Paper Citation Record · LEDGER

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism

As of 21 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2606.09377.

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

pith.paper-citation-record.v1
2606.09377 v2

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T17:20:04.247977Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

28 of 28 outbound references displayed

verified exact9
verified fuzzy0
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch4

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ca44ac7c-4491-4a0e-b871-b2a94026fc93 · outbound

This paper cites URL https://www.semanticscholar.org/paper/Reluplex% 3A-An-Efficient-SMT-Solver-for-Verifying-Katz-Barrett/ b0dc598adda48acab590f95a5985fcc7abf2aca9.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism URL https://www.semanticscholar.org/paper/Reluplex% 3A-An-Efficient-SMT-Solver-for-Verifying-Katz-Barrett/ b0dc598adda48acab590f95a5985fcc7abf2aca9

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-27T17:20:04.247977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88784cdc-8239-4a55-a5e9-75b22a3a9800 · outbound

This paper cites Evaluating Robustness of Neural Networks with Mixed Integer Programming.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism Evaluating Robustness of Neural Networks with Mixed Integer Programming

Reference 2

Resolution: metadata mismatch; local_arxiv, observed 2026-07-03T00:17:29.236634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0d0e58ec-03dd-4d72-ba68-282040521df2 · outbound

This paper cites Optimized Symbolic Interval Propagation for Neural Network Verification.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism Optimized Symbolic Interval Propagation for Neural Network Verification

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:17:29.239093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ea37b0f6-4de1-4afe-b65e-fd1a8cf8662d · outbound

This paper cites The Third International Verification of Neural Networks Competition (VNN-COMP 2022): Summary and Results.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism The Third International Verification of Neural Networks Competition (VNN-COMP 2022): Summary and Results

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T00:17:29.233922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3540f83e-8265-4997-a307-e614314a56a1 · outbound

This paper cites The Fourth International Verification of Neural Networks Competition (VNN-COMP 2023): Summary and Results.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism The Fourth International Verification of Neural Networks Competition (VNN-COMP 2023): Summary and Results

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T00:17:29.247487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 26247f13-dd23-4c00-8ce0-6e6cad928120 · outbound

This paper cites Marabou 2.0: A Versatile Formal Analyzer of Neural Networks.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism Marabou 2.0: A Versatile Formal Analyzer of Neural Networks

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:17:29.228876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1cb5f54e-491a-4107-8f3a-2695de25e30c · outbound

This paper cites The Fifth International Verification of Neural Networks Competition (VNN-COMP 2024): Summary and Results.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism The Fifth International Verification of Neural Networks Competition (VNN-COMP 2024): Summary and Results

Reference 7

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T00:17:29.231293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7e02039f-4ee9-458c-a3d4-bf49f9684e11 · outbound

This paper cites nnenum: Verification of ReLU neural networks with optimized abstrac- tion refinement, 2021.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism nnenum: Verification of ReLU neural networks with optimized abstrac- tion refinement, 2021

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-27T17:20:04.247977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a87a171-2bed-42b5-be50-e8046ffecf2f · outbound

This paper cites Training neural networks is ∃R-complete.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism Training neural networks is ∃R-complete

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-27T17:20:04.247977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc04ad7a-afa6-4599-8661-26b6b612301c · outbound

This paper cites VNN-LIB: The verification of neural networks library, 2021.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism VNN-LIB: The verification of neural networks library, 2021

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-27T17:20:04.247977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94e44ed7-3c43-4a0f-8f40-16255aa37f5b · outbound

This paper cites Supporting standardization of neural networks verification with vnn-lib and coconet.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism Supporting standardization of neural networks verification with vnn-lib and coconet

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-27T17:20:04.247977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82dab82f-2d06-4aad-bb65-b152c7a50bf7 · outbound

This paper cites NeuralSAT: A DPLL(T)-based framework for verifying deep neural networks, 2023.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism NeuralSAT: A DPLL(T)-based framework for verifying deep neural networks, 2023

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-27T17:20:04.247977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab84d461-0fe2-49e6-a229-047c077fe503 · outbound

This paper cites Enhancing neural networks through formal verification.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism Enhancing neural networks through formal verification

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-27T17:20:04.247977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b5054ae-b3f9-46bb-8cdb-72f6cb79381f · outbound

This paper cites Le, Yonghui Wu, and Zhifeng Chen.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism Le, Yonghui Wu, and Zhifeng Chen

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-27T17:20:04.247977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bac70cd-3bb6-4018-8b8a-4bea4b08ff0a · outbound

This paper cites Input Validation for Neural Networks via Runtime Local Robustness Verification.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism Input Validation for Neural Networks via Runtime Local Robustness Verification

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:17:29.230630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 135482d7-66aa-413f-b007-5760beae3e81 · outbound

This paper cites Advancing Neural Network Verification through Hierarchical Safety Abstract Interpretation.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism Advancing Neural Network Verification through Hierarchical Safety Abstract Interpretation

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:17:29.217809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b5c8236f-79d5-4275-8a37-9f95630ebd02 · outbound

This paper cites Interval reachability analysis: Bounding trajectories of uncertain systems with boxes for control and verification, 2021.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism Interval reachability analysis: Bounding trajectories of uncertain systems with boxes for control and verification, 2021

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:17:29.244715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 162d2421-43e2-406b-85a5-b8585b44dd77 · outbound

This paper cites Moore, R.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism Moore, R

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-27T17:20:04.247977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9a3831e-3076-4fbc-a734-15d056276f3c · outbound

This paper cites Scaling polyhedral neural network verification on GPUs, 2021.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism Scaling polyhedral neural network verification on GPUs, 2021

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-27T17:20:04.247977Z

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Unavailable: canonical work link unavailable.

Observation e1156911-3783-43f1-a0e7-e3f31d17b286 · outbound

This paper cites ZeRO: Memory Optimizations Toward Training Trillion Parameter Models.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism ZeRO: Memory Optimizations Toward Training Trillion Parameter Models

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-07-03T00:17:29.241864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0d9ac18c-c686-4c4b-a117-b4f16ad5acb2 · outbound

This paper cites ˜Zico Kolter, Suman Jana, Cho-Jui Hsieh, and Huan Zhang.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism ˜Zico Kolter, Suman Jana, Cho-Jui Hsieh, and Huan Zhang

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-27T17:20:04.247977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae9bab58-4bf5-4273-9541-c6e69842b04e · outbound

This paper cites Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-07-03T00:17:29.250251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 105ad66a-35fa-430f-a008-b1eee79f8bf6 · outbound

This paper cites An abstract domain for certifying neural networks, 2019.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism An abstract domain for certifying neural networks, 2019

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-27T17:20:04.247977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d661f2f1-299f-4756-80d2-f4ba04ab9c12 · outbound

This paper cites Zico Kolter.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism Zico Kolter

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-27T17:20:04.247977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdd464b2-7033-4986-8ed9-77a57806aaf4 · outbound

This paper cites Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verification.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verification

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:17:29.226247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ad8f0366-e1e2-4a1c-9b7f-4fdeb5e48937 · outbound

This paper cites Automatic perturbation analysis for scalable certified robustness and beyond, 2020.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism Automatic perturbation analysis for scalable certified robustness and beyond, 2020

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-27T17:20:04.247977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a6dfad0-1806-4422-8aed-341518923642 · outbound

This paper cites Efficient Neural Network Robustness Certification with General Activation Functions.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism Efficient Neural Network Robustness Certification with General Activation Functions

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-07-03T00:17:29.220417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c2de0b72-bb49-4da4-a71e-22d2e260ce56 · outbound

This paper cites ˜Zico Kolter.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism ˜Zico Kolter

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-27T17:20:04.247977Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.