High-Fidelity Differential-information Driven Binary Vision Transformer | Paper Citation Record

Observation 726d54b2-c4b6-4421-b4cc-ab520cb3bc30 · outbound

This paper cites Improving vision transformers by revisit- ing high-frequency components.

High-Fidelity Differential-information Driven Binary Vision Transformer Improving vision transformers by revisit- ing high-frequency components

Reference 1

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This paper cites Binarized spectral compressive imaging.

High-Fidelity Differential-information Driven Binary Vision Transformer Binarized spectral compressive imaging

Reference 2

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This paper cites ” bnn-bn=?”: Train- ing binary neural networks without batch normalization.

High-Fidelity Differential-information Driven Binary Vision Transformer ” bnn-bn=?”: Train- ing binary neural networks without batch normalization

Reference 3

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This paper cites Binaryconnect: Training deep neural networks with binary weights during propagations.

High-Fidelity Differential-information Driven Binary Vision Transformer Binaryconnect: Training deep neural networks with binary weights during propagations

Reference 4

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This paper cites Imagenet: A large-scale hierarchical image database.

High-Fidelity Differential-information Driven Binary Vision Transformer Imagenet: A large-scale hierarchical image database

Reference 5

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This paper cites Network pruning via performance maximization.

High-Fidelity Differential-information Driven Binary Vision Transformer Network pruning via performance maximization

Reference 6

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This paper cites Gsb: Group superposition binarization for vision transformer with limited training samples.

High-Fidelity Differential-information Driven Binary Vision Transformer Gsb: Group superposition binarization for vision transformer with limited training samples

Reference 7

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This paper cites Towards optimization-friendly binary neu- ral network.

High-Fidelity Differential-information Driven Binary Vision Transformer Towards optimization-friendly binary neu- ral network

Reference 8

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Observation bc46e4f6-d928-4b7e-a4ea-506e1453ba79 · outbound

This paper cites Deep residual learning for image recognition.

High-Fidelity Differential-information Driven Binary Vision Transformer Deep residual learning for image recognition

Reference 9

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This paper cites Bivit: Extremely com- pressed binary vision transformers.

High-Fidelity Differential-information Driven Binary Vision Transformer Bivit: Extremely com- pressed binary vision transformers

Reference 10

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Observation 1ec5eb84-b19d-4a4b-aa8f-0beb47f4fe6d · outbound

This paper cites Bolt, 2020.

High-Fidelity Differential-information Driven Binary Vision Transformer Bolt, 2020

Reference 11

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This paper cites Binarized neural networks.

High-Fidelity Differential-information Driven Binary Vision Transformer Binarized neural networks

Reference 12

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Observation f2ba08b0-bfaa-40e6-853e-ac98419fe80b · outbound

This paper cites Learning multiple layers of features from tiny images.

High-Fidelity Differential-information Driven Binary Vision Transformer Learning multiple layers of features from tiny images

Reference 13

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This paper cites Binaryvit: Pushing binary vision transformers towards convolutional models.

High-Fidelity Differential-information Driven Binary Vision Transformer Binaryvit: Pushing binary vision transformers towards convolutional models

Reference 14

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This paper cites Bfd: Binarized frequency-enhanced distillation for vision transformer.

High-Fidelity Differential-information Driven Binary Vision Transformer Bfd: Binarized frequency-enhanced distillation for vision transformer

Reference 15

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This paper cites Exploring plain vision transformer backbones for object de- tection.

High-Fidelity Differential-information Driven Binary Vision Transformer Exploring plain vision transformer backbones for object de- tection

Reference 16

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Observation d38f9dec-e34c-4f72-876d-4216ceb3803a · outbound

This paper cites Bi-vit: Pushing the limit of vision transformer quantization.

High-Fidelity Differential-information Driven Binary Vision Transformer Bi-vit: Pushing the limit of vision transformer quantization

Reference 17

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This paper cites Q-vit: Accurate and fully quantized low-bit vision transformer.

High-Fidelity Differential-information Driven Binary Vision Transformer Q-vit: Accurate and fully quantized low-bit vision transformer

Reference 18

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This paper cites Siman: Sign-to- magnitude network binarization.

High-Fidelity Differential-information Driven Binary Vision Transformer Siman: Sign-to- magnitude network binarization

Reference 19

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This paper cites Ro- tated binary neural network.

High-Fidelity Differential-information Driven Binary Vision Transformer Ro- tated binary neural network

Reference 20

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Observation 4ff3891e-74d0-455b-af7e-9b4ca54da739 · outbound

This paper cites Towards accurate binary convolutional neural network.

High-Fidelity Differential-information Driven Binary Vision Transformer Towards accurate binary convolutional neural network

Reference 21

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This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

High-Fidelity Differential-information Driven Binary Vision Transformer Swin transformer: Hierarchical vision transformer using shifted windows

Reference 22

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This paper cites Bit: Robustly binarized multi-distilled trans- former.

High-Fidelity Differential-information Driven Binary Vision Transformer Bit: Robustly binarized multi-distilled trans- former

Reference 23

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This paper cites Reactnet: Towards precise binary neural net- work with generalized activation functions.

High-Fidelity Differential-information Driven Binary Vision Transformer Reactnet: Towards precise binary neural net- work with generalized activation functions

Reference 24

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This paper cites Bi-real net: Enhancing the perfor- mance of 1-bit cnns with improved representational capabil- ity and advanced training algorithm.

High-Fidelity Differential-information Driven Binary Vision Transformer Bi-real net: Enhancing the perfor- mance of 1-bit cnns with improved representational capabil- ity and advanced training algorithm

Reference 25

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Observation 7867f681-6654-4a4b-93e7-a65d3ed913cf · outbound

This paper cites Image matching from handcrafted to deep fea- tures: A survey.

High-Fidelity Differential-information Driven Binary Vision Transformer Image matching from handcrafted to deep fea- tures: A survey

Reference 26

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This paper cites Low rank approximation: algorithms, im- plementation, applications, volume 906.

High-Fidelity Differential-information Driven Binary Vision Transformer Low rank approximation: algorithms, im- plementation, applications, volume 906

Reference 27

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This paper cites Rectified linear units im- prove restricted boltzmann machines.

High-Fidelity Differential-information Driven Binary Vision Transformer Rectified linear units im- prove restricted boltzmann machines

Reference 28

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This paper cites Bibert: Accurate fully binarized bert.

High-Fidelity Differential-information Driven Binary Vision Transformer Bibert: Accurate fully binarized bert

Reference 29

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This paper cites Binary neural networks: A survey.

High-Fidelity Differential-information Driven Binary Vision Transformer Binary neural networks: A survey

Reference 30

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This paper cites Forward and backward information retention for accurate binary neural networks.

High-Fidelity Differential-information Driven Binary Vision Transformer Forward and backward information retention for accurate binary neural networks

Reference 31

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This paper cites BiBench: Benchmarking and Analyzing Network Binarization.

High-Fidelity Differential-information Driven Binary Vision Transformer BiBench: Benchmarking and Analyzing Network Binarization

Reference 32

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This paper cites Xnor-net: Imagenet classification using bi- nary convolutional neural networks.

High-Fidelity Differential-information Driven Binary Vision Transformer Xnor-net: Imagenet classification using bi- nary convolutional neural networks

Reference 33

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This paper cites U-net: Convolutional networks for biomedical image segmentation.

High-Fidelity Differential-information Driven Binary Vision Transformer U-net: Convolutional networks for biomedical image segmentation

Reference 34

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This paper cites An attentive inductive bias for sequential recom- mendation beyond the self-attention.

High-Fidelity Differential-information Driven Binary Vision Transformer An attentive inductive bias for sequential recom- mendation beyond the self-attention

Reference 35

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This paper cites Segmenter: Transformer for semantic segmenta- tion.

High-Fidelity Differential-information Driven Binary Vision Transformer Segmenter: Transformer for semantic segmenta- tion

Reference 36

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This paper cites Training data-efficient image transformers & distillation through at- tention.

High-Fidelity Differential-information Driven Binary Vision Transformer Training data-efficient image transformers & distillation through at- tention

Reference 37

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This paper cites Adabin: Improving binary neural networks with adaptive bi- nary sets.

High-Fidelity Differential-information Driven Binary Vision Transformer Adabin: Improving binary neural networks with adaptive bi- nary sets

Reference 38

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This paper cites Pyramid vision transformer: A versatile backbone for dense prediction without convolutions.

High-Fidelity Differential-information Driven Binary Vision Transformer Pyramid vision transformer: A versatile backbone for dense prediction without convolutions

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:42:22.892198Z

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This paper cites Bvt-ima: Binary vision transformer with information-modified attention.

High-Fidelity Differential-information Driven Binary Vision Transformer Bvt-ima: Binary vision transformer with information-modified attention

Reference 40

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Observation 3b7f3204-a6a0-46a6-ad14-3cfa58513fed · outbound

This paper cites Tiny imagenet challenge.

High-Fidelity Differential-information Driven Binary Vision Transformer Tiny imagenet challenge

Reference 41

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Observation 70386e91-0a7b-4b3f-be9a-5746d3435b8d · outbound

This paper cites Resilient binary neural network.

High-Fidelity Differential-information Driven Binary Vision Transformer Resilient binary neural network

Reference 42

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Observation 4499861d-e548-44cb-80d7-b3943aa4cc74 · outbound

This paper cites Recurrent bilinear optimization for binary neural networks.

High-Fidelity Differential-information Driven Binary Vision Transformer Recurrent bilinear optimization for binary neural networks

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:42:22.410279Z

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This paper cites Learning frequency domain approxima- tion for binary neural networks.

High-Fidelity Differential-information Driven Binary Vision Transformer Learning frequency domain approxima- tion for binary neural networks

Reference 44

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This paper cites Lavt: Language-aware vision transformer for referring image segmentation.

High-Fidelity Differential-information Driven Binary Vision Transformer Lavt: Language-aware vision transformer for referring image segmentation

Reference 45

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This paper cites Pathfinder for Low-altitude Aircraft with Binary Neural Network.

High-Fidelity Differential-information Driven Binary Vision Transformer Pathfinder for Low-altitude Aircraft with Binary Neural Network

Reference 46

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This paper cites Si-bivit: Binarizing vision transformers with spatial interaction.

High-Fidelity Differential-information Driven Binary Vision Transformer Si-bivit: Binarizing vision transformers with spatial interaction

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:42:22.071113Z

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Observation 5cbb5e43-68c8-4ccb-8fa2-1747dbc4674c · outbound

This paper cites BiDense: Binarization for Dense Prediction.

High-Fidelity Differential-information Driven Binary Vision Transformer BiDense: Binarization for Dense Prediction

Reference 48

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This paper cites Pokebnn: A binary pursuit of lightweight accuracy.

High-Fidelity Differential-information Driven Binary Vision Transformer Pokebnn: A binary pursuit of lightweight accuracy

Reference 49

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Observation febed67d-d43e-43e0-8431-bf26e844c7eb · outbound

This paper cites Vit-yolo: Transformer-based yolo for object detection.

High-Fidelity Differential-information Driven Binary Vision Transformer Vit-yolo: Transformer-based yolo for object detection

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:42:21.751705Z

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Observation 77bb2bdf-7404-439a-a0a4-70f26f627eb6 · outbound

This paper cites Semantic under- standing of scenes through the ade20k dataset.

High-Fidelity Differential-information Driven Binary Vision Transformer Semantic under- standing of scenes through the ade20k dataset

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:42:21.560590Z

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Observation bc8d4c8e-7cf1-43b4-918a-fdde0868cee3 · outbound

This paper cites Towards effective low-bitwidth convolutional neural networks.

High-Fidelity Differential-information Driven Binary Vision Transformer Towards effective low-bitwidth convolutional neural networks

Reference 52

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Observation 271b5a97-5dd8-4964-a7d2-5de3b28bc923 · outbound

This paper cites Let the element of O be Ok,l and the element of X be Xm,n, we have ∂Ok,l ∂Xm,n = ∂V + ∂Q + ∂K.

High-Fidelity Differential-information Driven Binary Vision Transformer Let the element of O be Ok,l and the element of X be Xm,n, we have ∂Ok,l ∂Xm,n = ∂V + ∂Q + ∂K

Reference 55

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T20:42:21.245033Z

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.

Observation 40d5365c-3e92-4986-9fc5-42d4e77abfbc · outbound

This paper cites 1, we take an input vector X ∈ R2×2 as an example.

High-Fidelity Differential-information Driven Binary Vision Transformer 1, we take an input vector X ∈ R2×2 as an example

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:42:21.049175Z

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.

Observation d133b0a7-9496-4eef-865d-6e349e9168a1 · outbound

This paper cites Let A ∈ Rm×n be the original matrix.

High-Fidelity Differential-information Driven Binary Vision Transformer Let A ∈ Rm×n be the original matrix

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:42:20.826279Z

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.

Observation e1d64084-3fe1-449b-a6ff-2755f8478255 · outbound

This paper cites In this situation, the learnable parameter becomes a scalar p ∈ R1×1.

High-Fidelity Differential-information Driven Binary Vision Transformer In this situation, the learnable parameter becomes a scalar p ∈ R1×1

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:42:20.657115Z

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.

Observation c0d6e23d-1d4f-41dd-8904-442a11a3319c · outbound

This paper cites an unresolved cited work.

High-Fidelity Differential-information Driven Binary Vision Transformer Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-08-06T20:42:20.440626Z

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.

Observation 96742770-73e9-4d2d-90d9-8587a00e613a · outbound

This paper cites Then, we utilize the BOLT toolbox [11] to implement each method to the edge device based on an ARM Cortex-A76 CPU (without CUDA).

High-Fidelity Differential-information Driven Binary Vision Transformer Then, we utilize the BOLT toolbox [11] to implement each method to the edge device based on an ARM Cortex-A76 CPU (without CUDA)

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:42:20.218796Z

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.

Observation e1fbea9c-67ef-42c0-b885-0320a6e22a14 · outbound

This paper cites 1, 2, 5, 6, 7, 8.

High-Fidelity Differential-information Driven Binary Vision Transformer 1, 2, 5, 6, 7, 8

Reference 159

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:42:24.748171Z

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.

Observation 5f565091-2b05-41c2-b4c0-d983a27c5cc8 · outbound

This paper cites an unresolved cited work.

High-Fidelity Differential-information Driven Binary Vision Transformer Unresolved cited work

Reference 2018

Resolution: unresolved; raw_fallback, observed 2026-08-06T20:42:21.434724Z

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.

Coverage vector

Reference resolution

Outbound references

Pith citing papers