Paper Citation Record · LEDGER

PipeDream: Fast and Efficient Pipeline Parallel DNN Training

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 28 inbound Pith citation observations for arXiv:1806.03377.

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

pith.paper-citation-record.v1
1806.03377 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 28 of 28 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 28 of 28 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:20:58.789532Z

measured 1 of 1 external citation measurements

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

Source: pith, 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

97
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 8f99c712-d1bb-448e-a4d6-9732757e5846 · inbound

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

Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-10T18:34:44.836255Z

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 5405b971-f3cd-4a37-8850-60e169e1c25f · inbound

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

ZeRO: Memory Optimizations Toward Training Trillion Parameter Models PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-05-16T09:24:35.867064Z

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 3efc4f73-603d-488e-a080-3756f8fb6d6f · inbound

GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding cites this paper.

GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-11T02:26:44.805619Z

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 54a09fd4-1241-4169-b150-b087037a10e1 · inbound

Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity cites this paper.

Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-12T23:57:11.048267Z

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 af61a47e-b27d-4f06-98ad-f7133b7bbb2c · inbound

ST-MoE: Designing Stable and Transferable Sparse Expert Models cites this paper.

ST-MoE: Designing Stable and Transferable Sparse Expert Models PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 62

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T23:14:25.548820Z

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 70ce4c06-9ed9-491f-bc29-cd60621b7424 · inbound

GPT-NeoX-20B: An Open-Source Autoregressive Language Model cites this paper.

GPT-NeoX-20B: An Open-Source Autoregressive Language Model PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-05-24T12:34:28.303900Z

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 e4ecba00-e008-45be-8f6f-888fd6110f9c · inbound

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

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 73

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T13:35:36.081409Z

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 d5fa683c-080d-4f90-80c6-d0c86f35f8ee · inbound

PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel cites this paper.

PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-12T04:15:20.068407Z

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 aff25c00-436b-4564-af9a-7f1b056038f1 · inbound

DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models cites this paper.

DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 52

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T01:07:22.247126Z

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 af27a4c9-7849-4c41-8384-4732354c24f0 · inbound

DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models cites this paper.

DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-11T22:50:11.837908Z

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 0a6bbe57-34e5-4909-9cd8-049a27289036 · inbound

AI Safety Landscape for Large Language Models: Taxonomy, State-of-the-art, and Future Directions cites this paper.

AI Safety Landscape for Large Language Models: Taxonomy, State-of-the-art, and Future Directions PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 298

Resolution: verified exact; local_arxiv, observed 2026-05-23T21:55:50.703652Z

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 0d08922e-937e-4b4f-8655-414507764227 · inbound

MixGCN: Scalable GCN Training by Mixture of Parallelism and Mixture of Accelerators cites this paper.

MixGCN: Scalable GCN Training by Mixture of Parallelism and Mixture of Accelerators PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T22:20:58.789532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8c95e2a-01a0-4983-be3a-0787005b17af · inbound

Foundations of Large Language Models cites this paper.

Foundations of Large Language Models PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-10T20:14:58.823417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73f3d9ae-05b6-4a92-a784-b02222c5483c · inbound

COSMIC: Enabling Full-Stack Co-Design and Optimization of Distributed Machine Learning Systems cites this paper.

COSMIC: Enabling Full-Stack Co-Design and Optimization of Distributed Machine Learning Systems PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T15:31:08.413191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fcc388e8-10f4-48cc-a89d-78c841b56b78 · inbound

MPipeMoE: Memory Efficient MoE for Pre-trained Models with Adaptive Pipeline Parallelism cites this paper.

MPipeMoE: Memory Efficient MoE for Pre-trained Models with Adaptive Pipeline Parallelism PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T22:15:28.228455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85e46ada-e053-4c71-8814-64457dc87646 · inbound

Kimi K2: Open Agentic Intelligence cites this paper.

Kimi K2: Open Agentic Intelligence PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-10T17:49:28.128081Z

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 25377506-779f-42c7-8987-e064d909e00b · inbound

SpikingBrain: Spiking Brain-inspired Large Models cites this paper.

SpikingBrain: Spiking Brain-inspired Large Models PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-05-18T18:51:45.602853Z

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 054bdcd8-5793-454b-92ca-0a6f6a9321b3 · inbound

OctoPipe: Reducing Pipeline Bubbles for Heterogeneous Models via Co-Optimizing Partitioning, Placement, and Scheduling cites this paper.

OctoPipe: Reducing Pipeline Bubbles for Heterogeneous Models via Co-Optimizing Partitioning, Placement, and Scheduling PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T14:42:57.952940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 597bdd83-b4f5-4542-b453-a181c5219d31 · inbound

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

Scalable Synthesis of distributed LLM workloads through Symbolic Tensor Graphs PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:45.455385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7eddbc0a-8973-4737-8561-d409de6d01ae · inbound

Kling-Omni Technical Report cites this paper.

Kling-Omni Technical Report PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-05-15T21:00:58.638539Z

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 05b648a2-08d4-4458-a1d0-fa2137678b43 · inbound

Efficient Training on Multiple Consumer GPUs with RoundPipe cites this paper.

Efficient Training on Multiple Consumer GPUs with RoundPipe PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:31:26.754534Z

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 5403e35d-eb3f-4600-89da-66815d1f9523 · inbound

Rescaled Asynchronous SGD: Optimal Distributed Optimization under Data and System Heterogeneity cites this paper.

Rescaled Asynchronous SGD: Optimal Distributed Optimization under Data and System Heterogeneity PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 116

Resolution: metadata mismatch; local_arxiv, observed 2026-05-14T19:32:51.333375Z

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 7ef6ffc8-8e92-4591-9c1a-977506cb0111 · inbound

Demystifying Pipeline Parallelism: First Theory for PipeDream cites this paper.

Demystifying Pipeline Parallelism: First Theory for PipeDream PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 12

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T01:56:28.486918Z

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 0d016fad-29fb-487c-bc0b-673c9e4f078a · inbound

Breaking the Bubble: Asynchronous Pipeline Parallel Training with Bounded Weight Inconsistency cites this paper.

Breaking the Bubble: Asynchronous Pipeline Parallel Training with Bounded Weight Inconsistency PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-07-02T16:57:09.398018Z

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 cc59b262-0f21-4dbe-9b22-e66bdc41825e · inbound

Piper: A Programmable Distributed Training System cites this paper.

Piper: A Programmable Distributed Training System PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-07-03T07:57:44.641164Z

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 7f33d645-9fea-44e7-856c-e4fd06c44dcd · inbound

Simulating Unified Tensor Resharding in heterogeneous AI systems cites this paper.

Simulating Unified Tensor Resharding in heterogeneous AI systems PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-07-04T14:19:54.709742Z

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 5022126f-bf39-4c78-8384-9400b1cc8d5f · inbound

Auto-Scaling Heterogeneous Neural Processing Units for Energy and Cost-Efficient LLM Serving cites this paper.

Auto-Scaling Heterogeneous Neural Processing Units for Energy and Cost-Efficient LLM Serving PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-01T20:54:12.759516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 736d81f2-aaf5-4acc-83d5-acc22127cca2 · inbound

RAG-Stack: Co-Optimizing RAG Serving Performance and Quality cites this paper.

RAG-Stack: Co-Optimizing RAG Serving Performance and Quality PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-05T18:13:13.750734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.