Paper Citation Record · LEDGER

NanoFlow: Towards Optimal Large Language Model Serving Throughput

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2408.12757.

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

pith.paper-citation-record.v1
2408.12757 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 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 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:30:34.441416Z

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

0
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 9636216e-aac4-4212-a1ed-e54d8b11d05d · inbound

Kinetics: Rethinking Test-Time Scaling Laws cites this paper.

Kinetics: Rethinking Test-Time Scaling Laws NanoFlow: Towards Optimal Large Language Model Serving Throughput

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:34.441416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a275db72-d7ee-4520-bd53-7035783ed824 · inbound

Nexus:Proactive Intra-GPU Disaggregation of Prefill and Decode in LLM Serving cites this paper.

Nexus:Proactive Intra-GPU Disaggregation of Prefill and Decode in LLM Serving NanoFlow: Towards Optimal Large Language Model Serving Throughput

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-06T19:04:00.018717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11274d95-91cf-475e-b1a9-373b85f355a5 · inbound

On Evaluating Performance of LLM Inference Serving Systems cites this paper.

On Evaluating Performance of LLM Inference Serving Systems NanoFlow: Towards Optimal Large Language Model Serving Throughput

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T18:11:16.262684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55532324-5a12-45f1-b6fd-75421016dbd9 · inbound

On Evaluating Performance of LLM Inference Serving Systems cites this paper.

On Evaluating Performance of LLM Inference Serving Systems NanoFlow: Towards Optimal Large Language Model Serving Throughput

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T18:11:16.322242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fe95d27-a9fc-486f-8ac6-5b01de35e34a · inbound

Agentic Witnessing: Pragmatic and Scalable TEE-Enabled Privacy-Preserving Auditing cites this paper.

Agentic Witnessing: Pragmatic and Scalable TEE-Enabled Privacy-Preserving Auditing NanoFlow: Towards Optimal Large Language Model Serving Throughput

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-09T00:34:30.192398Z

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 fb2bbcf9-a1d8-4ab4-a0f5-38f112192068 · inbound

Resource-aware Computation-Communication Overlap for multi-GPU ML Workloads cites this paper.

Resource-aware Computation-Communication Overlap for multi-GPU ML Workloads NanoFlow: Towards Optimal Large Language Model Serving Throughput

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T03:37:35.991585Z

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 96d7fdc0-a735-4c31-9844-4c2b05b065aa · inbound

Achieving Cloud-Grade SLOs for Local Mixture-of-Experts Inference through CPU-GPU Hybrid Design cites this paper.

Achieving Cloud-Grade SLOs for Local Mixture-of-Experts Inference through CPU-GPU Hybrid Design NanoFlow: Towards Optimal Large Language Model Serving Throughput

Reference 59

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T07:27:44.453159Z

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 de9a7c98-b60b-4d12-a03c-e6320022e531 · inbound

SAC: Disaggregated KV Cache System for Sparse Attention LLMs with CXL cites this paper.

SAC: Disaggregated KV Cache System for Sparse Attention LLMs with CXL NanoFlow: Towards Optimal Large Language Model Serving Throughput

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T05:09:35.717356Z

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 0077e074-ec36-41aa-a8d5-339277276fe9 · inbound

Token-Operations-Oriented Inference Optimization Techniques for Large Models cites this paper.

Token-Operations-Oriented Inference Optimization Techniques for Large Models NanoFlow: Towards Optimal Large Language Model Serving Throughput

Reference 211

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T05:09:36.790508Z

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 7eb6445c-87dc-4b19-9caa-5794131b8b03 · inbound

Token-Operations-Oriented Inference Optimization Techniques for Large Models cites this paper.

Token-Operations-Oriented Inference Optimization Techniques for Large Models NanoFlow: Towards Optimal Large Language Model Serving Throughput

Reference 211

Resolution: unresolved; no resolver link, observed 2026-08-02T10:49:23.721737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e955080-a0f7-4840-b0ee-9e4bec337fac · inbound

Efficient Clustering with Provable Guardrails for LLM Inference at Scale cites this paper.

Efficient Clustering with Provable Guardrails for LLM Inference at Scale NanoFlow: Towards Optimal Large Language Model Serving Throughput

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-01T12:03:18.901949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.