Paper Citation Record · LEDGER

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations

As of 19 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 1 inbound Pith citation observation for arXiv:2501.09954.

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

pith.paper-citation-record.v1
2501.09954 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:33:37.691263Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:33:59.260617Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T20:34:03.137214Z

Reference resolution

35 of 35 outbound references displayed

verified exact3
verified fuzzy19
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 72e49753-fad8-4881-9ba9-aa2b594d0cc4 · outbound

This paper cites Algorithm-Hardware Co-Design of Distribution-Aware Logarithmic-Posit Encodings for Efficient DNN Inference.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Algorithm-Hardware Co-Design of Distribution-Aware Logarithmic-Posit Encodings for Efficient DNN Inference

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-10T19:33:38.382001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 958251d4-ffae-4ded-9882-60f38e26f37b · outbound

This paper cites Maeri: Enabling flexible dataflow mapping over dnn accelerators via reconfigurable interconnects,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Maeri: Enabling flexible dataflow mapping over dnn accelerators via reconfigurable interconnects,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:33:39.712234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 306b0f65-2fc9-4a38-9c69-efae8dc54106 · outbound

This paper cites MicroScopiQ: Accelerating Foundational Models through Outlier-Aware Microscaling Quantization.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations MicroScopiQ: Accelerating Foundational Models through Outlier-Aware Microscaling Quantization

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-10T19:33:38.278280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f382fe46-bccc-4bcb-a4d5-104ea4167f29 · outbound

This paper cites Dosa: Differentiable model-based one-loop search for dnn accelerators,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Dosa: Differentiable model-based one-loop search for dnn accelerators,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T19:33:36.913605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba5cd7df-3536-462d-95dd-70300ca752e0 · outbound

This paper cites AIRCHITECT: Learning Custom Architecture Design and Mapping Space.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations AIRCHITECT: Learning Custom Architecture Design and Mapping Space

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T19:33:37.003716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b90485d-0f0e-43a3-b7c0-26a60e7c5325 · outbound

This paper cites Nvdla deep learning accelerator,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Nvdla deep learning accelerator,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:33:39.681348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f45bc254-18b1-4c77-bd50-f2480d55d9f8 · outbound

This paper cites Eyeriss: An energy- efficient reconfigurable accelerator for deep convolutional neural net- works,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Eyeriss: An energy- efficient reconfigurable accelerator for deep convolutional neural net- works,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:33:39.635297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 29a83901-9d5f-46c4-aa3e-44ba4e7b1dc2 · outbound

This paper cites Shidiannao: Shifting vision processing closer to the sensor,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Shidiannao: Shifting vision processing closer to the sensor,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:33:39.522659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 82e3e79e-91f3-4367-8038-eff366639ecf · outbound

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

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Imagenet: A large-scale hierarchical image database,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T19:33:37.161185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dde3529d-1e1f-42db-8a1b-f1d292acb3ba · outbound

This paper cites Unified perceptual parsing for scene understanding,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Unified perceptual parsing for scene understanding,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T19:33:37.170370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ef4f350-b04c-4dea-a773-e1ccb0c4cf62 · outbound

This paper cites Learn- ing a continuous and reconstructible latent space for hardware accelerator design,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Learn- ing a continuous and reconstructible latent space for hardware accelerator design,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:33:39.414484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a64ac6fd-6da4-49f7-b386-1e3002c36a8d · outbound

This paper cites Confuciux: Autonomous hardware resource assignment for dnn accelerators using reinforcement learning,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Confuciux: Autonomous hardware resource assignment for dnn accelerators using reinforcement learning,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T19:33:37.189512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8baffe04-c066-4511-8c6d-6c1cd4ecd2d0 · outbound

This paper cites Gamma: Automating the hw mapping of dnn models on accelerators via genetic algorithm,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Gamma: Automating the hw mapping of dnn models on accelerators via genetic algorithm,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:33:39.339772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7c9b2a5a-cae5-40bf-8b7b-560a2905c5a8 · outbound

This paper cites Digamma: Domain- aware genetic algorithm for hw-mapping co-optimization for dnn accel- erators,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Digamma: Domain- aware genetic algorithm for hw-mapping co-optimization for dnn accel- erators,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:33:39.304519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c5411dfc-fe93-4a63-9f3e-7859c1f5581f · outbound

This paper cites Hasco: Towards agile hardware and software co-design for tensor computation,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Hasco: Towards agile hardware and software co-design for tensor computation,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:33:39.197567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 35af7329-1338-4fd9-8275-9a0adfd87cbb · outbound

This paper cites Gandse: Generative adversarial network-based design space exploration for neural network accelerator design,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Gandse: Generative adversarial network-based design space exploration for neural network accelerator design,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:33:39.099095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 131c0ede-3bf9-4aa3-8dc0-843ff388c331 · outbound

This paper cites A systematic methodology for characterizing scalability of dnn accelerators using scale-sim,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations A systematic methodology for characterizing scalability of dnn accelerators using scale-sim,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:33:39.002582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a8fbe63b-3d97-45b4-af17-40f607414904 · outbound

This paper cites Ntrans- net: A multi-scale neutrosophic-uncertainty guided transformer network for indoor depth completion,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Ntrans- net: A multi-scale neutrosophic-uncertainty guided transformer network for indoor depth completion,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:33:38.924752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2958999a-79da-4fe8-a9ba-ec535a54bfd1 · outbound

This paper cites MAESTRO: A data-centric approach to understand reuse, performance, and hardware cost of DNN mappings,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations MAESTRO: A data-centric approach to understand reuse, performance, and hardware cost of DNN mappings,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:33:38.893292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f342c4ba-af77-4214-aa0d-c3c0495256c0 · outbound

This paper cites A systematic methodology for characterizing scalability of dnn accelerators using scale-sim,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations A systematic methodology for characterizing scalability of dnn accelerators using scale-sim,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:33:38.847946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 29fa0b57-cb4f-414f-bebc-fd1738319230 · outbound

This paper cites Contrastive quant: quantization makes stronger contrastive learning,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Contrastive quant: quantization makes stronger contrastive learning,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:33:38.798195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ab94501e-bfda-476a-8057-1bd2cb190c02 · outbound

This paper cites Synergistic self- supervised and quantization learning,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Synergistic self- supervised and quantization learning,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:33:38.754552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5000218b-2e72-4b75-8bb3-ea0de7603fb2 · outbound

This paper cites Jumping through local minima: Quantization in the loss landscape of vision transformers,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Jumping through local minima: Quantization in the loss landscape of vision transformers,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:33:38.720048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9840c8e9-7190-4a3e-be97-03f06b22f6a1 · outbound

This paper cites CLAMP-ViT: Contrastive Data-Free Learning for Adaptive Post-Training Quantization of ViTs.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations CLAMP-ViT: Contrastive Data-Free Learning for Adaptive Post-Training Quantization of ViTs

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-10T19:33:38.062825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6ea39518-7e3e-4c6b-92d8-4dc13536c97a · outbound

This paper cites Positive–negative equal contrastive loss for semantic segmentation,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Positive–negative equal contrastive loss for semantic segmentation,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:33:38.697818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9c20ead8-c65a-4308-a0a2-cdfb871dfe88 · outbound

This paper cites Targeted supervised contrastive learning for long-tailed recognition,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Targeted supervised contrastive learning for long-tailed recognition,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:33:38.674852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b62c5b9e-5d9b-4448-8711-969368a13226 · outbound

This paper cites A meta-analysis of overfitting in machine learning,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations A meta-analysis of overfitting in machine learning,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T19:33:37.633401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07da979e-5004-4e15-a378-18be019dfc21 · outbound

This paper cites Attention is all you need,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Attention is all you need,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-10T19:33:37.640838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6741481b-5b7e-40d6-aa0f-dcdc33d67495 · outbound

This paper cites Automatic chemical design using a data-driven continuous representation of molecules,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Automatic chemical design using a data-driven continuous representation of molecules,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:33:38.622011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7a67e5d9-5d80-4c3a-a05f-9487ee4ed26d · outbound

This paper cites OccDepth: A Depth-Aware Method for 3D Semantic Scene Completion.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations OccDepth: A Depth-Aware Method for 3D Semantic Scene Completion

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T19:33:37.653147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c62f214-c846-49da-a80d-9d9cd91d7711 · outbound

This paper cites Generalized focal loss: Learning qualified and distributed bounding boxes for dense object detection,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Generalized focal loss: Learning qualified and distributed bounding boxes for dense object detection,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T19:33:37.659508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85ee32fe-07ca-45a1-8e89-302b7fd29881 · outbound

This paper cites Deep residual learning for image recognition,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Deep residual learning for image recognition,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T19:33:37.668651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f684d8e-5dc3-46fb-b6fa-2b2c9018ef7f · outbound

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

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T19:33:37.675761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d92b25d0-4abc-40c9-ab70-64c0483b62bc · outbound

This paper cites The Llama 3 Herd of Models.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations The Llama 3 Herd of Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-10T19:33:37.682431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7951d3ef-09e0-47b6-9313-91fe49119971 · outbound

This paper cites Mind mappings: Enabling efficient algorithm-accelerator mapping space search,.

AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations Mind mappings: Enabling efficient algorithm-accelerator mapping space search,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T19:33:37.691263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 2c6f2bf1-d7f4-43e8-a0fe-91159a8cdef5 · inbound

DiffAxE: Diffusion-driven Hardware Accelerator Generation and Design Space Exploration cites this paper.

DiffAxE: Diffusion-driven Hardware Accelerator Generation and Design Space Exploration AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-05T20:34:03.184551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.