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Paper Citation Record · LEDGER

Extreme Compression of Large Language Models via Additive Quantization

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 41 inbound Pith citation observations for arXiv:2401.06118.

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

pith.paper-citation-record.v1
2401.06118 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

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 41 of 41 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T23:03:44.588832Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T14:39:57.850108Z

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0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3dd06b7b-8bce-49cb-a565-a81aefc033e8 · inbound

LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models cites this paper.

LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models Extreme Compression of Large Language Models via Additive Quantization

Reference 2

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arxiv_id, observed 2026-05-11T12:40:02.208737Z

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=2026-05-11T12:40:02.129674Z digest=sha256:b0863bac5bf5a7c17055f848cfe2515c918cf0c412a8d3af28c0e2057c40a825

Observation d88f3d30-7423-4d92-b7f0-ba9d9a364a0d · inbound

SpinQuant: LLM quantization with learned rotations cites this paper.

SpinQuant: LLM quantization with learned rotations Extreme Compression of Large Language Models via Additive Quantization

Reference 4

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arxiv_id, observed 2026-05-15T15:52:34.665680Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T15:52:34.606853Z digest=sha256:efc3efa5e1799619f1c631cfd873db4f78836ebafe9bf212f3a1f31b72515ea5

Observation 658cba5f-2a5f-4553-a33f-3deabaab3908 · inbound

RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models cites this paper.

RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models Extreme Compression of Large Language Models via Additive Quantization

Reference 11

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no resolver link, observed 2026-08-07T23:03:44.588832Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:03:44.588832Z digest=sha256:57223d6d79872892f9bfeac67ea784e623d461107c3bc09e27571f8bcfcd1191

Observation daa42476-cae2-4cc7-a772-afad805be48b · inbound

NSNQuant: A Double Normalization Approach for Calibration-Free Low-Bit Vector Quantization of KV Cache cites this paper.

NSNQuant: A Double Normalization Approach for Calibration-Free Low-Bit Vector Quantization of KV Cache Extreme Compression of Large Language Models via Additive Quantization

Reference 11

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source=pdf_text observed=2026-08-07T14:42:20.242101Z digest=sha256:c7a76b5b6123c08693d6d3ffef28915ea2d0f14fa1699351444a74fea26c57f5

Observation 9f794de9-c001-4ba4-8925-f3957faa6e3a · inbound

FPTQuant: Function-Preserving Transforms for LLM Quantization cites this paper.

FPTQuant: Function-Preserving Transforms for LLM Quantization Extreme Compression of Large Language Models via Additive Quantization

Reference 38

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no resolver link, observed 2026-08-07T10:43:46.566561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:43:46.566561Z digest=sha256:16d54ecb3f0e1f31db1dc964650911e5f35bd3cc5403884c4cbc62768bc1deda

Observation bb9922a0-e0f7-4fd0-a282-f63fb37a2d3d · inbound

PCDVQ: Enhancing Vector Quantization for Large Language Models via Polar Coordinate Decoupling cites this paper.

PCDVQ: Enhancing Vector Quantization for Large Language Models via Polar Coordinate Decoupling Extreme Compression of Large Language Models via Additive Quantization

Reference 9

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no resolver link, observed 2026-08-07T10:42:40.742493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:42:40.742493Z digest=sha256:33506bf456a9d0d0a9f707c0646785bfabab02e0c789980670b6e4331535277f

Observation 58eaad20-086d-4325-9ae9-7323145700c7 · inbound

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models cites this paper.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Extreme Compression of Large Language Models via Additive Quantization

Reference 16

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source=pdf_text observed=2026-08-06T23:00:19.532049Z digest=sha256:f8a911555810512a8e194f9ffebaad18d8ab9eaea10272437d50f9c27912b591

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

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs cites this paper.

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

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

Observation 3a7063dd-279e-4af3-b72b-569d925c50c6 · inbound

Provable Post-Training Quantization: Theoretical Analysis of OPTQ and Qronos cites this paper.

Provable Post-Training Quantization: Theoretical Analysis of OPTQ and Qronos Extreme Compression of Large Language Models via Additive Quantization

Reference 6

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arxiv_id, observed 2026-05-18T23:52:53.045199Z

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=2026-05-18T23:52:06.036879Z digest=sha256:c2293e32a214d4d71d2df337608c9ef0c46f7422e224ef593d0cc58332411810

Observation dfc0ec88-b4a0-4c5d-9b0e-e792557c7531 · inbound

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs cites this paper.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Extreme Compression of Large Language Models via Additive Quantization

Reference 14

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:44.907408Z digest=sha256:41de5cb8ed5ffdb2d10b1ea21e22eae79791f9683318a1858e224bdbb3bf17f3

Observation 333bcaa5-066f-428e-9eee-ded1225fba65 · inbound

Motivating Next-Gen Accelerators with Flexible (N:M) Activation Sparsity via Benchmarking Lightweight Post-Training Sparsification Approaches cites this paper.

Motivating Next-Gen Accelerators with Flexible (N:M) Activation Sparsity via Benchmarking Lightweight Post-Training Sparsification Approaches Extreme Compression of Large Language Models via Additive Quantization

Reference 5

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arxiv_id, observed 2026-05-18T13:41:25.968867Z

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=2026-05-18T13:36:55.938673Z digest=sha256:47ca6c8b607743e5e3960f873659ef20cb8abcb8086373e61ac79f8f94ff9f3b

Observation cf5c1dce-4a29-48eb-9245-3601303fbc57 · inbound

SignRoundV2: Toward Closing the Performance Gap in Extremely Low-Bit Post-Training Quantization for LLMs cites this paper.

SignRoundV2: Toward Closing the Performance Gap in Extremely Low-Bit Post-Training Quantization for LLMs Extreme Compression of Large Language Models via Additive Quantization

Reference 2

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verified exact
arxiv_id, observed 2026-05-21T17:10:24.846706Z

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=2026-05-21T17:08:05.945757Z digest=sha256:296588e7fb144a7290805ffde829f248f1abb27adae745931d8f5876da3f7630

Observation cd9276b6-6e56-42e4-b282-ef7f11db4a9d · inbound

From Segments to Scenes: Temporal Understanding for Agentic Autonomous Driving via Vision-Language Models cites this paper.

From Segments to Scenes: Temporal Understanding for Agentic Autonomous Driving via Vision-Language Models Extreme Compression of Large Language Models via Additive Quantization

Reference 15

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no resolver link, observed 2026-08-03T18:28:17.210379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 489a29cb-7857-4be1-bf98-15d8e6810e65 · inbound

SALAAD: Sparse And Low-Rank Adaptation via ADMM for Large Language Model Inference cites this paper.

SALAAD: Sparse And Low-Rank Adaptation via ADMM for Large Language Model Inference Extreme Compression of Large Language Models via Additive Quantization

Reference 2024

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no resolver link, observed 2026-08-03T06:01:14.100670Z

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source=pdf_text observed=2026-08-03T06:01:14.100670Z digest=sha256:ea34543f6eced229378cf4151d56521c97f78c2f5ba12f346ea2ae827cffe134

Observation 45b46223-496e-4c88-ba72-22c31e4d0991 · inbound

BPDQ: Bit-Plane Decomposition Quantization on a Variable Grid for Large Language Models cites this paper.

BPDQ: Bit-Plane Decomposition Quantization on a Variable Grid for Large Language Models Extreme Compression of Large Language Models via Additive Quantization

Reference 5

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arxiv_id, observed 2026-05-21T14:14:12.382706Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation e5ef73dd-2ab6-4029-9439-b0f719b04bf2 · inbound

CoreQ: Learning-Free Mismatch Correction and Successive Rounding for Quantization cites this paper.

CoreQ: Learning-Free Mismatch Correction and Successive Rounding for Quantization Extreme Compression of Large Language Models via Additive Quantization

Reference 6

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arxiv_id, observed 2026-05-16T06:52:28.430581Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation f334d98c-2e02-47ea-ab38-a8fb93907250 · inbound

S2O: Early Stopping for Sparse Attention via Online Permutation cites this paper.

S2O: Early Stopping for Sparse Attention via Online Permutation Extreme Compression of Large Language Models via Additive Quantization

Reference 4

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arxiv_id, observed 2026-05-15T19:36:32.866811Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 6ba3859a-434d-4e99-95de-461bee102348 · inbound

ECG Foundation Models and Medical LLMs for Agentic Cardiovascular Intelligence at the Edge: A Review and Outlook cites this paper.

ECG Foundation Models and Medical LLMs for Agentic Cardiovascular Intelligence at the Edge: A Review and Outlook Extreme Compression of Large Language Models via Additive Quantization

Reference 99

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arxiv_id, observed 2026-05-13T20:28:14.274229Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 32fc55e5-b72b-42a9-a150-90d68dcd6960 · inbound

FP4 Explore, BF16 Train: Diffusion Reinforcement Learning via Efficient Rollout Scaling cites this paper.

FP4 Explore, BF16 Train: Diffusion Reinforcement Learning via Efficient Rollout Scaling Extreme Compression of Large Language Models via Additive Quantization

Reference 54

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arxiv_id, observed 2026-05-11T05:25:56.614042Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 4b9d5074-6984-40e8-a8c0-1370479d3c14 · inbound

GSQ: Highly-Accurate Low-Precision Scalar Quantization for LLMs via Gumbel-Softmax Sampling cites this paper.

GSQ: Highly-Accurate Low-Precision Scalar Quantization for LLMs via Gumbel-Softmax Sampling Extreme Compression of Large Language Models via Additive Quantization

Reference 9

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arxiv_id, observed 2026-05-10T05:36:02.303475Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 3a17d4df-ac86-439a-9dfd-bebaa3d296e9 · inbound

GSQ: Highly-Accurate Low-Precision Scalar Quantization for LLMs via Gumbel-Softmax Sampling cites this paper.

GSQ: Highly-Accurate Low-Precision Scalar Quantization for LLMs via Gumbel-Softmax Sampling Extreme Compression of Large Language Models via Additive Quantization

Reference 9

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arxiv_id, observed 2026-05-19T18:02:42.259097Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 0dbeb0ac-ca5b-4fbc-8c29-b34318db1bef · inbound

SAW-INT4: System-Aware 4-Bit KV-Cache Quantization for Real-World LLM Serving cites this paper.

SAW-INT4: System-Aware 4-Bit KV-Cache Quantization for Real-World LLM Serving Extreme Compression of Large Language Models via Additive Quantization

Reference 5

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arxiv_id, observed 2026-05-10T03:14:08.292383Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T03:09:51.453839Z digest=sha256:65f3d5531c38b7b54a49dd5a4bf8fb056a4ef18f227ad313d8300dc8915a4c8b

Observation 6a650f0d-7fa8-4f00-b4a7-398ca6af3654 · inbound

LBLLM: Lightweight Binarization of Large Language Models via Three-Stage Distillation cites this paper.

LBLLM: Lightweight Binarization of Large Language Models via Three-Stage Distillation Extreme Compression of Large Language Models via Additive Quantization

Reference 39

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arxiv_id, observed 2026-05-11T12:46:04.531356Z

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source=arxiv_source observed=2026-05-10T03:04:14.900791Z digest=sha256:1824d90c7a6537f6a4d4fa7285a9b15f1453ca076af51af29da375a157ebfad1

Observation 48269ae2-16fa-4a43-ab45-baf1c23ae9cf · inbound

GAMMA: Global Bit Allocation for Mixed-Precision Models under Arbitrary Budgets cites this paper.

GAMMA: Global Bit Allocation for Mixed-Precision Models under Arbitrary Budgets Extreme Compression of Large Language Models via Additive Quantization

Reference 45

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arxiv_id, observed 2026-05-20T12:28:16.821701Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-20T12:25:39.417436Z digest=sha256:b4d32042807e8a774b9f98a5bc0f0bc2dccc3a65b53be187ec2860646944c77a

Observation 2a2a897d-b308-4140-bfad-424919528f20 · inbound

ActQuant: Sub-4-bit Action-Guided Quantization for Vision-Language-Action Models cites this paper.

ActQuant: Sub-4-bit Action-Guided Quantization for Vision-Language-Action Models Extreme Compression of Large Language Models via Additive Quantization

Reference 7

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arxiv_id, observed 2026-07-01T15:05:47.976295Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T17:54:56.386488Z digest=sha256:d8116554cc80c3b388209ae98f3304b06a206afcfaf6acb1e2a6857d6b40a377

Observation 3cda3c24-9941-44c3-89d3-d58c3e24e172 · inbound

Influence-Inspired Spectral Rotations for Extreme Low-Bit LLM Quantization cites this paper.

Influence-Inspired Spectral Rotations for Extreme Low-Bit LLM Quantization Extreme Compression of Large Language Models via Additive Quantization

Reference 13

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arxiv_id, observed 2026-06-30T12:14:39.062248Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation d72d6847-4844-4887-8057-75c4c71efd3f · inbound

WINDQuant: Weight-Informed Neural Decision-Making for Global Mixed-Precision LLM Quantization cites this paper.

WINDQuant: Weight-Informed Neural Decision-Making for Global Mixed-Precision LLM Quantization Extreme Compression of Large Language Models via Additive Quantization

Reference 1

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arxiv_id, observed 2026-06-29T19:33:53.959601Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation bc8f316e-7897-4f4a-ada1-14ead50af142 · inbound

HARP: Hadamard-Preconditioned Adaptive Rotation Processor for Extreme LLM Quantization cites this paper.

HARP: Hadamard-Preconditioned Adaptive Rotation Processor for Extreme LLM Quantization Extreme Compression of Large Language Models via Additive Quantization

Reference 1

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arxiv_id, observed 2026-06-29T13:53:29.657669Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T09:16:37.939055Z digest=sha256:23af81f551cc3af2f91b4e0e3795f4d46eba310f9bd7c09ee7ad32caa29c3a29

Observation 3a953875-6e80-4582-ac2d-67aab035d42e · inbound

Qift: Shift-Friendly No-Zero W2 Post-Training Quantization for Rotated W2A4/KV4 LLM Inference cites this paper.

Qift: Shift-Friendly No-Zero W2 Post-Training Quantization for Rotated W2A4/KV4 LLM Inference Extreme Compression of Large Language Models via Additive Quantization

Reference 10

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metadata mismatch
arxiv_id, observed 2026-07-01T22:06:15.957269Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T15:49:41.836888Z digest=sha256:62b9ab33541733ba66a8bc1dfa58f9a619fc3fbf9c7b9752db52485c2ef2a353

Observation 13e220e0-5905-4fd6-96e1-1c607db14c73 · inbound

Rethinking the Role of Tensor Decompositions in Post-Training LLM Compression cites this paper.

Rethinking the Role of Tensor Decompositions in Post-Training LLM Compression Extreme Compression of Large Language Models via Additive Quantization

Reference 7

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metadata mismatch
arxiv_id, observed 2026-07-02T01:46:26.898431Z

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=2026-06-28T11:31:25.851340Z digest=sha256:4f461d86f2092210a0bae172579558efb3d638c8826b03542545be22a53d6041

Observation f4e9c52e-ef22-423e-affa-381ea50aecf8 · inbound

LiftQuant: Continuous Bit-Width LLM via Dimensional Lifting and Projection cites this paper.

LiftQuant: Continuous Bit-Width LLM via Dimensional Lifting and Projection Extreme Compression of Large Language Models via Additive Quantization

Reference 48

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arxiv_id, observed 2026-07-02T02:06:27.011046Z

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=2026-06-28T11:14:03.535306Z digest=sha256:bfc9c7aee338c2fe89206817a504b3c7929d70ef25d2f58108c97a0fc1a796e7

Observation 1ea1b4fe-faf0-407b-b888-28787d78b9f9 · inbound

LiftQuant: Continuous Bit-Width LLM via Dimensional Lifting and Projection cites this paper.

LiftQuant: Continuous Bit-Width LLM via Dimensional Lifting and Projection Extreme Compression of Large Language Models via Additive Quantization

Reference 48

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metadata mismatch
arxiv_id, observed 2026-06-30T11:24:38.301078Z

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=2026-06-30T11:17:53.736872Z digest=sha256:6c00ff7a0f486448b1539387dd684bcf8a41c37745f6237229c48db77c30ca53

Observation 83aedfc9-6608-44c9-bd81-e3f1d9ee33ca · inbound

Multi-Bitwidth Quantization for LLMs Using Additive Codebooks cites this paper.

Multi-Bitwidth Quantization for LLMs Using Additive Codebooks Extreme Compression of Large Language Models via Additive Quantization

Reference 67

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arxiv_id, observed 2026-07-03T13:48:21.354907Z

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=2026-06-27T07:29:14.923431Z digest=sha256:f9d09d0c1d642f7b4e5470bd021fc678b94b55ac4b6de96a65e580570cc9258d

Observation c38210ad-15bc-46e6-a32b-2e8b5f66b6ea · inbound

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems cites this paper.

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems Extreme Compression of Large Language Models via Additive Quantization

Reference 150

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T11:09:46.230247Z

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=2026-06-26T08:09:57.542558Z digest=sha256:5418a4420c82611b1ef5b01b29cdd6e0fca9faff8c176e0daf2b7316317efec9

Observation c86b2b5d-32b6-49d8-833c-44c9cf9ff354 · inbound

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems cites this paper.

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems Extreme Compression of Large Language Models via Additive Quantization

Reference 150

Resolution
unresolved
no resolver link, observed 2026-08-02T10:27:18.293481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T10:27:18.293481Z digest=sha256:d17e58824b9a5c138fb45fd49c55b84b6d3931f61c5b23e2b590575570770706

Observation 07535700-f01f-4327-8453-3e5bdb230fd3 · inbound

Smaller Models, Unexpected Costs: Trade-offs in LLM Quantization for Automated Program Repair cites this paper.

Smaller Models, Unexpected Costs: Trade-offs in LLM Quantization for Automated Program Repair Extreme Compression of Large Language Models via Additive Quantization

Reference 19

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T14:39:57.851690Z

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=2026-06-26T03:10:37.068739Z digest=sha256:2de1707b5ca1e9561e5e4c0d7c22ae11e49ee31acd22064084477b1d6fa56a20

Observation 382d3d53-2e97-4f26-8029-f94b47b65942 · inbound

Smaller Models, Unexpected Costs: Trade-offs in LLM Quantization for Automated Program Repair cites this paper.

Smaller Models, Unexpected Costs: Trade-offs in LLM Quantization for Automated Program Repair Extreme Compression of Large Language Models via Additive Quantization

Reference 19

Resolution
unresolved
no resolver link, observed 2026-07-12T11:49:34.865484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T11:49:34.865484Z digest=sha256:73fdf17f49f39236ebca4f2364f89f4bc96940bc2d3881dc4fa401b7a9c0c344

Observation b72dd6dc-1cf9-4c3c-b5ed-fd9b823302c7 · inbound

Breaking the Rounding Trap: Securing LLMs against Quantization-Conditioned Backdoors cites this paper.

Breaking the Rounding Trap: Securing LLMs against Quantization-Conditioned Backdoors Extreme Compression of Large Language Models via Additive Quantization

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-06-30T08:04:28.755411Z

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=2026-06-30T07:47:18.350953Z digest=sha256:1cf4e4980fb3c6a11dcae5280808637f82710a280e4aa7cc6dbc9418966b2a0c

Observation a37e7a8f-29ce-45ad-818b-9a0fffe88d7f · inbound

Breaking the Rounding Trap: Securing LLMs against Quantization-Conditioned Backdoors cites this paper.

Breaking the Rounding Trap: Securing LLMs against Quantization-Conditioned Backdoors Extreme Compression of Large Language Models via Additive Quantization

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-04T04:39:06.778635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T04:39:06.778635Z digest=sha256:49222f234f5cfe1f6f8d8566c8d9209c40ed8eee74cf6f28a86a6d84e65d3ac5

Observation 7b6e680d-99cb-4fc7-8bfa-e3b9323788d2 · inbound

Reliability Scaling Laws for Quantized Large Language Models cites this paper.

Reliability Scaling Laws for Quantized Large Language Models Extreme Compression of Large Language Models via Additive Quantization

Reference 87

Resolution
unresolved
no resolver link, observed 2026-07-14T08:45:52.855783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T08:45:52.855783Z digest=sha256:0c1ed88b66b0df2ac9f406a9d251906fe484a92f77af38db163674ad295b875a

Observation 2fec4cf6-8036-4a8f-8ff8-cdab958a7770 · inbound

A Motion-Aware Vector Quantization Framework with Centroid Reuse for Efficient VLA Inference cites this paper.

A Motion-Aware Vector Quantization Framework with Centroid Reuse for Efficient VLA Inference Extreme Compression of Large Language Models via Additive Quantization

Reference 8

Resolution
unresolved
no resolver link, observed 2026-07-31T22:36:29.223928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T22:36:29.223928Z digest=sha256:2d8e9d4b0be644f63cb92264a21673c891295a37d3f8abfcc09fca3c02bbcd6d