Paper Citation Record · LEDGER

Torch.fx: Practical Program Capture and Transformation for Deep Learning in Python

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2112.08429.

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

pith.paper-citation-record.v1
2112.08429 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:31:49.793139Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:47:37.698622Z

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 7653016a-47e8-4a14-a7ca-30104e418a9e · inbound

PyG 2.0: Scalable Learning on Real World Graphs cites this paper.

PyG 2.0: Scalable Learning on Real World Graphs Torch.fx: Practical Program Capture and Transformation for Deep Learning in Python

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-06T15:03:07.616640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3eccbcc-586a-4a48-bb71-afdd3196d5e7 · inbound

GraphMend: Code Transformations for Fixing Graph Breaks in PyTorch 2 cites this paper.

GraphMend: Code Transformations for Fixing Graph Breaks in PyTorch 2 Torch.fx: Practical Program Capture and Transformation for Deep Learning in Python

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-18T16:06:34.996707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 21066473-b826-4001-92c1-5f9368b10766 · inbound

Scalable Synthesis of distributed LLM workloads through Symbolic Tensor Graphs cites this paper.

Scalable Synthesis of distributed LLM workloads through Symbolic Tensor Graphs Torch.fx: Practical Program Capture and Transformation for Deep Learning in Python

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:49.782131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00cad49c-27a3-430a-8812-fed9e886a552 · inbound

Flint: Compiler Enabled Cluster-Free Design Space Exploration for Distributed ML cites this paper.

Flint: Compiler Enabled Cluster-Free Design Space Exploration for Distributed ML Torch.fx: Practical Program Capture and Transformation for Deep Learning in Python

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T05:25:55.192119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1965e506-6e9e-4cd0-bcf2-336cd0f6634e · inbound

ExecuTorch -- A Unified PyTorch Solution to Run AI Models On-Device cites this paper.

ExecuTorch -- A Unified PyTorch Solution to Run AI Models On-Device Torch.fx: Practical Program Capture and Transformation for Deep Learning in Python

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T07:56:27.728026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4d6a4874-e4c0-4e87-be67-9beb15862db6 · inbound

Self-Distillation Policy Optimization via Visual Feedback: Bridging Code and Visual Artifacts cites this paper.

Self-Distillation Policy Optimization via Visual Feedback: Bridging Code and Visual Artifacts Torch.fx: Practical Program Capture and Transformation for Deep Learning in Python

Reference 23

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T04:47:37.700473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7557ebae-6e36-4667-b664-c7d90dd98660 · inbound

Memory-Efficient Activation Checkpointing with Sliding Window and Hirschberg's Algorithm for 0/1 Knapsack Solving in PyTorch cites this paper.

Memory-Efficient Activation Checkpointing with Sliding Window and Hirschberg's Algorithm for 0/1 Knapsack Solving in PyTorch Torch.fx: Practical Program Capture and Transformation for Deep Learning in Python

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-14T04:31:49.793139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.