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Paper Citation Record · LEDGER

Nearly Lossless Adaptive Bit Switching

As of 10 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2502.01199.

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

pith.paper-citation-record.v1
2502.01199 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T16:22:12.706820Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

40 of 40 outbound references displayed

  • verified exact4
  • verified fuzzy23
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1f0032aa-dce9-4527-a2e5-9fdba6990e69 · outbound

This paper cites DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients.

Nearly Lossless Adaptive Bit Switching DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients

Reference 1

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

This paper cites Learned Step Size Quantization.

Nearly Lossless Adaptive Bit Switching Learned Step Size Quantization

Reference 2

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Observation 5c1df354-2a02-4a01-8e70-9c404a184f44 · outbound

This paper cites Adabits: Neural network quantization with adaptive bit-widths,.

Nearly Lossless Adaptive Bit Switching Adabits: Neural network quantization with adaptive bit-widths,

Reference 3

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Observation a0a86594-40c4-430c-9459-2ada6ae5784c · outbound

This paper cites Multiquant: Training once for multi-bit quantization of neural networks,.

Nearly Lossless Adaptive Bit Switching Multiquant: Training once for multi-bit quantization of neural networks,

Reference 4

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source=pdf_text observed=2026-08-09T16:22:12.525698Z digest=sha256:59ceaebb6b3909446f44972ad7c2b84a7147655ce30afcc771b872c4edc287d0

Observation da52a68b-f38d-405d-aa2f-2db5c3ee6940 · outbound

This paper cites Eq-net: Elastic quantization neural networks,.

Nearly Lossless Adaptive Bit Switching Eq-net: Elastic quantization neural networks,

Reference 5

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Observation 87705d6b-da20-452c-851f-76c236ca3284 · outbound

This paper cites Any-precision deep neural networks,.

Nearly Lossless Adaptive Bit Switching Any-precision deep neural networks,

Reference 6

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source=pdf_text observed=2026-08-09T16:22:12.535909Z digest=sha256:210da547d2d084544bd9f4d7020be9be65a768acfc7a7d4382f66ae7844af56a

Observation 8f5172d3-3c3a-4c63-be8a-5151c08dbd4d · outbound

This paper cites Improved techniques for quantizing deep networks with adaptive bit-widths,.

Nearly Lossless Adaptive Bit Switching Improved techniques for quantizing deep networks with adaptive bit-widths,

Reference 8

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source=pdf_text observed=2026-08-09T16:22:12.551808Z digest=sha256:bfd4cc306602e723ecc101359c1da1205dbbc44cbc5e7af9929c555c6af39e82

Observation 3283caf0-2910-4d4a-8295-f6dbaae12976 · outbound

This paper cites Bit-mixer: Mixed-precision networks with runtime bit-width selection,.

Nearly Lossless Adaptive Bit Switching Bit-mixer: Mixed-precision networks with runtime bit-width selection,

Reference 9

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source=pdf_text observed=2026-08-09T16:22:12.556434Z digest=sha256:c3e6145466c15320dea6ad99756bbd9da7e9f5610b96d309948245262b41f442

Observation b1fb3c60-ebdc-4f02-a015-445419ee35e6 · outbound

This paper cites Arbitrary Bit-width Network: A Joint Layer-Wise Quantization and Adaptive Inference Approach.

Nearly Lossless Adaptive Bit Switching Arbitrary Bit-width Network: A Joint Layer-Wise Quantization and Adaptive Inference Approach

Reference 10

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local_arxiv, observed 2026-08-09T16:22:12.946251Z

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Observation e1458b35-d4c5-4ec8-91b4-f05e9cd461d7 · outbound

This paper cites Hawq-v2: Hessian aware trace-weighted quantization of neural networks,.

Nearly Lossless Adaptive Bit Switching Hawq-v2: Hessian aware trace-weighted quantization of neural networks,

Reference 11

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source=pdf_text observed=2026-08-09T16:22:12.566563Z digest=sha256:95e6b842da89e4e4ffe57efdda2997c49c702c259ea0197435dc23f5b5a8b64f

Observation 21894d66-524a-4b4c-8011-187dd03e06d6 · outbound

This paper cites Stochastic quantization for learning accurate low-bit deep neural networks,.

Nearly Lossless Adaptive Bit Switching Stochastic quantization for learning accurate low-bit deep neural networks,

Reference 12

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source=pdf_text observed=2026-08-09T16:22:12.571627Z digest=sha256:f7c9f5ffda91aa54571a3e2151b96a5b3815b68369ab477a28478d9cc793efb1

Observation 695581e5-a772-46c3-beb4-88c579ebe07f · outbound

This paper cites Towards Efficient Training for Neural Network Quantization.

Nearly Lossless Adaptive Bit Switching Towards Efficient Training for Neural Network Quantization

Reference 13

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local_arxiv, observed 2026-08-09T16:22:12.924092Z

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source=pdf_text observed=2026-08-09T16:22:12.576238Z digest=sha256:54fdfffb261b9b65bfac0e335da1349b6a54176c60870b38c0853a6d639b0d06

Observation f0b54e9e-c06f-4c0e-b4fe-bfaa562b2150 · outbound

This paper cites Deep Residual Learning for Image Recognition.

Nearly Lossless Adaptive Bit Switching Deep Residual Learning for Image Recognition

Reference 14

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source=pdf_text observed=2026-08-09T16:22:12.581409Z digest=sha256:69568f30a03c014c8e990c4c392c7ed928a807e487c52241708b21948d5d2c95

Observation dbe4ff4a-e7ad-4c70-b9b6-f4f59d8a957f · outbound

This paper cites Training for multi-resolution inference using reusable quantization terms,.

Nearly Lossless Adaptive Bit Switching Training for multi-resolution inference using reusable quantization terms,

Reference 15

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source=pdf_text observed=2026-08-09T16:22:12.586301Z digest=sha256:067dce37a5f5b8c14559159e79ff8c4cc729c59829ceb82a9614ffcf7cd4ec87

Observation 0f8d0dc4-7cbd-45a0-b816-6ae26302ddd2 · outbound

This paper cites Bitwave: Exploiting column-based bit-level sparsity for deep learning acceleration,.

Nearly Lossless Adaptive Bit Switching Bitwave: Exploiting column-based bit-level sparsity for deep learning acceleration,

Reference 16

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source=pdf_text observed=2026-08-09T16:22:12.590719Z digest=sha256:b791a3e529ada8dc14cace2b02675d217778ec515e18444ec66b079da71cda96

Observation 3b6d2c90-6eff-484c-a235-95e8fbf8003b · outbound

This paper cites Self-knowledge distillation with progressive refinement of targets,.

Nearly Lossless Adaptive Bit Switching Self-knowledge distillation with progressive refinement of targets,

Reference 17

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Observation 89304846-c825-4d0b-abfe-47b449871b6d · outbound

This paper cites Haq: Hardware-aware automated quantization with mixed precision,.

Nearly Lossless Adaptive Bit Switching Haq: Hardware-aware automated quantization with mixed precision,

Reference 18

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source=pdf_text observed=2026-08-09T16:22:12.600078Z digest=sha256:7063fed64a59324db8ab50e60dbacc7061c0e5306781c33335a2ab1de022242c

Observation 34052334-2fa6-4bc7-a3b4-f42dec3df60e · outbound

This paper cites Releq: an automatic reinforcement learning approach for deep quantization of neural networks,.

Nearly Lossless Adaptive Bit Switching Releq: an automatic reinforcement learning approach for deep quantization of neural networks,

Reference 19

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source=pdf_text observed=2026-08-09T16:22:12.604764Z digest=sha256:e43d3ee78da6167f9579a4ce56dff98532ae2f096d8b2567811387e829351afa

Observation 2eee8bc0-e30e-48d1-be75-057027dcf7f7 · outbound

This paper cites Mixed Precision Quantization of ConvNets via Differentiable Neural Architecture Search.

Nearly Lossless Adaptive Bit Switching Mixed Precision Quantization of ConvNets via Differentiable Neural Architecture Search

Reference 20

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Observation c87375f9-b7a5-4037-bcb4-2475a6724c01 · outbound

This paper cites Single path one-shot neural architecture search with uniform sampling,.

Nearly Lossless Adaptive Bit Switching Single path one-shot neural architecture search with uniform sampling,

Reference 21

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Observation 42deba3e-7b37-47b1-adf6-7be313d7f65a · outbound

This paper cites Once quantization-aware training: High performance extremely low-bit architecture search,.

Nearly Lossless Adaptive Bit Switching Once quantization-aware training: High performance extremely low-bit architecture search,

Reference 22

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Observation 5b3486f0-fa07-4c57-b19f-1422482e4385 · outbound

This paper cites Sharpness-aware Quantization for Deep Neural Networks.

Nearly Lossless Adaptive Bit Switching Sharpness-aware Quantization for Deep Neural Networks

Reference 23

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Observation faa9812f-5c9b-4a8e-ad96-33e0180cbcfe · outbound

This paper cites Hawq-v3: Dyadic neural network quantization,.

Nearly Lossless Adaptive Bit Switching Hawq-v3: Dyadic neural network quantization,

Reference 24

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:22:12.628515Z digest=sha256:8541ddc9ff1dfd05745eb890de2eb13e576530dcff9a6d647fc1be404a71bc1d

Observation 5dde9efc-7a30-4e1d-a561-26c2aefc2865 · outbound

This paper cites Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference.

Nearly Lossless Adaptive Bit Switching Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference

Reference 25

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source=pdf_text observed=2026-08-09T16:22:12.633935Z digest=sha256:83f39275e94cf5b25a4755190046abc109632f1d507c72b7c217e1d2ec6a311a

Observation b823d7e2-b248-4913-b997-4f7b5167cae1 · outbound

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

Nearly Lossless Adaptive Bit Switching Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 26

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Observation e3e4e44f-22c9-42e2-92a0-09bfcb79b46a · outbound

This paper cites Large Batch Training of Convolutional Networks.

Nearly Lossless Adaptive Bit Switching Large Batch Training of Convolutional Networks

Reference 27

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Unavailable: canonical work link unavailable.

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Observation d0746bca-3a82-42ae-99eb-8f28229382d7 · outbound

This paper cites Rethinking differentiable search for mixed-precision neural networks,.

Nearly Lossless Adaptive Bit Switching Rethinking differentiable search for mixed-precision neural networks,

Reference 28

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 82abc1de-f1e1-4746-9d7b-ce43b2fd101e · outbound

This paper cites Single path one-shot neural architecture search with uniform sampling,.

Nearly Lossless Adaptive Bit Switching Single path one-shot neural architecture search with uniform sampling,

Reference 29

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raw_fallback, observed 2026-08-09T16:22:13.137423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 550e7648-4422-4420-b417-55a5c62e0262 · outbound

This paper cites Hawq: Hessian aware quantization of neural networks with mixed-precision,.

Nearly Lossless Adaptive Bit Switching Hawq: Hessian aware quantization of neural networks with mixed-precision,

Reference 30

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raw_fallback, observed 2026-08-09T16:22:13.121206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:22:12.658768Z digest=sha256:807139661b2580e38ba5e43c73504bb5cf0d49f178f0d8736e656f7432d645c7

Observation 16ba8d5f-0f45-42b4-9f77-39c47002f931 · outbound

This paper cites Ompq: Orthogonal mixed precision quantization,.

Nearly Lossless Adaptive Bit Switching Ompq: Orthogonal mixed precision quantization,

Reference 31

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:22:12.663476Z digest=sha256:ea9c9793cba54e15adb2ffc592a632e381acf3253f801062f211c72e0624715d

Observation f56a6d04-024e-4a14-bfb2-4fc7bfc91eac · outbound

This paper cites A quantization-friendly separable convolution for mobilenets,.

Nearly Lossless Adaptive Bit Switching A quantization-friendly separable convolution for mobilenets,

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:22:12.668242Z digest=sha256:9a61143d28779215b57511fb81cc1db070d2f4ada3885d821afb1dd395ad0d75

Observation 979d57a2-3a7a-4dab-bfef-87236cbca9f2 · outbound

This paper cites One Model for All Quantization: A Quantized Network Supporting Hot-Swap Bit-Width Adjustment.

Nearly Lossless Adaptive Bit Switching One Model for All Quantization: A Quantized Network Supporting Hot-Swap Bit-Width Adjustment

Reference 33

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local_arxiv, observed 2026-08-09T16:22:12.805227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:22:12.673255Z digest=sha256:1a6dfd4e248705a43d7b6a3463f026d8a77556f69dc99f25095794eab20ff019

Observation 8681bba8-c624-440c-b67f-ea9e8249d4e3 · outbound

This paper cites Gradient $\ell_1$ Regularization for Quantization Robustness.

Nearly Lossless Adaptive Bit Switching Gradient $\ell_1$ Regularization for Quantization Robustness

Reference 34

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verified exact
local_arxiv, observed 2026-08-09T16:22:12.782154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:22:12.678157Z digest=sha256:a6c0b9db6cb2e155c93c3847fd9d58d19ebcbd87875330e70ef097f2f263ac98

Observation 45f59fca-7924-4308-a88a-bb000e1e9d7a · outbound

This paper cites Robust quantization: One model to rule them all,.

Nearly Lossless Adaptive Bit Switching Robust quantization: One model to rule them all,

Reference 35

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raw_fallback, observed 2026-08-09T16:22:13.072880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:22:12.683387Z digest=sha256:0dadf5f8d8ecbb96ce333c21bec430e5d03ce530df2b2840311f97fdbbb2440a

Observation 4d24ced4-11de-4a3c-93dd-d9d52a13ab52 · outbound

This paper cites Vertical layering of quantized neural networks for heteroge- neous inference,.

Nearly Lossless Adaptive Bit Switching Vertical layering of quantized neural networks for heteroge- neous inference,

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:22:12.688181Z digest=sha256:1d17fa5f727892566cac07d79df6bbaccc32117336f415d2d43a969a12b28c36

Observation 7c1263a1-d0af-4afa-bc95-8f8e09bb3854 · outbound

This paper cites Mask r-cnn,.

Nearly Lossless Adaptive Bit Switching Mask r-cnn,

Reference 37

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raw_fallback, observed 2026-08-09T16:22:13.042059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:22:12.692793Z digest=sha256:3bdd95b37a0d5b80e29ef423f72b5279b87d7fed13a8c9a75f02fff401b8492c

Observation f304c5ef-f860-4f18-b9c0-554392131185 · outbound

This paper cites Tinyllama: An open-source small language model,.

Nearly Lossless Adaptive Bit Switching Tinyllama: An open-source small language model,

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-09T16:22:12.697508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:22:12.697508Z digest=sha256:2cb0721c502e947f1d30f5402ac929528c65d2a0b88c19f002de74df2058e596

Observation c209c6c6-0d0f-48f8-b61e-7986857e37df · outbound

This paper cites Lsq+: Improving low-bit quantization through learnable offsets and better initialization,.

Nearly Lossless Adaptive Bit Switching Lsq+: Improving low-bit quantization through learnable offsets and better initialization,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:22:13.016840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:22:12.702212Z digest=sha256:5a860377eaf978d80f675e0da0157663e4087e38d5ef84c7f4eda431bb6e386a

Observation f769e984-07e0-4fb4-b682-2b9e24b60884 · outbound

This paper cites Slimmable Neural Networks.

Nearly Lossless Adaptive Bit Switching Slimmable Neural Networks

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-09T16:22:12.706820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:22:12.706820Z digest=sha256:69e349aec0262d199b52bb5c09c2f2fe9e3ec766ec03cfda64964776439ba5c4

Observation 2455f888-cdb2-4f5d-be41-50808495b064 · outbound

This paper cites From Quantized DNNs to Quantizable DNNs.

Nearly Lossless Adaptive Bit Switching From Quantized DNNs to Quantizable DNNs

Reference 2020

Resolution
metadata mismatch
local_arxiv, observed 2026-08-09T16:22:12.968721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:22:12.546902Z digest=sha256:b4edaf04b404f091fe7d5759ff0e8770000628a1828231208078f0ab705acc0d

Pith citing papers

No inbound Pith citation observations are available.