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Paper Citation Record · LEDGER

Learned Step Size Quantization

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 58 inbound Pith citation observations for arXiv:1902.08153.

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

pith.paper-citation-record.v1
1902.08153 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 58 of 58 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 58 of 58 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T16:22:12.514507Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

296
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 31971a76-fc2c-4c49-9eb1-4b2ec9453ef5 · inbound

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale cites this paper.

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale Learned Step Size Quantization

Reference 131

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arxiv_id, observed 2026-05-13T13:35:36.073220Z

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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=2026-05-13T13:35:35.972596Z digest=sha256:16e6e12b1a5879b65da8f39531a8709185e8e0249eded5b0bae44633bbab1ed1

Observation 44c1c523-db5d-4199-9746-6dce1c83ad7c · inbound

AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration cites this paper.

AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration Learned Step Size Quantization

Reference 11

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arxiv_id, observed 2026-05-24T08:29:11.362464Z

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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=2026-05-24T08:27:35.798991Z digest=sha256:9260dcdfc3bb7f61031300d6bbc864809bfbecd6dbe019c89754cc0d50e7e0d4

Observation 1680614d-ac59-48fc-ab79-bc3cefb9a1c6 · inbound

Reclaiming Residual Knowledge: A Novel Paradigm to Low-Bit Quantization cites this paper.

Reclaiming Residual Knowledge: A Novel Paradigm to Low-Bit Quantization Learned Step Size Quantization

Reference 11

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arxiv_id, observed 2026-05-23T22:28:31.067884Z

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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=2026-05-23T22:25:53.700079Z digest=sha256:f11fe90f4dcab6502e832e69dc5f2589c39fc070e8bcc073ac4ea4ac2b5b32a2

Observation 53e7adea-934e-45a3-9350-eb09fae0bc33 · inbound

Nearly Lossless Adaptive Bit Switching cites this paper.

Nearly Lossless Adaptive Bit Switching Learned Step Size Quantization

Reference 2

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source=pdf_text observed=2026-08-09T16:22:12.514507Z digest=sha256:08dc8b2bc6cf9b5f2e37a00e516f90ad773ea412692e5b8c615fb91a3fb6212a

Observation d4f1fefe-c81d-44d3-84d5-d63e70f665ba · inbound

Efficient Diffusion Models: A Survey cites this paper.

Efficient Diffusion Models: A Survey Learned Step Size Quantization

Reference 16

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source=pdf_text observed=2026-08-09T16:13:35.860096Z digest=sha256:11d01f9219d2c35d86a6e8b3f365666ba73b116f890e2f65f3c8650135ab8ac6

Observation a684b590-357e-4f2b-823d-84224357e7ff · inbound

LowRA: Accurate and Efficient LoRA Fine-Tuning of LLMs under 2 Bits cites this paper.

LowRA: Accurate and Efficient LoRA Fine-Tuning of LLMs under 2 Bits Learned Step Size Quantization

Reference 11

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source=pdf_text observed=2026-08-08T10:26:45.429133Z digest=sha256:a005ec45c933909332bd4b9c790ca5450ccf4e331fb82f9ba745469fe9f10ff8

Observation 6b9dac8b-19f0-4c22-9bbe-e23ddb94b25c · inbound

AHCQ-SAM: Toward Accurate and Hardware-Compatible Post-Training Segment Anything Model Quantization cites this paper.

AHCQ-SAM: Toward Accurate and Hardware-Compatible Post-Training Segment Anything Model Quantization Learned Step Size Quantization

Reference 5

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arxiv_id, observed 2026-05-23T01:52:23.036648Z

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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=2026-05-23T01:48:34.562325Z digest=sha256:bf371ff0a8f245fc25840d834a13ecb5f64ffefd751f886b63aaeba11c68f04f

Observation 39e43c9c-7f1a-448c-8ae6-bde3be19a16c · inbound

Scaling Law for Quantization-Aware Training cites this paper.

Scaling Law for Quantization-Aware Training Learned Step Size Quantization

Reference 9

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source=pdf_text observed=2026-08-07T15:41:06.036806Z digest=sha256:eab829bdc324085130026303ee21617e522e9400ed9fca1c66c3d43afc0ef201

Observation 236c17b8-9918-47c9-aa7d-3e09aa1d7f80 · inbound

Dual Precision Quantization for Efficient and Accurate Deep Neural Networks Inference cites this paper.

Dual Precision Quantization for Efficient and Accurate Deep Neural Networks Inference Learned Step Size Quantization

Reference 1

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source=pdf_text observed=2026-08-07T15:36:05.491210Z digest=sha256:9132b217fa77473a132b3ce8c0f7e1397f405c67f8fc7d8c7a150b51b171eb4a

Observation 96c378ab-2551-4677-8817-b454a008e5d2 · inbound

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing cites this paper.

Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing Learned Step Size Quantization

Reference 7

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source=pdf_text observed=2026-08-07T15:07:22.600554Z digest=sha256:fa5325e8771d027ac967ca4bc1d4a2fe1aa585d6c8c44038f80d03af2cf8c1e5

Observation 71d6a732-72b7-470d-b92c-21e7eb3600e3 · inbound

Frequency Composition for Compressed and Domain-Adaptive Neural Networks cites this paper.

Frequency Composition for Compressed and Domain-Adaptive Neural Networks Learned Step Size Quantization

Reference 10

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source=pdf_text observed=2026-08-07T13:50:34.125519Z digest=sha256:db06968840683d87f736b5ad59cd673fcf65ec862a8b58ba6cef1c1a7c3c50ac

Observation c3481ddd-bf17-490d-863f-34eecde84714 · inbound

Flexible Mixed Precision Quantization for Learned Image Compression cites this paper.

Flexible Mixed Precision Quantization for Learned Image Compression Learned Step Size Quantization

Reference 20

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source=pdf_text observed=2026-08-07T11:52:58.474593Z digest=sha256:acc9a8344e69317405b4fa6cfe16da697b2d1b9cdc12164608febb19ddec94e3

Observation 40d849c3-31e1-42ab-8cce-2d293def07e2 · inbound

Structured Pruning and Quantization for Learned Image Compression cites this paper.

Structured Pruning and Quantization for Learned Image Compression Learned Step Size Quantization

Reference 39

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source=pdf_text observed=2026-08-07T11:51:38.003222Z digest=sha256:02eff234e3b4d01ce558e2b9b74aa187174656fa7a94776d12d03503704ac609

Observation 9768d41f-423b-434f-94b1-129a3380f40e · inbound

Unified Scaling Laws for Compressed Representations cites this paper.

Unified Scaling Laws for Compressed Representations Learned Step Size Quantization

Reference 7

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source=pdf_text observed=2026-08-07T11:39:52.179507Z digest=sha256:8b9a8fd60aadb8470337df4247a78bd0f579d948f389872d194ed77b78a41b86

Observation 7c51df52-81ac-42bb-a7a1-992de9239ea5 · inbound

ScalableHD: Scalable and High-Throughput Hyperdimensional Computing Inference on Multi-Core CPUs cites this paper.

ScalableHD: Scalable and High-Throughput Hyperdimensional Computing Inference on Multi-Core CPUs Learned Step Size Quantization

Reference 53

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source=pdf_text observed=2026-08-07T04:56:57.249212Z digest=sha256:4cc5c2e8b6fd2ae4bc06ae7a858ce784b1591058e951c12201141e82dd0a5d4f

Observation 07d7a2a6-20c0-47b9-939c-faf30ae1bf2e · inbound

TruncQuant: Truncation-Ready Quantization for DNNs with Flexible Weight Bit Precision cites this paper.

TruncQuant: Truncation-Ready Quantization for DNNs with Flexible Weight Bit Precision Learned Step Size Quantization

Reference 26

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source=pdf_text observed=2026-08-07T04:18:09.205283Z digest=sha256:aadac637e168cd44345478c58e56e2182c0b0c528e58f610e68dabc5f337a376

Observation 290b2395-8c77-4bbb-b477-f9a3d3714391 · inbound

GPLQ: A General, Practical, and Lightning QAT Method for Vision Transformers cites this paper.

GPLQ: A General, Practical, and Lightning QAT Method for Vision Transformers Learned Step Size Quantization

Reference 7

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source=pdf_text observed=2026-08-07T04:10:24.991159Z digest=sha256:671d9eebc34318da9caf4d188df37ebec09062506aaa58d092f0a974f522a6ee

Observation 8307382a-9527-4d6a-bbfc-f6b9999c0c6f · inbound

Compression Aware Certified Training cites this paper.

Compression Aware Certified Training Learned Step Size Quantization

Reference 10

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source=pdf_text observed=2026-08-07T01:07:47.498768Z digest=sha256:31242b60aa674e09f14551ec9bd92ac0d63048a55cb0389769010c932d844de4

Observation dccd5cfe-54e6-427a-9325-b1addcea781f · inbound

PQCAD-DM: Progressive Quantization and Calibration-Assisted Distillation for Extremely Efficient Diffusion Model cites this paper.

PQCAD-DM: Progressive Quantization and Calibration-Assisted Distillation for Extremely Efficient Diffusion Model Learned Step Size Quantization

Reference 33

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source=pdf_text observed=2026-08-06T23:42:35.252934Z digest=sha256:b17a149e2c5d3274fe42bf44f6e2f5d574bbf7e51aff10f0590621e2fbba3720

Observation 1764b4e4-73de-4d2d-9015-b1c14d93593c · inbound

MPQ-DMv2: Flexible Residual Mixed Precision Quantization for Low-Bit Diffusion Models with Temporal Distillation cites this paper.

MPQ-DMv2: Flexible Residual Mixed Precision Quantization for Low-Bit Diffusion Models with Temporal Distillation Learned Step Size Quantization

Reference 22

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source=pdf_text observed=2026-08-06T19:57:19.426181Z digest=sha256:f715292b48e44243d6ceffde2257031acd55a68cd6d44c2b5863fdb9ae51578e

Observation b4ac89f9-5cec-46f8-8778-f0398913346f · inbound

Is Quantization a Deal-breaker? Empirical Insights from Large Code Models cites this paper.

Is Quantization a Deal-breaker? Empirical Insights from Large Code Models Learned Step Size Quantization

Reference 35

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source=pdf_text observed=2026-08-06T17:56:21.315395Z digest=sha256:88b753ad201e11090478b7b69514e28a1e05ea06556877d56848a713bd8c644b

Observation 8b6f505e-be6e-4521-be51-583d6161aa85 · inbound

Post-Training Quantization of Generative and Discriminative LSTM Text Classifiers: A Study of Calibration, Class Balance, and Robustness cites this paper.

Post-Training Quantization of Generative and Discriminative LSTM Text Classifiers: A Study of Calibration, Class Balance, and Robustness Learned Step Size Quantization

Reference 7

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source=pdf_text observed=2026-08-06T17:55:14.139337Z digest=sha256:1b03509a4d6831495eb4000ad0611afd6b98e9bd6ed82c60fad776312cf88347

Observation cbfc8fdb-1a46-43e1-b2ad-11d343256647 · inbound

DMQ: Dissecting Outliers of Diffusion Models for Post-Training Quantization cites this paper.

DMQ: Dissecting Outliers of Diffusion Models for Post-Training Quantization Learned Step Size Quantization

Reference 12

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source=pdf_text observed=2026-08-06T16:42:11.799216Z digest=sha256:1d4784c47b9768bfb699cbdb0d27c28dc9c818e7525e76e7bb2e82745fe70ccc

Observation a237aaf0-7e3c-4e3e-b092-3296471d6481 · inbound

DFQ-ViT: Data-Free Quantization for Vision Transformers without Fine-tuning cites this paper.

DFQ-ViT: Data-Free Quantization for Vision Transformers without Fine-tuning Learned Step Size Quantization

Reference 10

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source=pdf_text observed=2026-08-06T16:09:07.022111Z digest=sha256:b7fb3a5f396ccc0c5836e1fbaaa2895301d27c6c274bdbf6394a303721ad336c

Observation dd440759-04de-4927-a98b-eb4bca742f94 · inbound

Task-Specific Zero-shot Quantization-Aware Training for Object Detection cites this paper.

Task-Specific Zero-shot Quantization-Aware Training for Object Detection Learned Step Size Quantization

Reference 15

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source=pdf_text observed=2026-08-06T15:05:21.429063Z digest=sha256:a51a95a22486fdbc8173e7972ba596b8db966e5f083be3a3ecfc33c50f01f40f

Observation 4a647b1d-9898-4422-b763-fdba6849a14c · inbound

MSQ: Memory-Efficient Bit Sparsification Quantization cites this paper.

MSQ: Memory-Efficient Bit Sparsification Quantization Learned Step Size Quantization

Reference 7

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source=pdf_text observed=2026-08-06T11:56:59.780872Z digest=sha256:cb4e610bdb4743451782d45be4fbb8fb281dbe65ed553fb9fb57b7ef49a5ddaf

Observation 41d0a812-6b18-4e6d-aa92-aa55a80c09a6 · inbound

Progressive Element-wise Gradient Estimation for Neural Network Quantization cites this paper.

Progressive Element-wise Gradient Estimation for Neural Network Quantization Learned Step Size Quantization

Reference 4

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source=pdf_text observed=2026-08-05T15:16:58.407678Z digest=sha256:224da6e00bbdc241d274cf09f8c211bdf66450d2bb033c8976bf235ba878093e

Observation 126dd45d-9b93-4862-a571-8cf62f5229ee · inbound

Quantization Meets OOD: Generalizable Quantization-aware Training from a Flatness Perspective cites this paper.

Quantization Meets OOD: Generalizable Quantization-aware Training from a Flatness Perspective Learned Step Size Quantization

Reference 8

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source=pdf_text observed=2026-08-05T13:12:23.842748Z digest=sha256:b057487e5893e01d6a54ff96a1e2f4f0e2d6c4b6a205baefc861a63a5e5bf843

Observation f612e707-561c-4ce3-94d2-17ee752e2e2e · inbound

TinyMusician: On-Device Music Generation with Knowledge Distillation and Mixed Precision Quantization cites this paper.

TinyMusician: On-Device Music Generation with Knowledge Distillation and Mixed Precision Quantization Learned Step Size Quantization

Reference 2020

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source=pdf_text observed=2026-08-05T13:12:14.403164Z digest=sha256:b56b7f75d8c9ddc31ba67dffc549f3b92a564f5d57fc279e6e895df1371c2e11

Observation cd70e39b-ba15-4377-b2c1-3dc24d5e704e · inbound

DPQuant: Efficient and Differentially-Private Model Training via Dynamic Quantization Scheduling cites this paper.

DPQuant: Efficient and Differentially-Private Model Training via Dynamic Quantization Scheduling Learned Step Size Quantization

Reference 17

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arxiv_id, observed 2026-05-18T19:11:46.648023Z

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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=2026-05-18T19:09:04.217591Z digest=sha256:601b9cdecbf4f1db667f3db04d631ecf109ce8f8265f51d46f60516751467d20

Observation 9b2ee982-5da9-4f62-a49b-3e11bbd87699 · inbound

QuantV2X: A Fully Quantized Multi-Agent System for Cooperative Perception cites this paper.

QuantV2X: A Fully Quantized Multi-Agent System for Cooperative Perception Learned Step Size Quantization

Reference 2023

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source=pdf_text observed=2026-08-05T10:50:16.862305Z digest=sha256:067101be76e07bd11a8e811e3470aa697655fde3ae0ca34386824935b3a9768d

Observation 998955bc-b234-451d-960a-ae836362f91a · inbound

CAGE: Curvature-Aware Gradient Estimation For Accurate Quantization-Aware Training cites this paper.

CAGE: Curvature-Aware Gradient Estimation For Accurate Quantization-Aware Training Learned Step Size Quantization

Reference 9

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source=pdf_text observed=2026-08-04T08:50:45.221727Z digest=sha256:b3ccd68b9e0374da5a3f702125e1f8c86f461fe9777182d9e655c82c664f88a7

Observation dea28714-5f1f-4ccc-b9e7-446ab3ec1a20 · inbound

BWTA: Accurate and Efficient Binarized Transformer by Algorithm-Hardware Co-design cites this paper.

BWTA: Accurate and Efficient Binarized Transformer by Algorithm-Hardware Co-design Learned Step Size Quantization

Reference 56

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arxiv_id, observed 2026-05-13T17:28:02.202298Z

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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=2026-05-13T17:26:54.609595Z digest=sha256:a35d3f4e08cbacea72c2a1e277d4a1c6bd03b616ce21aaf8abf7771aacf93f72

Observation 0153782f-2b55-49d7-902f-5212e6ee5eec · inbound

Prune-Quantize-Distill: An Ordered Pipeline for Efficient Neural Network Compression cites this paper.

Prune-Quantize-Distill: An Ordered Pipeline for Efficient Neural Network Compression Learned Step Size Quantization

Reference 15

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arxiv_id, observed 2026-05-13T17:08:01.005812Z

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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=2026-05-13T17:03:48.689643Z digest=sha256:8c08613d65deb91dc7318329020c86f11fdcbba52e40e8d4a04b94b27875b71e

Observation c81116b7-85bc-4a43-a97a-565e43699293 · inbound

Streaming Chain cites this paper.

Streaming Chain Learned Step Size Quantization

Reference 15

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source=pdf_text observed=2026-07-13T10:56:59.609600Z digest=sha256:b32ee7bf81bda5fde1a0a3de28f5d6e98fa1651a19471d510f388bd738157e55

Observation 42685933-42af-4882-96c2-39ca4de5a61d · 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 Learned Step Size Quantization

Reference 10

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arxiv_id, observed 2026-05-10T05:36:02.318550Z

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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=2026-05-10T05:29:51.182114Z digest=sha256:b56fdcf96e0b3dbb501300edf43e7ada8b3d4dfe8c3b806ac7a2ca7da13beaa3

Observation c6a48177-ecae-451d-a973-15c12e2ede31 · 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 Learned Step Size Quantization

Reference 10

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arxiv_id, observed 2026-05-19T18:02:42.262146Z

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=2026-05-19T18:01:08.514022Z digest=sha256:0d8c9b4d2482e5abb26e5673fb33d8c862203d11bae22e9f395920181d918cc5

Observation b6e4dcc6-8777-4049-a388-7ac1ff043371 · inbound

Network Edge Inference for Large Language Models: Principles, Techniques, and Opportunities cites this paper.

Network Edge Inference for Large Language Models: Principles, Techniques, and Opportunities Learned Step Size Quantization

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-05-11T20:16:10.524889Z

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=2026-05-08T09:45:57.201837Z digest=sha256:db18b4d372a1d677c00c24f6043ddc148c7d952fd8739e1a0227562045cbd179

Observation 67e0fdd0-457d-4a87-b0d2-48b67d6c06ad · inbound

Colinearity Decay: Training Quantization-Friendly ViTs with Outlier Decay cites this paper.

Colinearity Decay: Training Quantization-Friendly ViTs with Outlier Decay Learned Step Size Quantization

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T16:56:07.915496Z

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=2026-05-09T14:24:54.946996Z digest=sha256:06410a84cb1e264012be52dbc735fd1628ecd4506a639b1574c383a1690b3f7b

Observation 32018b6c-027a-49b0-ab6f-4a5177c8507a · inbound

OSAQ: Outlier Self-Absorption for Accurate Low-bit LLM Quantization cites this paper.

OSAQ: Outlier Self-Absorption for Accurate Low-bit LLM Quantization Learned Step Size Quantization

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:30:44.070205Z

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=2026-05-08T18:23:14.935801Z digest=sha256:e004f83d9150c3a9e2ac2444708943d31156254329c37d78ec5036fb7cefe5e1

Observation df43dc13-4ab7-4605-a063-e0f1984e1f4c · inbound

OSAQ: Outlier Self-Absorption for Accurate Low-bit LLM Quantization cites this paper.

OSAQ: Outlier Self-Absorption for Accurate Low-bit LLM Quantization Learned Step Size Quantization

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-12T03:01:18.227436Z

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=2026-05-12T02:59:00.997742Z digest=sha256:333bc76721970659e3b59f506c4d8b8840c9f0a55cff4925d1d27fef0e228d19

Observation 5d7ecf12-a9f5-44a5-915a-50a6b3a33633 · inbound

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale cites this paper.

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale Learned Step Size Quantization

Reference 26

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T06:06:28.066914Z

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=2026-05-12T04:33:41.411292Z digest=sha256:ca797369c9ba49ce40fdff08852b8e402d3a46da88b80bea0fc954bbfced5561

Observation a7bdc49f-cfb2-44af-aec9-66cc197757f5 · inbound

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale cites this paper.

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale Learned Step Size Quantization

Reference 26

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T04:59:46.115251Z

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=2026-05-15T04:55:01.973832Z digest=sha256:24c4d4ddbc2d326cad6bf031f333c86414186e9ed2bf7e75ae211227e8e8aecd

Observation 9157aa84-cdcf-4559-af53-99d65bf9047c · inbound

Nonlinear Bipolar Compensation: Handling Outliers in Post-Training Quantization cites this paper.

Nonlinear Bipolar Compensation: Handling Outliers in Post-Training Quantization Learned Step Size Quantization

Reference 10

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T20:59:01.912985Z

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=2026-05-20T20:55:10.360775Z digest=sha256:e03f429962f1e00c48057501c4467c7b6b482ddea3c8b70f6bd8740b611ab7e2

Observation 68dcdfb4-530a-43d8-b48e-cb0f73ed7839 · inbound

CAR-SAM: Cross-Attention Reconstruction for Post-Training Quantization of the Segment Anything Model cites this paper.

CAR-SAM: Cross-Attention Reconstruction for Post-Training Quantization of the Segment Anything Model Learned Step Size Quantization

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-05-19T21:32:47.912829Z

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=2026-05-19T21:30:10.628872Z digest=sha256:849d0b008f205964815ac71a42eae56390f598c1bae9ce543ac6e817e128ee24

Observation 03739a84-7a2e-490c-b52f-6047627a4e30 · inbound

When Bits Break Recourse: Counterfactual-Faithful Quantization cites this paper.

When Bits Break Recourse: Counterfactual-Faithful Quantization Learned Step Size Quantization

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-20T14:43:22.026533Z

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=2026-05-20T14:43:18.182586Z digest=sha256:12b19671d42a171a9e60d67f9e9726d6ae0c958905e6b29d78bd40316e184d9f

Observation bb2c1927-2b61-430c-9cb5-1118c699bc1b · inbound

When Bits Break Recourse: Counterfactual-Faithful Quantization cites this paper.

When Bits Break Recourse: Counterfactual-Faithful Quantization Learned Step Size Quantization

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-03T02:20:53.370884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T02:20:53.370884Z digest=sha256:04fd51b178a71660de71b9f56406b851f55b8538c2ad9d5683f2ecdf217809f7

Observation 6362ee4d-a4c7-4c58-a066-077ef16e8c3c · inbound

When Bits Break Recourse: Counterfactual-Faithful Quantization cites this paper.

When Bits Break Recourse: Counterfactual-Faithful Quantization Learned Step Size Quantization

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-04T05:08:29.585923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T05:08:29.585923Z digest=sha256:da4fb1bcaa3c1068fb99839c3f45cdcd36149b144a2e23b3d5584c840cbbc42e

Observation fbee18d4-50ba-4103-baef-d2f39146fd17 · inbound

Llamas on the Web: Memory-Efficient, Performance-Portable, and Multi-Precision LLM Inference with WebGPU cites this paper.

Llamas on the Web: Memory-Efficient, Performance-Portable, and Multi-Precision LLM Inference with WebGPU Learned Step Size Quantization

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-21T02:53:55.320139Z

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=2026-05-21T02:52:40.923230Z digest=sha256:37631c20c205e5c425ce4bdacd96c2f3b392c72254c8580ba4db498ab8713f88

Observation a2c54c39-4a01-4aaa-adfb-858f6b5abfa7 · inbound

Motion-Compensated Weight Compression cites this paper.

Motion-Compensated Weight Compression Learned Step Size Quantization

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-06-30T13:04:40.387726Z

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=2026-06-30T12:58:27.637822Z digest=sha256:afd8c9568853df20583beada1d9c4196c024c647baefdef43086cb76960604b0

Observation 80f51098-826e-4b32-9554-39700d4458cd · inbound

Alignment Collapse Under KV Cache Quantization: Diagnosis and Mitigation cites this paper.

Alignment Collapse Under KV Cache Quantization: Diagnosis and Mitigation Learned Step Size Quantization

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-07-01T22:16:16.072130Z

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=2026-06-28T15:37:34.129339Z digest=sha256:77cc527ea474b3e69312df49086359e6e54397ae971971e41747e6a6a2f0f397

Observation b99cdcb8-ee70-4299-84cb-3efeb6362a89 · inbound

Neural Network Quantization by Learning Low-Loss Subspaces cites this paper.

Neural Network Quantization by Learning Low-Loss Subspaces Learned Step Size Quantization

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T16:59:58.458592Z

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=2026-06-26T00:05:03.762579Z digest=sha256:c6a3b14a7dda23471212ae5ffc9fd23d94ee639f20307a535f1a6f9f6d46105b

Observation 039dfd3a-41b3-40b8-862e-476ed7c348e9 · inbound

Layerwise Progressive Freezing: A Training Scaffold for Depth-Scalable Binary Networks cites this paper.

Layerwise Progressive Freezing: A Training Scaffold for Depth-Scalable Binary Networks Learned Step Size Quantization

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-06-29T05:13:06.464635Z

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=2026-06-29T05:08:23.176105Z digest=sha256:24f61819c70e2e0abcb48600f1f692bf14dcd1938bfb39cb07a6b1308f266bd8

Observation 5af4991f-3a88-4d89-92cd-e4d247ad68a1 · inbound

Zero-Shot Quantization for Object Detectors using Off-the-Shelf Generative Models cites this paper.

Zero-Shot Quantization for Object Detectors using Off-the-Shelf Generative Models Learned Step Size Quantization

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T09:05:37.356845Z

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=2026-07-01T06:47:12.273391Z digest=sha256:b908dcf6a5ef3ae63ed1a7e2d25bcb2f8208188b5c97f7960b1b23def640fe9c

Observation 309faec2-c6d1-4dcb-ab1b-a5cd1144c729 · inbound

Zero-Shot Quantization for Object Detectors using Off-the-Shelf Generative Models cites this paper.

Zero-Shot Quantization for Object Detectors using Off-the-Shelf Generative Models Learned Step Size Quantization

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-02T09:19:34.334377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T09:19:34.334377Z digest=sha256:8e04d666f5b7950e13941b0eba967e817ee75955d6c0972a850cb9e2b2b4f07a

Observation f58b4862-c954-487e-bd95-a35a52059fd7 · inbound

Quantize with Confidence? An Empirical Study of Quantization for Code Generation cites this paper.

Quantize with Confidence? An Empirical Study of Quantization for Code Generation Learned Step Size Quantization

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-02T03:32:51.696835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T03:32:51.696835Z digest=sha256:39cc662aecda3c5d03dd910fcda2acfad187df709823ac2adea77165877cfda6

Observation 4cf1a8e3-2252-4309-8c31-797433b000cb · inbound

Local Stability and Gaussian Smoothing of Quantized Neural Networks cites this paper.

Local Stability and Gaussian Smoothing of Quantized Neural Networks Learned Step Size Quantization

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-01T10:41:37.432929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T10:41:37.432929Z digest=sha256:497ff3bf71a20f67c3912664661d8e928563ec7d95e3142e7331781d56e30ef6

Observation a211fb2b-3085-45b4-8bf1-583eef5a886f · inbound

Opt.Gear Technical Report cites this paper.

Opt.Gear Technical Report Learned Step Size Quantization

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T00:40:38.734813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:40:38.734813Z digest=sha256:4653daf875a47f8c08ecfc3a50c40d40ae8da9f4b07c60b3166dd63ba2af8386