026-08-06T19:09:15.725978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:15.725978Z digest=sha256:48fbe17063fcb5087721b0c613a9d526da0c1a37e14325409b18d7034d86dc15

Observation 7619b8f7-de18-48de-834b-aebcfddc8a0a · outbound

This paper cites an unresolved cited work.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Unresolved cited work

Reference 25

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raw_fallback, observed 2026-08-06T19:09:18.376825Z

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=2026-08-06T19:09:15.809980Z digest=sha256:90a70d4155e26b671843658782e95351b49fdc81ed69444b703173855597e66d

Observation 9e0187db-8278-41e5-a27b-5244df8b9c57 · outbound

This paper cites MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning

Reference 26

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no resolver link, observed 2026-08-06T19:09:15.867188Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:15.867188Z digest=sha256:d2032ee6b4e01de59dfd9f9da255087444f96eefc627873494601037de573ac8

Observation 514785f6-3676-4f0a-837f-ec11753a5c96 · outbound

This paper cites Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Reference 27

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no resolver link, observed 2026-08-06T19:09:15.947268Z

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source=arxiv_source observed=2026-08-06T19:09:15.947268Z digest=sha256:8ec1d22f850f89e3309c43d60e7961e6f847dbe1a4c7292173b5aea0f5be2b5b

Observation 90d31e21-942f-4bbe-a86c-ce80640bcbad · outbound

This paper cites an unresolved cited work.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Unresolved cited work

Reference 28

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unresolved
raw_fallback, observed 2026-08-06T19:09:18.211560Z

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=2026-08-06T19:09:16.019235Z digest=sha256:a5732b8d57162d7688fd332c758fc7489094ab8d8c9fd4e25ccc2fe0486af283

Observation 844df51a-8dcc-4883-97e2-cff04b4e25a6 · outbound

This paper cites QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks

Reference 29

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no resolver link, observed 2026-08-06T19:09:16.104514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:16.104514Z digest=sha256:081cca88daf9a241532ff20bdd36815d55ee2534eada3cdbdbf0b269c5671d57

Observation 14643411-d717-4f2b-865f-1e77d05e16e6 · outbound

This paper cites an unresolved cited work.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Unresolved cited work

Reference 30

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no resolver link, observed 2026-08-06T19:09:16.172716Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:16.172716Z digest=sha256:538acf7eca0695f5bb424b5e65aa511f051102bcc1a246a922de304c23fa426d

Observation 8a125a0b-1da2-499f-9967-609e08831712 · outbound

This paper cites GPTVQ: The Blessing of Dimensionality for LLM Quantization.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs GPTVQ: The Blessing of Dimensionality for LLM Quantization

Reference 31

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no resolver link, observed 2026-08-06T19:09:16.255194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:16.255194Z digest=sha256:e11733fa70567dac2de7e68915c2f72bfd605df37c75aa3390f922b0e483f4b4

Observation d1f19044-b3b0-4588-b17b-4f98a31f9d69 · outbound

This paper cites BitNet: Scaling 1-bit Transformers for Large Language Models.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs BitNet: Scaling 1-bit Transformers for Large Language Models

Reference 32

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no resolver link, observed 2026-08-06T19:09:16.341546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:16.341546Z digest=sha256:3d7c7aee268f3877d0cd4ad224c4e9f869cc574e07a4c21e9221d37fa743a94b

Observation 2b1a711b-f56c-4f39-ba0d-aa9fd0ccd6d5 · outbound

This paper cites CMATH: Can Your Language Model Pass Chinese Elementary School Math Test?.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs CMATH: Can Your Language Model Pass Chinese Elementary School Math Test?

Reference 33

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no resolver link, observed 2026-08-06T19:09:16.450823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:16.450823Z digest=sha256:cd4165e1b26f01da91c4335f165e197bfae57dd9a627db73df2afd1b9f2bd1fa

Observation ec343832-99a7-42c9-abff-106eb6741309 · outbound

This paper cites an unresolved cited work.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Unresolved cited work

Reference 34

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no resolver link, observed 2026-08-06T19:09:16.529853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:16.529853Z digest=sha256:155e595b7aadbbd538c40bf3f4005bc9c5f5da548415349620aaf9fe489c431d

Observation b7415f28-0d79-4155-a9b3-bf1fa81e3d9f · outbound

This paper cites OneBit: Towards Extremely Low-bit Large Language Models.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs OneBit: Towards Extremely Low-bit Large Language Models

Reference 35

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no resolver link, observed 2026-08-06T19:09:16.636435Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:16.636435Z digest=sha256:6da4f1ed3a79c5c68aad49cf173c90281894493c378c850dc4bafd4ba7d543e9

Observation 347ac852-7bf1-46bc-942b-21eef900b8c5 · outbound

This paper cites Qwen3 Technical Report.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Qwen3 Technical Report

Reference 36

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no resolver link, observed 2026-08-06T19:09:16.740132Z

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source=arxiv_source observed=2026-08-06T19:09:16.740132Z digest=sha256:b9182b88b0fdb8737cb9cab8ace77eb68c1f8fa438098ef47ba3eac4e9a4afc6

Observation 6b517bf6-9853-4281-b76f-901aafddcbc8 · outbound

This paper cites Qwen2 Technical Report.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Qwen2 Technical Report

Reference 37

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no resolver link, observed 2026-08-06T19:09:16.889877Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:16.889877Z digest=sha256:e2ec89d8aeb39492e7b31a2c4c2bca2bf2bf88fef706281d924e2f24a4eb8a98

Observation ef89513c-90db-42e1-bc68-680dad0b4532 · outbound

This paper cites Qwen2.5 Technical Report.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs Qwen2.5 Technical Report

Reference 38

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:17.004127Z digest=sha256:a71b85ed8d601b6351c85919b35850c897f97e164d3df399913324f9e09223ca

Observation 28fb5980-f9e9-4941-af17-81ce411a7a1f · outbound

This paper cites online" 'onlinestring :=.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs online" 'onlinestring :=

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T19:09:17.091141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:17.091141Z digest=sha256:251751bcd559cdf5fb6f5827684eed9125d7b315f01d4e21d8067f9a165902a8

Observation 04f9e3bf-b5df-4a19-8831-cebf0749d5ba · outbound

This paper cites write newline.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs write newline

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T19:09:17.207868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:17.207868Z digest=sha256:b376de2e9b473640f151439a91b663af7ab5a7b224ea90695e45c45d3f0d0067

Pith citing papers

Observation ac703c6c-393c-4c3c-bea2-82529cbb6db5 · inbound

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization cites this paper.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-07-03T04:57:38.331678Z

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=2026-06-27T13:32:32.996055Z digest=sha256:526ea74112dc51401da319a97c2138ab0fa78767cec5aaafa028fec6f5630bb7

Observation 291b7156-4a4c-43fc-ab4e-2557744742a2 · inbound

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization cites this paper.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-07-02T22:47:25.261681Z

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=2026-07-02T22:47:05.759610Z digest=sha256:c64f1ba08869acbc160403ec2b40ff3984272df6b4777aa6e29e8d341a50724f