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Paper Citation Record · LEDGER

VAQF: Fully Automatic Software-Hardware Co-Design Framework for Low-Bit Vision Transformer

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2201.06618.

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

pith.paper-citation-record.v1
2201.06618 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T04:51:34.757196Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T05:26:39.845024Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 47156234-fdd7-4df7-a25d-005371eddb5f · inbound

Mamba-X: An End-to-End Vision Mamba Accelerator for Edge Computing Devices cites this paper.

Mamba-X: An End-to-End Vision Mamba Accelerator for Edge Computing Devices VAQF: Fully Automatic Software-Hardware Co-Design Framework for Low-Bit Vision Transformer

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-06T04:51:34.757196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:51:34.757196Z digest=sha256:d2bb587027e264fa6970d272609264f24b339142cb83e9b9044478faec35dbcb

Observation c01a33a8-280b-44d2-8ac1-018a4edd2b0b · inbound

Trilinear Compute-in-Memory Architecture for Energy-Efficient Transformer Acceleration cites this paper.

Trilinear Compute-in-Memory Architecture for Energy-Efficient Transformer Acceleration VAQF: Fully Automatic Software-Hardware Co-Design Framework for Low-Bit Vision Transformer

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-05-11T07:55:59.647252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T16:54:25.942236Z digest=sha256:a137b66c8566ff42ccf3008d7c36e73d5864efcdd3c4713ead5b6d40bab9f77a

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

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

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

Resolution
verified exact
arxiv_id, observed 2026-07-02T05:26:39.846966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-28T08:13:04.763453Z digest=sha256:70d65d85f0c7e870c7376004ad8534dcb32ef2f620aeca2df8be1a64a030fe6e

Observation 9e0a7a4f-5073-4f13-8cfe-a5e9e8a82b72 · inbound

FlexViT: A Flexible FPGA-based Accelerator for Edge Vision Transformers cites this paper.

FlexViT: A Flexible FPGA-based Accelerator for Edge Vision Transformers VAQF: Fully Automatic Software-Hardware Co-Design Framework for Low-Bit Vision Transformer

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-07-01T12:15:44.157232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-01T02:14:18.760398Z digest=sha256:8049102a222cdbad4c3fdc05df0636bb7141d862ec64a548f17588d9efa22afb

Observation a2b57f28-02d8-4957-aa9c-0fe6e7838eb3 · inbound

ExaGEMM: Exploration Framework for CPU-Driven ML Inference via Associative In-Register Computing for Low-Bit GEMM cites this paper.

ExaGEMM: Exploration Framework for CPU-Driven ML Inference via Associative In-Register Computing for Low-Bit GEMM VAQF: Fully Automatic Software-Hardware Co-Design Framework for Low-Bit Vision Transformer

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-02T01:37:48.483123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T01:37:48.483123Z digest=sha256:482821ad4680fd0c5f4670e7d0acba727eecabf3f1165a3360bc9a492b48e33d