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Paper Citation Record · LEDGER

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs

As of 15 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 1 inbound Pith citation observation for arXiv:2502.08807.

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

pith.paper-citation-record.v1
2502.08807 v2

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T23:42:25.300663Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:43:29.234890Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T11:43:35.816362Z

Reference resolution

46 of 46 outbound references displayed

  • verified exact2
  • verified fuzzy31
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 53832c10-45dc-476f-b045-09a7b3adc8c0 · outbound

This paper cites Unified language model pre-training for natural language understanding and generation,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Unified language model pre-training for natural language understanding and generation,

Reference 1

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no resolver link, observed 2026-08-07T23:42:25.007904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:42:25.007904Z digest=sha256:bbe182ea2874100ec4edcc041c23c1badd37b52ec3e7be2bc81125aec25fb578

Observation 4936a231-d22f-4958-a908-5afb771ec831 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 2

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no resolver link, observed 2026-08-07T23:42:25.013630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:42:25.013630Z digest=sha256:c581ae9f71e01b73983edb8890f3045bb77e23089dd8bf2a06d5d6f7981863f8

Observation d439e947-47eb-4d4f-9fbf-a7256457e426 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 3

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no resolver link, observed 2026-08-07T23:42:25.018643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:42:25.018643Z digest=sha256:bee24733e8b64aac899fc37b846162ab89ea773c76092cafb390dd97b7fa5df8

Observation d344252a-ff5d-4cb1-b390-4967cab785bd · outbound

This paper cites A review on large language models: Architectures, applications, taxonomies, open issues and challenges,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs A review on large language models: Architectures, applications, taxonomies, open issues and challenges,

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-07T23:42:26.386648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.023441Z digest=sha256:26a388a3570f3ef1d091ca7aa2c79ab196ee5e6d761e2664e43dc2a6363536d3

Observation d6a3531e-8b27-4d67-b96f-aac023854415 · outbound

This paper cites Attention is all you need,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Attention is all you need,

Reference 5

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no resolver link, observed 2026-08-07T23:42:25.029931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:42:25.029931Z digest=sha256:57e67ec9a3a924f20c9c38927988259e2b230e12946ac6902a636d7eee36e9f2

Observation 0ad047e4-893a-413c-8ea8-9e57e82a1ae4 · outbound

This paper cites Allo: A programming model for composable accelerator design,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Allo: A programming model for composable accelerator design,

Reference 6

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unresolved
no resolver link, observed 2026-08-07T23:42:25.034717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:42:25.034717Z digest=sha256:c29b87bc75c5635abb4dcee9190570e32490cf948559b8d499d932d4b12d3810

Observation c5be5f49-28fe-414d-9b0c-3eea9bd3202a · outbound

This paper cites Flexcnn: An end-to-end framework for composing cnn accelerators on fpga,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Flexcnn: An end-to-end framework for composing cnn accelerators on fpga,

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-07T23:42:26.322268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.040913Z digest=sha256:15a3d0d201f306cac94b2df11a031ab848dfb248a741ada476396d8c51f6d6c6

Observation 0205b166-9cc7-41b1-ad5b-7c889a5df0bb · outbound

This paper cites Tpu v4: An optically reconfigurable supercomputer for machine learning with hardware sup- port for embeddings,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Tpu v4: An optically reconfigurable supercomputer for machine learning with hardware sup- port for embeddings,

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-07T23:42:26.293988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.047418Z digest=sha256:dffde03f67c141f6834c30efb5329be1429f516ff09fd49afb5debad2b2f332b

Observation 4bf31d73-71d8-42e4-a908-ea55578635c2 · outbound

This paper cites Fet-opu: A flexible and efficient fpga-based overlay processor for transformer networks,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Fet-opu: A flexible and efficient fpga-based overlay processor for transformer networks,

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-07T23:42:26.260975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.052884Z digest=sha256:9f0661de875401611598e0da75cfc0a68f7e2b78934f256dcfaee4a3e8c9f04a

Observation 3de44d2a-8c84-4b41-9afe-47c06bdba333 · outbound

This paper cites Hardware acceleration of fully quantized bert for efficient natural language processing,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Hardware acceleration of fully quantized bert for efficient natural language processing,

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-07T23:42:26.239036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.060339Z digest=sha256:6cb3a57738c48bdf9421524c00417db1dc2c944ef784c030d731261f441db239

Observation 3d128b80-c527-447e-ac6b-eba0da348057 · outbound

This paper cites Dnnexplorer: a framework for modeling and exploring a novel paradigm of fpga-based dnn accelerator,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Dnnexplorer: a framework for modeling and exploring a novel paradigm of fpga-based dnn accelerator,

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-07T23:42:26.209546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.066366Z digest=sha256:d3695d2b540338df90f94e5144349a0342c49cc21e8c926fadf65221f361857f

Observation 6a40b328-d28d-445d-a2dd-613240757282 · outbound

This paper cites Understanding the potential of fpga-based spatial accel- eration for large language model inference,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Understanding the potential of fpga-based spatial accel- eration for large language model inference,

Reference 12

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unresolved
no resolver link, observed 2026-08-07T23:42:25.072072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:42:25.072072Z digest=sha256:f210276707c31fd983e82bae55e720690b78f79dc18e31e52235fd556e7540ad

Observation 3763345c-11bd-4b37-a280-b3e480e9c7e7 · outbound

This paper cites Ssr: Spatial sequential hybrid architecture for latency throughput tradeoff in transformer acceleration,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Ssr: Spatial sequential hybrid architecture for latency throughput tradeoff in transformer acceleration,

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-07T23:42:26.151949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.083019Z digest=sha256:310e80407e5a17638619681404c4b5a76f9e14713e3c9c6ed56ad3a4eff1749c

Observation 1708985e-c13e-4701-81ba-5c95d188a7b8 · outbound

This paper cites Language models are unsupervised multitask learners,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Language models are unsupervised multitask learners,

Reference 14

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unresolved
no resolver link, observed 2026-08-07T23:42:25.090118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:42:25.090118Z digest=sha256:8350372dafe88ce6b3f9c7a19f1aefd78d714d59773cc721d2cfe2649d666807

Observation 4dd33f58-5519-4ff6-9335-11905e437a9c · outbound

This paper cites Deep residual learning for image recognition,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Deep residual learning for image recognition,

Reference 15

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unresolved
no resolver link, observed 2026-08-07T23:42:25.097184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:42:25.097184Z digest=sha256:8076061e44314ff44969234aab2283669ee5441863441f6a2bafe663d13e69bb

Observation 72248158-c86b-48f8-bf5a-c4c35bda9203 · outbound

This paper cites Aggregated residual transformations for deep neural networks,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Aggregated residual transformations for deep neural networks,

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T23:42:25.107177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:42:25.107177Z digest=sha256:87134df2b8dcd0516598e8e6fbb95f3cd8c3d4295c324639eae8434caf8a8037

Observation 201709a1-09e0-46bd-8c12-ca22fa02b136 · outbound

This paper cites Inter-layer scheduling space definition and exploration for tiled accelerators,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Inter-layer scheduling space definition and exploration for tiled accelerators,

Reference 17

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verified fuzzy
raw_fallback, observed 2026-08-07T23:42:26.062970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.113362Z digest=sha256:959629f01c79ff8857840985412074e2f48442acb96046e59f6a49d2d940f475

Observation 9bdeb9fd-b944-4097-ac42-89b8a84d815a · outbound

This paper cites A fully pipelined and dynamically composable architecture of cgra,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs A fully pipelined and dynamically composable architecture of cgra,

Reference 18

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verified fuzzy
raw_fallback, observed 2026-08-07T23:42:26.044366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.121548Z digest=sha256:c33acd1245f529091c017f4d29e54cf940979406e73ff2cc8b4e44b0282d0ff6

Observation 99c067da-4756-4c21-b8ce-56b7361fd1f9 · outbound

This paper cites A multi-neural network acceleration architecture,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs A multi-neural network acceleration architecture,

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-07T23:42:26.025472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.129833Z digest=sha256:54e1611f45c3d30da0085e1fac3557488a4d3c0f2829b23854e5d6501f0ad093

Observation c11509df-73d0-4dbb-87c5-1ff99250d546 · outbound

This paper cites Overgen: Improving fpga usability through domain-specific overlay generation,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Overgen: Improving fpga usability through domain-specific overlay generation,

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-07T23:42:26.008760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.136942Z digest=sha256:693b454a1b7a8f989970d5395ff155deba4be94f0df1480792bb31de3d948f13

Observation 80a7fb2b-69cb-4299-9955-56cd0fe13943 · outbound

This paper cites Hardware Abstractions and Hardware Mechanisms to Support Multi-Task Execution on Coarse-Grained Reconfigurable Arrays.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Hardware Abstractions and Hardware Mechanisms to Support Multi-Task Execution on Coarse-Grained Reconfigurable Arrays

Reference 21

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no resolver link, observed 2026-08-07T23:42:25.142657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:42:25.142657Z digest=sha256:103043935f4709073aba52689245674335d2be21ff58f39c3a4e5a4458fb47f1

Observation 435fdf56-4f10-4e06-9437-1ecd030695d3 · outbound

This paper cites Fpga hls today: successes, challenges, and opportunities,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Fpga hls today: successes, challenges, and opportunities,

Reference 22

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verified fuzzy
raw_fallback, observed 2026-08-07T23:42:25.988116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.152196Z digest=sha256:2ea8845b5a0b363c4472492ecf65dabec2095ba479b7c28fd039a1c33443c7d4

Observation 431d877f-51cd-4332-b032-b918e0239b49 · outbound

This paper cites Dfx: A low-latency multi-fpga appliance for accelerating transformer-based text generation,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Dfx: A low-latency multi-fpga appliance for accelerating transformer-based text generation,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:42:25.967427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.160848Z digest=sha256:7500aecdf68e0d0e6a35ce0dbafb68d51ee5d57cdb0f2f6341f53f487b23d603

Observation e9c9316e-b0ab-4fc6-8815-cd5037e62bda · outbound

This paper cites GenGNN: A Generic FPGA Framework for Graph Neural Network Acceleration.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs GenGNN: A Generic FPGA Framework for Graph Neural Network Acceleration

Reference 24

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verified exact
local_arxiv, observed 2026-08-07T23:42:25.444850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.165246Z digest=sha256:1d50880e279d407a8fd41606197cfb2e1d4aabdd70a03b7c4bcf9ce6e77bd132

Observation 45916175-f94d-4e66-afb5-6ed0404537f6 · outbound

This paper cites ZynqNet: An FPGA-Accelerated Embedded Convolutional Neural Network.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs ZynqNet: An FPGA-Accelerated Embedded Convolutional Neural Network

Reference 25

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verified exact
local_arxiv, observed 2026-08-07T23:42:25.411048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.171565Z digest=sha256:c0cc2f1faba758d3e109a449296f1141620ddce9e8741d46895759a6354f8bff

Observation 9b3fb62f-6064-4af4-a5f0-eba03aa4374c · outbound

This paper cites Flightllm: Efficient large language model inference with a complete mapping flow on fpgas,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Flightllm: Efficient large language model inference with a complete mapping flow on fpgas,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:42:25.942947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.177473Z digest=sha256:360a3dbba258c4d7e6181a66931ba92b0f25bb138ba2899d4fbe0c2fec0716e8

Observation 6520112e-b067-45a5-b67d-0321a1595ebd · outbound

This paper cites A cgra-based approach for accelerating convolutional neural networks,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs A cgra-based approach for accelerating convolutional neural networks,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:42:25.912977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.182880Z digest=sha256:8f1ef882943e74a3e0f8a41d58f24869146022721d13be45777d4c2f7357b0be

Observation 85c013a3-3c42-47d8-955f-aa17b2424073 · outbound

This paper cites Impact of fpga architecture on area and performance of cgra overlays,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Impact of fpga architecture on area and performance of cgra overlays,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:42:25.892994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.189215Z digest=sha256:96fdc2402d1c83f703b1f8093c73ee54f83a3a190af4d0c06b8337bc813dd615

Observation 20272ffa-61e4-494d-a8c5-0c758c2724d7 · outbound

This paper cites Fpga dynamic and partial reconfiguration: A survey of architectures, methods, and applications,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Fpga dynamic and partial reconfiguration: A survey of architectures, methods, and applications,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:42:25.873951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.197152Z digest=sha256:554f427e22961fc04cfb70371308ec240f99cf7067837d073639628a634b8e97

Observation 7d267a23-ae44-43a9-8b02-8cf19bec8650 · outbound

This paper cites Feather: A reconfigurable accelerator with data reordering support for low-cost on-chip dataflow switching,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Feather: A reconfigurable accelerator with data reordering support for low-cost on-chip dataflow switching,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:42:25.850563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.201733Z digest=sha256:1ef1817bd8119267ef350ec93326135b6c434ac6fdbd5e7cedd889ec7a7deeb7

Observation 6650bc73-1f32-4ed9-8dc8-c23418ffce0d · outbound

This paper cites Opu: An fpga-based overlay processor for convolutional neural networks,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Opu: An fpga-based overlay processor for convolutional neural networks,

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-07T23:42:25.828892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.206124Z digest=sha256:64ac7254c749e872133f49d3ec2b9189cf5c5c6c973d128faa83176a98acbe1f

Observation 4dd9b3e7-5b9d-44b7-8dca-1f241df80db9 · outbound

This paper cites Light-opu: An fpga-based overlay processor for lightweight convolutional neural networks,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Light-opu: An fpga-based overlay processor for lightweight convolutional neural networks,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:42:25.802778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.212492Z digest=sha256:b0f43c0996008c49db07170b703c263f6d9d6490aec652603df127d3625450f6

Observation b9cafa13-e6b8-485c-aed8-75a46a948486 · outbound

This paper cites Deep Learning with Dynamic Computation Graphs.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Deep Learning with Dynamic Computation Graphs

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T23:42:25.217870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:42:25.217870Z digest=sha256:5dfe6f77b0304f1d78c0952aeb336e23dcdd2eb148d6b2f55a60bf94911b086c

Observation f642ef24-cbf8-452d-8610-ba2f079514c6 · outbound

This paper cites Alveo u280 data center accelerator card data sheet.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Alveo u280 data center accelerator card data sheet

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:42:25.780269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.223195Z digest=sha256:c3d2e1a099666e0ac146a7ce1f9ca616a19227ab3e7b280214ed637b056a6b3a

Observation c2842359-6765-4f7b-8181-d4b428b6af3d · outbound

This paper cites Amd versal hbm series product selection guide.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Amd versal hbm series product selection guide

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:42:25.755364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.227912Z digest=sha256:c3760ae76ddf20dd78a7a559847812b9a22869b5c0ba0bcbcf2dbe9f6f522e0a

Observation 331af8a5-9f7f-4d48-8e15-259fd14ebbbc · outbound

This paper cites A survey on vision transformer,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs A survey on vision transformer,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:42:25.736544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.234624Z digest=sha256:0fd0738d8e252bbe708986f21a8813a673e553c621d6c0494c25e7dc8272a781

Observation a29e5557-0233-4975-b0ce-209d971aba31 · outbound

This paper cites Graph Attention Networks.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Graph Attention Networks

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T23:42:25.239374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:42:25.239374Z digest=sha256:ed94b110f1e75e6841a18c0ff4281153cd695c8697f0199e3561f77712b48d34

Observation 38d299a5-0e13-41c4-ab1c-5064ba7fd805 · outbound

This paper cites Yolov3: An incremental improvement,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Yolov3: An incremental improvement,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:42:25.713862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.244361Z digest=sha256:4ad3d408a58d51444b583db0670f288c5885896c3e2c06bc1530291a81ac9df0

Observation 3183cde4-0489-44b6-ba29-2e3ee016acba · outbound

This paper cites Vgg convolutional neural networks practical,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Vgg convolutional neural networks practical,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:42:25.692719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.251378Z digest=sha256:f717baf7e83b17cb59c6d1182a366c67ee8237b6731dde7bfefa113e4ba2ab3e

Observation 6faf79d8-df27-4083-b0bf-d2d43c37c1cf · outbound

This paper cites Zero-vae-gan: Generating unseen features for generalized and trans- ductive zero-shot learning,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Zero-vae-gan: Generating unseen features for generalized and trans- ductive zero-shot learning,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:42:25.674303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.257321Z digest=sha256:92609718f37a7c0310bb4300166b633b206856d1a6660492eba54c8350b5fc10

Observation fc2a5d22-134c-4dec-b66d-3f3e4c4ec017 · outbound

This paper cites Rosetta: A Realistic High-Level Synthesis Benchmark Suite for Software- Programmable FPGAs,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Rosetta: A Realistic High-Level Synthesis Benchmark Suite for Software- Programmable FPGAs,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:42:25.652510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.262294Z digest=sha256:02bd37672faed1a25543b0d9a12493e21a87cc31e35955f823aecc852deb0f51

Observation ecf333e5-192c-40c9-a215-731fed065beb · outbound

This paper cites Polybench: The polyhedral benchmark suite,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Polybench: The polyhedral benchmark suite,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:42:25.623350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.267768Z digest=sha256:f07083bffc18777c5c3ed8995f8ee96a0a9e4d095f7bbe662087b3542d15c97c

Observation 7767e708-8e8a-41e7-a700-4eef366ff280 · outbound

This paper cites Tapa: a scalable task-parallel dataflow programming framework for modern fpgas with co-optimization of hls and physical design,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Tapa: a scalable task-parallel dataflow programming framework for modern fpgas with co-optimization of hls and physical design,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:42:25.590717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.276646Z digest=sha256:dd64626cb55dff57f888acdb160bfdcd1222b3083dbb6591034229f4accc1f2c

Observation c0f13032-f6b0-451c-96bd-19af638f6ed1 · outbound

This paper cites Fast inference of deep neural networks in FPGAs for particle physics,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Fast inference of deep neural networks in FPGAs for particle physics,

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T23:42:25.285100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:42:25.285100Z digest=sha256:f59fc8862f86a159edfd26a449391c8c34ce7e518c943de57ade10bc7642f79c

Observation a256145c-1d33-4a18-bf64-1ef6ebc76d8c · outbound

This paper cites Amd versal premium series product selection guide.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Amd versal premium series product selection guide

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:42:25.555475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.291093Z digest=sha256:91f78faa0c046a8bf9b1d81be1815c585f431ffed49450ae25dc5563e41eccca

Observation 67fda3b8-2ae5-4896-8321-bc7833172cc0 · outbound

This paper cites Autobridge: Coupling coarse-grained floorplanning and pipelining for high-frequency hls design on multi-die fpgas,.

InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs Autobridge: Coupling coarse-grained floorplanning and pipelining for high-frequency hls design on multi-die fpgas,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:42:25.534013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T23:42:25.300663Z digest=sha256:39c0d8a91859e6d3a1aadc057a463dea72222f4d86c3303cbda3f6ae0fa48e55

Pith citing papers

Observation 7efeefde-0d10-4482-8b15-d58aad6f22ac · inbound

Reconfigurable Stream Network Architecture cites this paper.

Reconfigurable Stream Network Architecture InTAR: Inter-Task Auto-Reconfigurable Accelerator Design for High Data Volume Variation in DNNs

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-12T11:43:35.849427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T11:43:29.234890Z digest=sha256:aacd902e25a6ff3c60678f2c48ae4915a0b4de5adae4b56d2ce82b2fbddfa571