Image Captioning with Sparse Recurrent Neural Network | Paper Citation Record

Observation 97b080c0-a41e-4970-bdd2-3add89b7f55f · outbound

This paper cites To prune, or not to prune: exploring the efﬁcacy of pruning for model compression,.

Image Captioning with Sparse Recurrent Neural Network To prune, or not to prune: exploring the efﬁcacy of pruning for model compression,

Reference 1

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Observation aba7a75c-f54b-49ee-8bb5-1252ca8dc63a · outbound

This paper cites Exploring sparsity in recurrent neural networks,.

Image Captioning with Sparse Recurrent Neural Network Exploring sparsity in recurrent neural networks,

Reference 2

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Observation 0e987c19-1f1e-48ef-85c1-cdc17583756a · outbound

This paper cites Deep compression: Compressing deep neural networks with pruning, trained quantization and Huffman coding,.

Image Captioning with Sparse Recurrent Neural Network Deep compression: Compressing deep neural networks with pruning, trained quantization and Huffman coding,

Reference 3

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Observation 02fba9ba-db99-4902-a739-5958481d927d · outbound

This paper cites Learning both weights and connections for efﬁcient neural network,.

Image Captioning with Sparse Recurrent Neural Network Learning both weights and connections for efﬁcient neural network,

Reference 4

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This paper cites Persistent RNNs: Stashing recurrent weights on-chip,.

Image Captioning with Sparse Recurrent Neural Network Persistent RNNs: Stashing recurrent weights on-chip,

Reference 5

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Observation fe5e0fd1-0f51-4c99-9d6d-eb255e8c8531 · outbound

This paper cites Convex neural networks,.

Image Captioning with Sparse Recurrent Neural Network Convex neural networks,

Reference 6

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Observation 0904977a-4ab8-4347-baef-3b215f8312f0 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Image Captioning with Sparse Recurrent Neural Network Distilling the Knowledge in a Neural Network

Reference 7

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Observation 3ea78df8-b161-48d9-a025-9f751e4c31e2 · outbound

This paper cites Understanding deep learning requires rethinking generalization.

Image Captioning with Sparse Recurrent Neural Network Understanding deep learning requires rethinking generalization

Reference 8

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Observation 9d3469ad-f7c5-4f2e-bdc1-a11843a49907 · outbound

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

Image Captioning with Sparse Recurrent Neural Network BinaryConnect: Training deep neural networks with binary weights during propagations,

Reference 9

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Observation 1ba5a382-ea9b-4db2-ae1c-2eac2b5618f2 · outbound

This paper cites Quantized neural networks: Training neural networks with low precision weights and activations,.

Image Captioning with Sparse Recurrent Neural Network Quantized neural networks: Training neural networks with low precision weights and activations,

Reference 10

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Observation 49d6f1a1-cd66-47fc-b0f8-d7b056596054 · outbound

This paper cites XNOR-Net: ImageNet classiﬁcation using binary convolutional neural networks,.

Image Captioning with Sparse Recurrent Neural Network XNOR-Net: ImageNet classiﬁcation using binary convolutional neural networks,

Reference 11

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Observation e1a22653-5bb2-4c7d-83f7-db86f53a0067 · outbound

This paper cites Optimal brain damage,.

Image Captioning with Sparse Recurrent Neural Network Optimal brain damage,

Reference 12

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Observation 62138e0a-22ef-4480-81db-da04b3403633 · outbound

This paper cites Optimal brain surgeon and general network pruning,.

Image Captioning with Sparse Recurrent Neural Network Optimal brain surgeon and general network pruning,

Reference 13

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Observation 95d91ce3-a2b6-44d5-adb1-f2e2c9879f1a · outbound

This paper cites Skeletonization: A technique for trimming the fat from a network via relevance assessment,.

Image Captioning with Sparse Recurrent Neural Network Skeletonization: A technique for trimming the fat from a network via relevance assessment,

Reference 14

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Observation 6eb28f72-7125-400d-b440-b6180ba54a2b · outbound

This paper cites A simple procedure for pruning back-propagation trained neural networks,.

Image Captioning with Sparse Recurrent Neural Network A simple procedure for pruning back-propagation trained neural networks,

Reference 15

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Observation 7ab500e0-4e7b-44b8-bbf4-978dce1e7ce9 · outbound

This paper cites A back-propagation algorithm with optimal use of hidden units,.

Image Captioning with Sparse Recurrent Neural Network A back-propagation algorithm with optimal use of hidden units,

Reference 16

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Observation 35f1a46c-44b1-4690-8d7b-ff3f52f88920 · outbound

This paper cites Structural learning with forgetting,.

Image Captioning with Sparse Recurrent Neural Network Structural learning with forgetting,

Reference 17

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Observation 514e3a6c-c0e4-4b16-ba4f-a8eb9640b83c · outbound

This paper cites Dynamic network surgery for efﬁcient DNNs,.

Image Captioning with Sparse Recurrent Neural Network Dynamic network surgery for efﬁcient DNNs,

Reference 18

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Observation 3717d38d-220e-461f-86dd-18c82bbd7198 · outbound

This paper cites Variational dropout and the local reparameteri- zation trick,.

Image Captioning with Sparse Recurrent Neural Network Variational dropout and the local reparameteri- zation trick,

Reference 19

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Observation 277661a5-a085-46c4-b003-41bcc06c47f3 · outbound

This paper cites Variational dropout sparsiﬁes deep neural networks,.

Image Captioning with Sparse Recurrent Neural Network Variational dropout sparsiﬁes deep neural networks,

Reference 20

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Observation ed8c637d-3aa6-479c-9f2c-ff67ea3e7ffa · outbound

This paper cites Compressing neural networks using the variational information bottleneck,.

Image Captioning with Sparse Recurrent Neural Network Compressing neural networks using the variational information bottleneck,

Reference 21

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Observation b89256f2-73a3-490e-91f1-91ed4574f954 · outbound

This paper cites Pruning ﬁlters for efﬁcient ConvNets,.

Image Captioning with Sparse Recurrent Neural Network Pruning ﬁlters for efﬁcient ConvNets,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.703009Z

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Observation d8adeba4-6aab-4ef7-bc88-1559b4f5098a · outbound

This paper cites ThiNet: A ﬁlter level pruning method for deep neural network compression,.

Image Captioning with Sparse Recurrent Neural Network ThiNet: A ﬁlter level pruning method for deep neural network compression,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.689445Z

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Observation d4991d00-a74d-47a9-846a-b5c8c0a0f363 · outbound

This paper cites NISP: Pruning networks using neuron importance score propagation,.

Image Captioning with Sparse Recurrent Neural Network NISP: Pruning networks using neuron importance score propagation,

Reference 24

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Observation 0932787f-9595-432c-909a-dbf5d8e8f0d9 · outbound

This paper cites Compression of neural machine translation models via pruning,.

Image Captioning with Sparse Recurrent Neural Network Compression of neural machine translation models via pruning,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.661568Z

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Observation 50552a72-6395-472c-96e7-b11efe1f8c31 · outbound

This paper cites SNIP: Single-shot network pruning based on connec- tion sensitivity,.

Image Captioning with Sparse Recurrent Neural Network SNIP: Single-shot network pruning based on connec- tion sensitivity,

Reference 26

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Observation 48f76fb7-c090-486e-90c3-56350e5affb0 · outbound

This paper cites Long short-term memory,.

Image Captioning with Sparse Recurrent Neural Network Long short-term memory,

Reference 27

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Observation 9607325b-2515-4398-b3ed-6a7d9d3ce932 · outbound

This paper cites AMC: AutoML for model compres- sion and acceleration on mobile devices,.

Image Captioning with Sparse Recurrent Neural Network AMC: AutoML for model compres- sion and acceleration on mobile devices,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.618417Z

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Observation f4cc7d56-1b54-447b-ab46-025791d373d3 · outbound

This paper cites The lottery ticket hypothesis: Finding sparse, trainable neural networks,.

Image Captioning with Sparse Recurrent Neural Network The lottery ticket hypothesis: Finding sparse, trainable neural networks,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.604449Z

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Observation a2f97539-513a-4273-ab9b-153b6e3297b5 · outbound

This paper cites Grow and Prune Compact, Fast, and Accurate LSTMs.

Image Captioning with Sparse Recurrent Neural Network Grow and Prune Compact, Fast, and Accurate LSTMs

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:39:57.070509Z

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Observation 40680bfc-0571-4b97-ad75-60f9bd92bb16 · outbound

This paper cites NeST: A neural network synthesis tool based on a grow-and- prune paradigm,.

Image Captioning with Sparse Recurrent Neural Network NeST: A neural network synthesis tool based on a grow-and- prune paradigm,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.592133Z

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Observation ee2c2e3d-b517-45c8-87e7-d28befc27e03 · outbound

This paper cites Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP.

Image Captioning with Sparse Recurrent Neural Network Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP

Reference 32

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Observation f8cd9b37-8301-4472-896d-80ff49469b8a · outbound

This paper cites Training sparse neural networks,.

Image Captioning with Sparse Recurrent Neural Network Training sparse neural networks,

Reference 33

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Observation 20059712-42db-4d02-b3fb-174709033485 · outbound

This paper cites Learning sparse neural networks throughl_0 regularization,.

Image Captioning with Sparse Recurrent Neural Network Learning sparse neural networks throughl_0 regularization,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.567480Z

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Observation 04d6b156-71a7-47e5-bd05-1a363660d243 · outbound

This paper cites Learning compact recurrent neural networks,.

Image Captioning with Sparse Recurrent Neural Network Learning compact recurrent neural networks,

Reference 35

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Observation b9aba393-f643-4006-b08e-b9bace845ee3 · outbound

This paper cites FastGRNN: A fast, accurate, stable and tiny kilobyte sized gated recurrent neural network,.

Image Captioning with Sparse Recurrent Neural Network FastGRNN: A fast, accurate, stable and tiny kilobyte sized gated recurrent neural network,

Reference 36

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Observation ae73fc9e-ce1d-42ca-88e7-482970c19355 · outbound

This paper cites Structured word embedding for low memory neural network language model,.

Image Captioning with Sparse Recurrent Neural Network Structured word embedding for low memory neural network language model,

Reference 37

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Observation 2961e34e-b53a-4bca-9e6e-9c7a08a80b17 · outbound

This paper cites LightRNN: Memory and computation-efﬁcient recurrent neural networks,.

Image Captioning with Sparse Recurrent Neural Network LightRNN: Memory and computation-efﬁcient recurrent neural networks,

Reference 38

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Observation abbcc520-f779-4864-b17c-228d6f266ace · outbound

This paper cites Exploring memory and time efﬁcient neural networks for image captioning,.

Image Captioning with Sparse Recurrent Neural Network Exploring memory and time efﬁcient neural networks for image captioning,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.492548Z

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Observation 0dfe355b-3b6a-4e3c-817e-df32a93d5409 · outbound

This paper cites COMIC: Towards a compact image captioning model with attention,.

Image Captioning with Sparse Recurrent Neural Network COMIC: Towards a compact image captioning model with attention,

Reference 40

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Observation 6cef55c4-830d-407a-8619-3ed6a154067f · outbound

This paper cites Efﬁcient sequence learning with group recurrent networks,.

Image Captioning with Sparse Recurrent Neural Network Efﬁcient sequence learning with group recurrent networks,

Reference 41

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Observation 2eb70257-ab70-4bbf-8227-9b6af0e60edb · outbound

This paper cites Show, attend and tell: Neural image caption generation with visual attention,.

Image Captioning with Sparse Recurrent Neural Network Show, attend and tell: Neural image caption generation with visual attention,

Reference 42

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Observation f04745c0-f408-4269-951f-b1bc3b5fc72e · outbound

This paper cites Aligning Where to See and What to Tell: Image Captioning with Region-based Attention and Scene-speciﬁc Contexts,.

Image Captioning with Sparse Recurrent Neural Network Aligning Where to See and What to Tell: Image Captioning with Region-based Attention and Scene-speciﬁc Contexts,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.427833Z

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Observation 5dc55f5a-03ea-48fb-a215-108af7deee0a · outbound

This paper cites Bottom-up and top-down attention for image captioning and visual question answering,.

Image Captioning with Sparse Recurrent Neural Network Bottom-up and top-down attention for image captioning and visual question answering,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.412967Z

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Observation 17ba2ec9-0bbe-4be5-b79f-ddd5c0bb0872 · outbound

This paper cites Learn- ing phrase representations using RNN encoder-decoder for statistical machine translation,.

Image Captioning with Sparse Recurrent Neural Network Learn- ing phrase representations using RNN encoder-decoder for statistical machine translation,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.395998Z

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Observation fe35632a-e847-4009-be2d-2ed020733305 · outbound

This paper cites Neural machine translation by jointly learning to align and translate,.

Image Captioning with Sparse Recurrent Neural Network Neural machine translation by jointly learning to align and translate,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.377013Z

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Observation 3762fcf3-e980-4d3c-99f9-b14d53fe71ba · outbound

This paper cites Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask.

Image Captioning with Sparse Recurrent Neural Network Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask

Reference 47

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Observation 613c93fe-1c4e-4d49-b2db-604e793eff9e · outbound

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

Image Captioning with Sparse Recurrent Neural Network Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:56.890438Z

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Observation 8dee18ae-ae4f-4ef2-ae15-4b10707a3e39 · outbound

This paper cites Understanding the difﬁculty of training deep feedforward neural networks,.

Image Captioning with Sparse Recurrent Neural Network Understanding the difﬁculty of training deep feedforward neural networks,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.361320Z

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Observation 1bbb03f6-55e3-4d24-8c6b-fd54766293bb · outbound

This paper cites Going deeper with convolutions,.

Image Captioning with Sparse Recurrent Neural Network Going deeper with convolutions,

Reference 50

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Observation 65a73708-f5a4-4a83-8bec-b71bcf243e6a · outbound

This paper cites Batch normalization: Accelerating deep network training by reducing internal covariate shift,.

Image Captioning with Sparse Recurrent Neural Network Batch normalization: Accelerating deep network training by reducing internal covariate shift,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.329615Z

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Observation 3102677b-1622-4ef1-88f4-354bbea64a5b · outbound

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

Image Captioning with Sparse Recurrent Neural Network ImageNet: A large-scale hierarchical image database,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.315863Z

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Observation f13f2062-723f-4d5b-8330-1753af27cbbe · outbound

This paper cites Adam: A method for stochastic optimization,.

Image Captioning with Sparse Recurrent Neural Network Adam: A method for stochastic optimization,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.301481Z

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Observation 1d692f07-93d6-4efe-a357-cbf408afd650 · outbound

This paper cites Microsoft COCO: Common objects in context,.

Image Captioning with Sparse Recurrent Neural Network Microsoft COCO: Common objects in context,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.284950Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7c746da4-f1bf-4c9f-b07e-0ddc213f64f4 · outbound

This paper cites Deep visual-semantic alignments for generating image descrip- tions,.

Image Captioning with Sparse Recurrent Neural Network Deep visual-semantic alignments for generating image descrip- tions,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.249106Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 06af12a3-72b3-4783-b168-9f8840f026dd · outbound

This paper cites BLEU: a method for automatic evaluation of machine translation,.

Image Captioning with Sparse Recurrent Neural Network BLEU: a method for automatic evaluation of machine translation,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.227137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ed20b865-c7cf-46c1-8334-7163afa125eb · outbound

This paper cites METEOR: An automatic metric for MT evaluation with im- proved correlation with human judgments,.

Image Captioning with Sparse Recurrent Neural Network METEOR: An automatic metric for MT evaluation with im- proved correlation with human judgments,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.204870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ac8517aa-d00e-4f3e-bf76-94e14322bac2 · outbound

This paper cites ROUGE: A package for automatic evaluation of summaries,.

Image Captioning with Sparse Recurrent Neural Network ROUGE: A package for automatic evaluation of summaries,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.187479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2220adc6-2380-42b4-9873-4676215a8b4b · outbound

This paper cites CIDEr: Consensus-based image description evaluation,.

Image Captioning with Sparse Recurrent Neural Network CIDEr: Consensus-based image description evaluation,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.171046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 82804285-9085-4b05-8aca-875c7283067c · outbound

This paper cites SPICE: Semantic propositional image caption evaluation,.

Image Captioning with Sparse Recurrent Neural Network SPICE: Semantic propositional image caption evaluation,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.151676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4d3050c2-35b8-40d3-92d0-c40d94579d6d · outbound

This paper cites Attention is all you need,.

Image Captioning with Sparse Recurrent Neural Network Attention is all you need,

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:56.946556Z

Source-reported events for the cited work

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Observation 21b642ee-ca29-4738-8746-5456f15abc5e · outbound

This paper cites Compressing word embeddings via deep compositional code learning,.

Image Captioning with Sparse Recurrent Neural Network Compressing word embeddings via deep compositional code learning,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:57.116586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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