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Paper Citation Record · LEDGER

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks

As of 14 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 2 inbound Pith citation observations for arXiv:2606.03458.

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

pith.paper-citation-record.v1
2606.03458 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T11:36:34.669513Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T00:43:50.881069Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

37 of 37 outbound references displayed

  • verified exact5
  • verified fuzzy0
  • unresolved30
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1658b75d-390c-4b66-8d5f-23df83a4cff2 · outbound

This paper cites Phi-4 Technical Report.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Phi-4 Technical Report

Reference 1

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verified exact
local_arxiv, observed 2026-07-02T01:46:26.339880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:7ce673f4a015f4756fca0176287c0e702d2a346eda785af17cb3265c88ec9c43

Observation d9c2af66-94bb-4f93-b8a4-9bbcd3cbe868 · outbound

This paper cites Quarot: Outlier-free 4-bit inference in rotated llms.Advances in Neural Information Processing Systems, 37:100213– 100240, 2024.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Quarot: Outlier-free 4-bit inference in rotated llms.Advances in Neural Information Processing Systems, 37:100213– 100240, 2024

Reference 2

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:a8e00540476f63e11cea882441e626b9520e99a697b629e8a8383b9b4803a361

Observation 3b20ce20-ce12-47b7-a1a6-c53db703815f · outbound

This paper cites Longbench: A bilingual, multitask benchmark for long context understanding.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Longbench: A bilingual, multitask benchmark for long context understanding

Reference 3

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:2154a3ad1ae16d93438dd0c1a0c24de557760de3d2f7b365b28e5df6ae25caa3

Observation ef4dcb9c-e043-4f46-b3a9-daa30a135deb · outbound

This paper cites Forest-of-thought: Scaling test-time compute for enhancing LLM reasoning.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Forest-of-thought: Scaling test-time compute for enhancing LLM reasoning

Reference 4

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:08f2b8f218cd3d031d46af827ad59ae2537f08a091167fed60bc6d1bf7e857f5

Observation fb843ad2-9d48-4931-a49c-23ef05a0b74b · outbound

This paper cites PyramidKV: Dynamic KV cache compression based on pyramidal information funneling.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks PyramidKV: Dynamic KV cache compression based on pyramidal information funneling

Reference 5

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:57e3f3e28ac3163e0b35cbc6ee51015fa943a2ff0f1424a6eb170d1d0c1be9b2

Observation ad73cda1-736b-4b7b-844f-c44b244546b5 · outbound

This paper cites Quip: 2-bit quanti- zation of large language models with guarantees.Advances in neural information processing systems, 36:4396–4429, 2023.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Quip: 2-bit quanti- zation of large language models with guarantees.Advances in neural information processing systems, 36:4396–4429, 2023

Reference 6

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:b9d8327954355d9e500f6487fe9176d74b4d00d216c983169538f2a194a094c7

Observation 864ddb71-da30-457d-a202-7fbb3174d739 · outbound

This paper cites an unresolved cited work.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Unresolved cited work

Reference 7

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:935d4c44824a38287e4197fcd245599061228973f2f959129c5afd7f6f3525fb

Observation 2389d9c7-a401-479b-88f9-56ef8fd6ede7 · outbound

This paper cites The Llama 3 Herd of Models.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks The Llama 3 Herd of Models

Reference 8

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local_arxiv, observed 2026-07-02T01:46:26.337211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:68b64482981756b91de7558d43fe7aa83b3e9ae7dfd19b0d569ae2897155d371

Observation ca8e92af-7a24-4193-ad91-020819830cae · outbound

This paper cites KVQuant: Towards 10 million context length llm inference with kv cache quantization.Advances in Neural Information Processing Systems, 37:1270–1303, 2024.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks KVQuant: Towards 10 million context length llm inference with kv cache quantization.Advances in Neural Information Processing Systems, 37:1270–1303, 2024

Reference 9

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:e39cb2334cdeb92e4a37d46f4a3d047bb20b737ee3b93aad32688b5669cfe384

Observation e1a16110-6aad-48ac-8a9c-f044136a06a3 · outbound

This paper cites Needle in a haystack-pressure testing llms.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Needle in a haystack-pressure testing llms

Reference 10

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:ca6e3309f94e84116ddff25ad8836a386d207e344ec515ad794780acc443a155

Observation f554b56d-b289-4f18-962d-7f9f82ff3d45 · outbound

This paper cites Lee, Sangdoo Yun, and Hyun Oh Song.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Lee, Sangdoo Yun, and Hyun Oh Song

Reference 11

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:8d053c5054c65a2958e8a740361104b0a6bffe9b4954e9578c7743f182e515ea

Observation a5845339-fc7a-4b42-ab5a-a627f3958600 · outbound

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

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Gonzalez, Hao Zhang, and Ion Stoica

Reference 12

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:abb99376f87fea5111d8c1147b6b6fc1750da0bb8ad08804a7055db7a5812147

Observation 77fd167f-c433-4771-8b42-c440347275dc · outbound

This paper cites How long can context length of open-source LLMs truly promise? InNeurIPS 2023 Workshop on Instruction Tuning and Instruction Following, 2023.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks How long can context length of open-source LLMs truly promise? InNeurIPS 2023 Workshop on Instruction Tuning and Instruction Following, 2023

Reference 13

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:00b4bc5fac2d7c1843234caf1dc609c8e35159cc73a9f8a6fdf82b040855ee72

Observation 432e46cf-7267-4581-ac3b-e3d59dfd9445 · outbound

This paper cites Snapkv: Llm knows what you are looking for before generation.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Snapkv: Llm knows what you are looking for before generation

Reference 14

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:cf5f85e5e0cf46da44403598fd17acc5bf71b5334d82e67003fac27b2c0ccff7

Observation fe4a6ef5-f06f-45e6-b0bd-306eafcd01ff · outbound

This paper cites Let’s verify step by step.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Let’s verify step by step

Reference 15

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:1b1f827080b8bbd066ff0a54994de007882ce989d64eda1c1405d16269aa7110

Observation 4f159434-a3f8-42e6-8552-63f5615cc130 · outbound

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

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 16

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local_arxiv, observed 2026-07-02T01:46:26.345515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:c973e096203be0bb0d16289273def0c2698e71cbf166330e70aefe446291a57d

Observation 5d5f6d12-bb0c-4674-9e2c-5e2ece592a7e · outbound

This paper cites Spinquant: LLM quantization with learned rotations.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Spinquant: LLM quantization with learned rotations

Reference 17

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:5ed6cff480b14f07b1ef255b4e4a08d6ed2975a13c4a8ce691c1a499f5925ccd

Observation ff49c2b2-772e-411c-990a-3f346392d2e4 · outbound

This paper cites Scissorhands: Exploiting the persistence of importance hypothesis for llm kv cache compression at test time.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Scissorhands: Exploiting the persistence of importance hypothesis for llm kv cache compression at test time

Reference 18

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:95dc23070bc47a4d0083fd50f469ff0ff9a7b54abe7f505d4ae6b0bafd27dc3c

Observation f94d4603-ad73-4fb3-90d5-dd0d432843c5 · outbound

This paper cites Kivi: A tuning-free asymmetric 2bit quantization for kv cache.Proceedings of Machine Learning Research, 235:32332–32344, 2024.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Kivi: A tuning-free asymmetric 2bit quantization for kv cache.Proceedings of Machine Learning Research, 235:32332–32344, 2024

Reference 19

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:7698d961ee8e64fcc9b0726792dc86fbed9708f136435e088282d54a8d2255a4

Observation fc85ced5-dfdd-45ff-af15-fc0c9b82e4b1 · outbound

This paper cites Pushing the limits of large language model quantization via the linearity theorem.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Pushing the limits of large language model quantization via the linearity theorem

Reference 20

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:cafa4d1eec5b0ca9b9891fcb17de9b1421b5a6214d9d35148cdd39c5a9ace49e

Observation 21d89b13-182e-4e98-9799-4f3d674d268e · outbound

This paper cites s1: Simple test-time scaling.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks s1: Simple test-time scaling

Reference 21

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:8418c52087b3ceb6aec9203ff95a64c49fe7296d261f5dac933321a05ab9aa1c

Observation 6cc7018f-38a1-4800-8252-90eff1af227b · outbound

This paper cites Sinq: Sinkhorn-normalized quantization for calibration-free low-precision llm weights.arXiv preprint arXiv:2509.22944, 2025.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Sinq: Sinkhorn-normalized quantization for calibration-free low-precision llm weights.arXiv preprint arXiv:2509.22944, 2025

Reference 22

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arxiv_id, observed 2026-07-02T01:46:26.331409Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:ec4d2b061d4e0d1759c226667876554169a1cd39f4524725af6456d9f2726a0a

Observation 0f4f16e8-1df8-4145-98cd-576effc43fbf · outbound

This paper cites Learning to reason with llms, September 2024.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Learning to reason with llms, September 2024

Reference 23

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:8f0d1c38213b3c4085b7a63a2f250d04694afb4f52b94786bb44933358791446

Observation 40f910ba-1120-4faa-ae53-9d4561b7fadf · outbound

This paper cites Thinking vs.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Thinking vs

Reference 24

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:d69f6b4206d4a201554bfba50447284d4a24a38312b81a96edb429834498f257

Observation 56754088-b643-40a8-82a7-1f821b525adf · outbound

This paper cites Scaling LLM test-time com- pute optimally can be more effective than scaling parameters for reasoning.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Scaling LLM test-time com- pute optimally can be more effective than scaling parameters for reasoning

Reference 25

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:4d5c4e73e6317b7965e204a8251c22ce875e1dec9565218ea58a695133885e44

Observation f9c21708-70a2-4b50-a518-00c57274d591 · outbound

This paper cites Advancing Intelligent Sequence Modeling: Evolution, Trade-offs, and Applications of State-Space Architectures from S4 to Mamba.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Advancing Intelligent Sequence Modeling: Evolution, Trade-offs, and Applications of State-Space Architectures from S4 to Mamba

Reference 26

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local_arxiv, observed 2026-07-02T01:46:26.334468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:d2e65f97a6a6a5ea3457afe8c41ca4a430accbb4358925f243205a017756363a

Observation 5d04826b-1c03-422e-a0a6-4bc7ff3d4f6c · outbound

This paper cites MultiQA: An empirical investigation of generalization and transfer in reading comprehension.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks MultiQA: An empirical investigation of generalization and transfer in reading comprehension

Reference 27

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:edde3d859fbd66d9efe1a1a59173233bdf9821b9b88eeaeabd634f0772574b07

Observation 146bf95f-30a3-43e1-b519-031995353598 · outbound

This paper cites Qtip: Quantization with trellises and incoherence processing.Advances in Neural Information Processing Systems, 37:59597–59620, 2024.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Qtip: Quantization with trellises and incoherence processing.Advances in Neural Information Processing Systems, 37:59597–59620, 2024

Reference 28

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:8a788dc05bea604322ef695876820ce1a729f7788a8f0826a0632e11a956da5e

Observation 2bb46859-8b6f-49f4-8443-d8d68aa1b66d · outbound

This paper cites D2O: Dynamic discriminative operations for efficient long-context inference of large language models.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks D2O: Dynamic discriminative operations for efficient long-context inference of large language models

Reference 29

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:09a7427429fdb58ac5a9605b995acff9038b170439c4edb3bd30f0a9f6f82c3c

Observation 995583d3-41c8-4a2c-9640-463bfb5486d4 · outbound

This paper cites Polarquant: Leveraging polar transformation for key cache quantization and decoding acceleration.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Polarquant: Leveraging polar transformation for key cache quantization and decoding acceleration

Reference 30

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:1c2067a4c95869de8c99deafca038991f578746c38be8fd08e47460da4a7c282

Observation c31fe54c-7dae-42dd-9d4d-0046c6760ce0 · outbound

This paper cites Accurate and efficient 2-bit kv cache quantization with dynamic channel-wise precision boost.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Accurate and efficient 2-bit kv cache quantization with dynamic channel-wise precision boost

Reference 31

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arxiv_id, observed 2026-07-02T01:46:26.342770Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:4fd91c0941ee43d51c015e3b267ca4af664910a9919c5d9de76460552d702f41

Observation 69b5d934-f1bb-4ce7-af69-ca1c19151674 · outbound

This paper cites Qwen3 technical report, 2025.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Qwen3 technical report, 2025

Reference 32

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:d19f78a263a552a092d8b9c0ff1cd451bf6074c247a4b127758611dbfb044f10

Observation 51525976-e353-412c-9d7e-4567ba890f51 · outbound

This paper cites Turboquant: Online vector quantization with near-optimal distortion rate.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Turboquant: Online vector quantization with near-optimal distortion rate

Reference 33

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:169e2f15997116180c9d0c772bdb461b8aa36e63f3380c6df4bbf56a5879f53e

Observation d0525176-c9b9-4af1-8fbc-681df2da991b · outbound

This paper cites American invitational mathematics examination (aime) 2024, 2024.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks American invitational mathematics examination (aime) 2024, 2024

Reference 34

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no resolver link, observed 2026-06-28T11:36:34.669513Z

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:a5d0838eed3e78426939d7ae0863fe14d4eea250519859ac38e873adc6e684f6

Observation b8d3f5c2-c303-4814-ac7a-2be4a17cf598 · outbound

This paper cites Cam: Cache merging for memory-efficient LLMs inference.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Cam: Cache merging for memory-efficient LLMs inference

Reference 35

Resolution
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no resolver link, observed 2026-06-28T11:36:34.669513Z

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:bc3a763a8dab5684af50b3df0e8bc366a3df4e6353a9a767a068fbb1e21e5d65

Observation 3eb9764a-dfc1-4066-bb9b-8aeec967e0b1 · outbound

This paper cites H 2O: Heavy-hitter oracle for efficient generative inference of large language models.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks H 2O: Heavy-hitter oracle for efficient generative inference of large language models

Reference 36

Resolution
unresolved
no resolver link, observed 2026-06-28T11:36:34.669513Z

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:8a8e79381cc235922be85e69b8eb8ad4bb2a14606eaa6a3987a3129d69ca1791

Observation 155f5b82-7a7a-4111-ac13-ee8b27c0c924 · outbound

This paper cites The best thing to do in San Francisco is eat a sandwich and sit in Dolores Park on a sunny day.

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks The best thing to do in San Francisco is eat a sandwich and sit in Dolores Park on a sunny day

Reference 37

Resolution
malformed identifier
no resolver link, observed 2026-06-28T11:36:34.669513Z

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source=pdf_text observed=2026-06-28T11:36:34.669513Z digest=sha256:b4df1a1847e64feeb79a5d0ffc8ed4dc4ccb8fe8901ec3c97e53735e66a35270

Pith citing papers

Observation 1d311557-1096-41fd-8937-d4c3141f5e63 · inbound

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines cites this paper.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks

Reference 23

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unresolved
no resolver link, observed 2026-08-01T04:48:27.791567Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-01T04:48:27.791567Z digest=sha256:38a904744783bf395ea2247d5fc48c2f061595ce977ddc99da9c427329198124

Observation de616d7e-1a19-47ff-84ef-a652b35d22eb · inbound

WitCert: Sound Runtime Risk Observability and Gating for KV-Cache Quantization cites this paper.

WitCert: Sound Runtime Risk Observability and Gating for KV-Cache Quantization KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks

Reference 28

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no resolver link, observed 2026-08-03T00:43:50.881069Z

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source=pdf_text observed=2026-08-03T00:43:50.881069Z digest=sha256:13cd5987d161bf806a32bc9ea4e5581ef85b14a879fb69250956b7b843ac1159