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Paper Citation Record · LEDGER

FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2101.05615.

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

pith.paper-citation-record.v1
2101.05615 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:47:31.893525Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

20
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation f5dbf02c-671b-4976-ba35-6f697b754af9 · inbound

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale cites this paper.

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference

Reference 142

Resolution
verified exact
arxiv_id, observed 2026-05-13T13:35:36.105091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T13:35:35.972596Z digest=sha256:da0f427bea9b244e1243df58c09ac45defdfd98b9a9f768ea99c89fdfc61cadd

Observation 2760bea2-f8f3-4305-86a7-8cd51bcb7228 · inbound

Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations cites this paper.

Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference

Reference 124

Resolution
verified exact
arxiv_id, observed 2026-05-13T19:39:32.859337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T19:39:32.740496Z digest=sha256:b8c1fb13d77e550aa9392631fc0f75d46b5c92a6fefad3ad61e4ac75a1df4bc0

Observation 96eee25f-712e-4760-b1c1-27ccf601c395 · inbound

FEATHER: A Reconfigurable Accelerator with Data Reordering Support for Low-Cost On-Chip Dataflow Switching cites this paper.

FEATHER: A Reconfigurable Accelerator with Data Reordering Support for Low-Cost On-Chip Dataflow Switching FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-24T01:13:42.916362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-24T01:09:38.836949Z digest=sha256:31b4b1e54f36b59188bbee8a1f69687e3ff985af8a42743645f130b9ae0aa916

Observation 07c1218e-4f7c-43b9-a57c-2a30ab3652fb · inbound

PinFM: Foundation Model for User Activity Sequences at a Billion-scale Visual Discovery Platform cites this paper.

PinFM: Foundation Model for User Activity Sequences at a Billion-scale Visual Discovery Platform FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T16:47:31.893525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:47:31.893525Z digest=sha256:488ec5748fd2433fac1445b9cec926ed0f29da960eb66049200d558ad06c3841

Observation dd22d635-801e-4206-9aa6-fcea97909e6a · inbound

Towards Automated Kernel Generation in the Era of LLMs cites this paper.

Towards Automated Kernel Generation in the Era of LLMs FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-03T08:49:48.482023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T08:49:48.482023Z digest=sha256:3d5b63c273095b3625eea10fe8e62468d4a090aec1b7b263e42c5bc47f5be525

Observation aa3f774a-d437-4994-b5e1-5a13dd7bee76 · inbound

Privatar: Scalable Privacy-preserving Multi-user VR via Secure Offloading cites this paper.

Privatar: Scalable Privacy-preserving Multi-user VR via Secure Offloading FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference

Reference 160

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T06:21:26.896267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-10T06:20:18.479234Z digest=sha256:5c8780064666ecbf5cf8a733adf1aaae0f13a2032158a80ff42568814522c267

Observation b5c8fb0b-47ee-4488-a785-69b66c574855 · inbound

At the Edge of the Heart: ULP FPGA-Based CNN for On-Device Cardiac Feature Extraction in Smart Health Sensors for Astronauts cites this paper.

At the Edge of the Heart: ULP FPGA-Based CNN for On-Device Cardiac Feature Extraction in Smart Health Sensors for Astronauts FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-12T00:46:12.479046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-07T14:26:58.326728Z digest=sha256:1e7b4facda750a044a1024d99fed87fa601966b4dfc1ecd9bc2b253270a46976

Observation 95920229-3736-482e-80cc-1ff5087bff86 · inbound

One Pool, Two Caches: Adaptive HBM Partitioning for Accelerating Generative Recommender Serving cites this paper.

One Pool, Two Caches: Adaptive HBM Partitioning for Accelerating Generative Recommender Serving FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-08T19:49:07.534023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-08T17:44:18.414311Z digest=sha256:14d2105c889290d7c985e3ac09fedc3c753773f8e56ae11585d0f2e14e448dff

Observation 1292add8-cc9f-451e-9259-7b48553ee9a5 · inbound

An Efficient Hybrid Sparse Attention with CPU-GPU Parallelism for Long-Context Inference cites this paper.

An Efficient Hybrid Sparse Attention with CPU-GPU Parallelism for Long-Context Inference FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-11T03:05:54.157523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-11T02:56:28.828593Z digest=sha256:a0aeb51966ba80954546855f477582ba93d55c8ba2b69c1a49f4deec4a6337d5

Observation dfa390ab-a690-4d8a-af32-b1c62461146b · inbound

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale cites this paper.

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:06:28.175681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-12T04:33:41.411292Z digest=sha256:db3608f610ca322f422162bc3738a7c44d9f75807585f19af1f32b3d0e5573f2

Observation 47b5be0e-cc8a-43b0-8c48-04cc7de10e60 · inbound

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale cites this paper.

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-15T04:59:46.240687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-15T04:55:01.973832Z digest=sha256:f389f596b3b92b55145897dd0b80396c17d67fd3132ff550aa1d84dca93209bb

Observation 5c7115d2-098a-4304-a357-d34a96f3594c · inbound

DPIFrame: A Dual-Level Parallelism Acceleration Framework for CTR Model Inference cites this paper.

DPIFrame: A Dual-Level Parallelism Acceleration Framework for CTR Model Inference FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-07-04T07:09:38.142853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-26T13:42:59.458894Z digest=sha256:0a37e603f442fc2039131b5463a9501a4d4db247d1ca0664b5b43810eed20e7a

Observation 07555963-89e6-40ca-b723-6a9d7d261074 · inbound

Energy-Efficient CNN Acceleration with MSDF Digit-Serial Arithmetic on FPGA cites this paper.

Energy-Efficient CNN Acceleration with MSDF Digit-Serial Arithmetic on FPGA FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-07-04T20:50:10.678976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-25T19:39:19.171282Z digest=sha256:d3431b634b667fe5a24df39b23724c8791f12b8b483d452abdbc97f5b41c5824