Paper Citation Record · LEDGER

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

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 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 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:19:29.168874Z

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

Observation 5b033ee9-601f-4d05-bac6-400ec649f6a7 · inbound

$\mu$nit Scaling: Simple and Scalable FP8 LLM Training cites this paper.

$\mu$nit Scaling: Simple and Scalable FP8 LLM Training FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-08T17:19:29.168874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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.

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.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.