Paper Citation Record · LEDGER

TorchAO: PyTorch-Native Training-to-Serving Model Optimization

As of 7 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 8 inbound Pith citation observations for arXiv:2507.16099.

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

pith.paper-citation-record.v1
2507.16099 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:24:17.854387Z

measured 23 of 23 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T15:11:09.157452Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T06:29:37.605132Z

Reference resolution

15 of 15 outbound references displayed

verified exact0
verified fuzzy1
unresolved14
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6ac0db3a-5086-4245-be3f-038de41f42d0 · outbound

This paper cites Accelerating Transformer Inference and Training with 2:4 Activation Sparsity.

TorchAO: PyTorch-Native Training-to-Serving Model Optimization Accelerating Transformer Inference and Training with 2:4 Activation Sparsity

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T15:24:16.428845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 564d2034-e16c-47d9-8aa3-0f0cbb3509e4 · outbound

This paper cites PARQ: Piecewise-Affine Regularized Quantization.

TorchAO: PyTorch-Native Training-to-Serving Model Optimization PARQ: Piecewise-Affine Regularized Quantization

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T15:24:16.681949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b832b031-4885-4357-8925-1d1b508f3784 · outbound

This paper cites TorchTitan: One-stop PyTorch native solution for production ready LLM pre-training.

TorchAO: PyTorch-Native Training-to-Serving Model Optimization TorchTitan: One-stop PyTorch native solution for production ready LLM pre-training

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T15:24:16.814568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28dc0925-555a-4564-98fb-2ff809e8a9e7 · outbound

This paper cites SpinQuant: LLM quantization with learned rotations.

TorchAO: PyTorch-Native Training-to-Serving Model Optimization SpinQuant: LLM quantization with learned rotations

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T15:24:16.930551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30b9630a-19d8-4f88-b4d8-f816bd38a0c7 · outbound

This paper cites Paretoq: Scaling laws in extremely low-bit llm quantization.

TorchAO: PyTorch-Native Training-to-Serving Model Optimization Paretoq: Scaling laws in extremely low-bit llm quantization

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T15:24:17.043894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74821af5-3621-4e38-a94a-85b7a787aef5 · outbound

This paper cites Accelerating Sparse Deep Neural Networks.

TorchAO: PyTorch-Native Training-to-Serving Model Optimization Accelerating Sparse Deep Neural Networks

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T15:24:17.178556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b732f6c7-90c8-4a87-af9b-f6255f175922 · outbound

This paper cites Microscaling Data Formats for Deep Learning.

TorchAO: PyTorch-Native Training-to-Serving Model Optimization Microscaling Data Formats for Deep Learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T15:24:17.313135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6293d38-3f58-4ad3-a320-9682b93cfbd1 · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

TorchAO: PyTorch-Native Training-to-Serving Model Optimization HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T15:24:17.619438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66dda01f-7d0e-465e-9fa7-60b22784bcb4 · outbound

This paper cites GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection.

TorchAO: PyTorch-Native Training-to-Serving Model Optimization GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T15:24:17.752626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebc71b69-400d-4859-bc55-e642d9b44877 · outbound

This paper cites SGLang: Efficient Execution of Structured Language Model Programs.

TorchAO: PyTorch-Native Training-to-Serving Model Optimization SGLang: Efficient Execution of Structured Language Model Programs

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T15:24:17.854387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b71d901-8d56-41e2-bc1f-11bebb7fc930 · outbound

This paper cites Torchao: Low-bit arm cpu and metal ker- nels for linear and embedding ops.

TorchAO: PyTorch-Native Training-to-Serving Model Optimization Torchao: Low-bit arm cpu and metal ker- nels for linear and embedding ops

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:24:18.383878Z

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.

Observation f1902be7-ee35-4736-88f9-ce89c36aae13 · outbound

This paper cites Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations.

TorchAO: PyTorch-Native Training-to-Serving Model Optimization Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-06T15:24:16.568903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3f3c4be-15f1-46e3-a09e-4fea89dbad4a · outbound

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

TorchAO: PyTorch-Native Training-to-Serving Model Optimization LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T15:24:16.077657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d3bdde2-b7e0-4445-bd84-c6aaa43f1abe · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

TorchAO: PyTorch-Native Training-to-Serving Model Optimization DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T15:24:16.299446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ac0f1cc-33d8-4b9f-a5b7-b6e9d9b4f38c · outbound

This paper cites The Llama 3 Herd of Models.

TorchAO: PyTorch-Native Training-to-Serving Model Optimization The Llama 3 Herd of Models

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-06T15:24:16.203023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation cc0bb48c-2b7f-4807-b097-a7f8e6b65a48 · inbound

Zero-Shot Quantization via Weight-Space Arithmetic cites this paper.

Zero-Shot Quantization via Weight-Space Arithmetic TorchAO: PyTorch-Native Training-to-Serving Model Optimization

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-13T20:08:12.611754Z

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.

Observation 7c13a4b4-3f55-48c8-a253-9f9f7be4021e · inbound

StoSignSGD: Unbiased Structural Stochasticity Fixes SignSGD for Training Large Language Models cites this paper.

StoSignSGD: Unbiased Structural Stochasticity Fixes SignSGD for Training Large Language Models TorchAO: PyTorch-Native Training-to-Serving Model Optimization

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-10T12:15:22.222337Z

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.

Observation 159391d1-f2ed-4895-9a8d-0999c5284a78 · inbound

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

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale TorchAO: PyTorch-Native Training-to-Serving Model Optimization

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:06:28.230353Z

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.

Observation e25d6f60-c26b-4a7a-8a7e-5ec5fe1938a5 · inbound

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

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale TorchAO: PyTorch-Native Training-to-Serving Model Optimization

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-05-15T04:59:46.033838Z

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.

Observation 931e6dab-9c33-4ac9-8d17-87802f39186a · inbound

torchtune: PyTorch native post-training library cites this paper.

torchtune: PyTorch native post-training library TorchAO: PyTorch-Native Training-to-Serving Model Optimization

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:43:58.665641Z

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.

Observation 74c80bb9-a86d-47ca-a07a-74b108be140b · inbound

CAT-Translate: Building Compact Open-Source Models for Japanese-English Translation cites this paper.

CAT-Translate: Building Compact Open-Source Models for Japanese-English Translation TorchAO: PyTorch-Native Training-to-Serving Model Optimization

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-07-04T06:29:37.606958Z

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.

Observation 136220bb-1fef-44b7-9aba-4e218fb10ad2 · inbound

StreamDQ: Near-Memory Weight DeQuantization in Custom HBM for Scalable AI Inference Acceleration cites this paper.

StreamDQ: Near-Memory Weight DeQuantization in Custom HBM for Scalable AI Inference Acceleration TorchAO: PyTorch-Native Training-to-Serving Model Optimization

Reference 52

Resolution: unresolved; no resolver link, observed 2026-07-13T01:10:03.032181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b1ccc5c-42f3-402b-8bb4-12c1d15be4f8 · inbound

Recti-Q: Feature-Space Rectification for Out-of-Distribution-Robust Quantized Perception in Edge Robotics cites this paper.

Recti-Q: Feature-Space Rectification for Out-of-Distribution-Robust Quantized Perception in Edge Robotics TorchAO: PyTorch-Native Training-to-Serving Model Optimization

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T15:11:09.157452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.