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Paper Citation Record · LEDGER

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators

As of 10 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2606.06515.

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

pith.paper-citation-record.v1
2606.06515 v1

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measured 38 of 38 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-06-28T08:13:04.763453Z

measured 38 of 38 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

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38 of 38 outbound references displayed

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Outbound references

Observation 1a2a3a25-7c93-4b90-af55-dec6d08dadfd · outbound

This paper cites Attention is all you need,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Attention is all you need,

Reference 1

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Observation 32573b23-a8a7-43a4-a5a2-7f24494635c6 · outbound

This paper cites An image is worth 16x16 words: Trans- formers for image recognition at scale,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators An image is worth 16x16 words: Trans- formers for image recognition at scale,

Reference 2

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Observation 87821082-d858-46ef-86f8-c84f6c29461e · outbound

This paper cites Training data-efficient image transformers & distillation through attention,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Training data-efficient image transformers & distillation through attention,

Reference 3

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Observation 513cc1ee-c52d-42f7-bb50-8724e5cc24cd · outbound

This paper cites Transformers in vision: A survey,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Transformers in vision: A survey,

Reference 4

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Observation a3212430-81d8-4bf3-84e2-0755f426c8d1 · outbound

This paper cites A survey on vision transformer,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators A survey on vision transformer,

Reference 5

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Observation c88f74c1-cf69-4b31-a051-73008048d8c5 · outbound

This paper cites Large language models for artificial general intelligence (AGI): A survey of foundational principles and approaches.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Large language models for artificial general intelligence (AGI): A survey of foundational principles and approaches

Reference 6

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Observation 96d8cece-afe7-4413-9bd5-a01c21b07c11 · outbound

This paper cites Artificial general intelligence: Advancements, challenges, and future directions in agi research,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Artificial general intelligence: Advancements, challenges, and future directions in agi research,

Reference 7

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Observation d88e355f-1ebe-4d13-abd6-ded6d96c8f50 · outbound

This paper cites Hardware accelerator for multi-head attention and position-wise feed-forward in the trans- former,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Hardware accelerator for multi-head attention and position-wise feed-forward in the trans- former,

Reference 8

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Observation 88408ed7-7dea-46db-bdb3-00138508b21a · outbound

This paper cites Accelerating framework of transformer by hardware design and model compression co-optimization,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Accelerating framework of transformer by hardware design and model compression co-optimization,

Reference 9

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Observation 11add31d-a6e7-4287-b060-79976c9312d7 · outbound

This paper cites Spatten: Efficient sparse attention architecture with cascade token and head pruning,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Spatten: Efficient sparse attention architecture with cascade token and head pruning,

Reference 10

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Observation 58fbd959-b616-4eb4-a057-ae90a7d619d9 · outbound

This paper cites VAQF: Fully Automatic Software-Hardware Co-Design Framework for Low-Bit Vision Transformer.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators VAQF: Fully Automatic Software-Hardware Co-Design Framework for Low-Bit Vision Transformer

Reference 11

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Observation 26dae875-ec2c-46ca-8d1c-40c4bfe2103c · outbound

This paper cites Transpim: A memory- based acceleration via software-hardware co-design for transformer,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Transpim: A memory- based acceleration via software-hardware co-design for transformer,

Reference 12

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Observation ffa4eb57-82e1-4561-83b7-af93a0bf47fd · outbound

This paper cites Tpu v4: An optically reconfigurable supercom- puter for machine learning with hardware support for embeddings,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Tpu v4: An optically reconfigurable supercom- puter for machine learning with hardware support for embeddings,

Reference 13

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Observation 369bccca-7b05-4269-848d-6e35f905dd89 · outbound

This paper cites Vitcod: Vision transformer acceleration via dedicated algorithm and accelerator co-design,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Vitcod: Vision transformer acceleration via dedicated algorithm and accelerator co-design,

Reference 14

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Observation 797bbb31-7b96-45de-8e11-88e661372aee · outbound

This paper cites A survey on silicon photonics for deep learning,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators A survey on silicon photonics for deep learning,

Reference 15

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Observation b42088dc-d852-4e8d-bb1b-f95b777cc162 · outbound

This paper cites Albireo: Energy- efficient acceleration of convolutional neural networks via silicon pho- tonics,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Albireo: Energy- efficient acceleration of convolutional neural networks via silicon pho- tonics,

Reference 16

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Observation 0c8adda4-21da-47ad-bd2c-60d58f8763de · outbound

This paper cites Photonics for artificial intelligence and neuromorphic computing,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Photonics for artificial intelligence and neuromorphic computing,

Reference 17

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Observation b0f4adc7-3689-46af-99a2-0bd0dd1b2e6e · outbound

This paper cites Light in ai: toward efficient neurocomputing with optical neural networks—a tutorial,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Light in ai: toward efficient neurocomputing with optical neural networks—a tutorial,

Reference 18

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Observation c7042807-e491-48cb-9983-46599b91aa02 · outbound

This paper cites Simphony: A device-circuit-architecture cross-layer modeling and simulation frame- work for heterogeneous electronic-photonic ai system,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Simphony: A device-circuit-architecture cross-layer modeling and simulation frame- work for heterogeneous electronic-photonic ai system,

Reference 19

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Observation 97fe1570-3c65-4519-9de3-2261d984cb4c · outbound

This paper cites Deep learning with coherent nanophotonic circuits,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Deep learning with coherent nanophotonic circuits,

Reference 20

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Observation 9e8db453-2ffd-44d5-ba93-afea31626603 · outbound

This paper cites Neuromorphic photonic networks using silicon photonic weight banks,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Neuromorphic photonic networks using silicon photonic weight banks,

Reference 21

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Observation 1ab021de-a2f8-4b8e-ba14-a4ecd135336f · outbound

This paper cites Crosslight: A cross- layer optimized silicon photonic neural network accelerator,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Crosslight: A cross- layer optimized silicon photonic neural network accelerator,

Reference 22

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Observation aa60eaa5-12d7-46db-a838-58bc2ec4ee4e · outbound

This paper cites Parallel convolutional processing using an integrated photonic tensor core,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Parallel convolutional processing using an integrated photonic tensor core,

Reference 23

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Observation c8d6e3c3-8f75-4625-aa99-0b238a43ad0c · outbound

This paper cites Lightening-transformer: A dynamically- operated optically-interconnected photonic transformer accelerator,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Lightening-transformer: A dynamically- operated optically-interconnected photonic transformer accelerator,

Reference 24

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Observation 2bda55bd-56e2-4cf5-9d6a-bb0ace93d552 · outbound

This paper cites Auto-vit-acc: An fpga-aware automatic acceleration framework for vision transformer with mixed-scheme quantization,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Auto-vit-acc: An fpga-aware automatic acceleration framework for vision transformer with mixed-scheme quantization,

Reference 25

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Observation 84e09224-a2e7-4f90-bb02-e7acdfc52a4a · outbound

This paper cites Heatvit: Hardware-efficient adaptive token pruning for vision transformers,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Heatvit: Hardware-efficient adaptive token pruning for vision transformers,

Reference 26

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Observation f2ad4627-69f8-498a-97cc-d57535021f93 · outbound

This paper cites Sprint: A high-performance, energy- efficient, and scalable chiplet-based accelerator with photonic intercon- nects for cnn inference,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Sprint: A high-performance, energy- efficient, and scalable chiplet-based accelerator with photonic intercon- nects for cnn inference,

Reference 27

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Observation 8945ac39-4347-4036-a95d-b90148dab92d · outbound

This paper cites Spacx: Silicon photonics-based scalable chiplet accelerator for dnn inference,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Spacx: Silicon photonics-based scalable chiplet accelerator for dnn inference,

Reference 28

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Observation 97098b91-9500-4b3e-b83c-6e6ec5345641 · outbound

This paper cites Tron: Transformer neural network acceleration with non-coherent silicon photonics,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Tron: Transformer neural network acceleration with non-coherent silicon photonics,

Reference 29

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Observation 0e49a01e-ef67-42a5-baef-1b65d4a9477c · outbound

This paper cites A light-speed large language model accelerator with optical stochastic computing,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators A light-speed large language model accelerator with optical stochastic computing,

Reference 30

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Observation 09d79c39-bd54-40bd-b863-c8e354f2a778 · outbound

This paper cites Astra: A stochastic transformer neural network accelerator with silicon photonics,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Astra: A stochastic transformer neural network accelerator with silicon photonics,

Reference 31

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Observation 0b7458d7-1365-46c4-8199-02a9b4f09f02 · outbound

This paper cites Merit: A sustainable dnn accelerator design with photonic phase-change memory,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Merit: A sustainable dnn accelerator design with photonic phase-change memory,

Reference 32

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Observation 1e6c7357-e9e8-46c5-985c-f21a8982078f · outbound

This paper cites Hyatten: Hybrid photonic-digital architec- ture for accelerating attention mechanism,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Hyatten: Hybrid photonic-digital architec- ture for accelerating attention mechanism,

Reference 33

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Observation f9b5d5f2-b312-4628-ae6b-697d018c689a · outbound

This paper cites P-dac: Power-efficient photonic accelerators for llm inference,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators P-dac: Power-efficient photonic accelerators for llm inference,

Reference 34

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source=pdf_text observed=2026-06-28T08:13:04.763453Z digest=sha256:cfeccf6bb77f9653268465cedd5d6ef405426839ca71ae068a3803a71fdc3061

Observation acee979d-e799-4531-bcf5-be43971d6bcc · outbound

This paper cites En- lighten: Lighten the transformer, enable efficient optical acceleration,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators En- lighten: Lighten the transformer, enable efficient optical acceleration,

Reference 35

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verified exact
arxiv_id, observed 2026-07-02T05:26:39.849830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T08:13:04.763453Z digest=sha256:2e730346a4963fadfe487e138990df67d8402293ee4237dded59b9364f316d70

Observation 2297e605-660a-4b19-bcab-51aba1ab58c7 · outbound

This paper cites Drmap: A generic dram data mapping policy for energy-efficient processing of convolu- tional neural networks,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Drmap: A generic dram data mapping policy for energy-efficient processing of convolu- tional neural networks,

Reference 36

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unresolved
no resolver link, observed 2026-06-28T08:13:04.763453Z

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source=pdf_text observed=2026-06-28T08:13:04.763453Z digest=sha256:587367124242ef8d0566be5eee337e7a6572f59ff6cab1d1f1a9bf23fbed8211

Observation fae4e553-112c-4675-b945-b8bbb5c15607 · outbound

This paper cites Romanet: Fine-grained reuse-driven off-chip memory access management and data organization for deep neural network acceler- ators,.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators Romanet: Fine-grained reuse-driven off-chip memory access management and data organization for deep neural network acceler- ators,

Reference 37

Resolution
unresolved
no resolver link, observed 2026-06-28T08:13:04.763453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T08:13:04.763453Z digest=sha256:7bdf0f9a380fe09c92aac97f43e3c608a34a695d01c6dcd85a63f82974e2e725

Observation 5f78d1fd-e900-40f4-ba30-aaf0ca91e48a · outbound

This paper cites PENDRAM: Enabling High-Performance and Energy-Efficient Processing of Deep Neural Networks through a Generalized DRAM Data Mapping Policy.

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators PENDRAM: Enabling High-Performance and Energy-Efficient Processing of Deep Neural Networks through a Generalized DRAM Data Mapping Policy

Reference 38

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verified exact
arxiv_id, observed 2026-07-02T05:26:39.870105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T08:13:04.763453Z digest=sha256:f12d2ea37e627119e1c607750ef7dbc9c0546e15cbdee6aa0b9381eaea09202f

Pith citing papers

No inbound Pith citation observations are available.