Paper Citation Record · LEDGER

On Evaluating Performance of LLM Inference Serving Systems

As of 7 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 5 inbound Pith citation observations for arXiv:2507.09019.

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

pith.paper-citation-record.v1
2507.09019 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:11:16.388804Z

measured 17 of 17 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T15:10:12.647037Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T23:52:49.103329Z

Reference resolution

12 of 12 outbound references displayed

verified exact0
verified fuzzy1
unresolved10
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 28100343-384c-4f3d-b8fb-69ae1e05919f · outbound

This paper cites MuxServe: Flexible Spatial-Temporal Multiplexing for Multiple LLM Serving.

On Evaluating Performance of LLM Inference Serving Systems MuxServe: Flexible Spatial-Temporal Multiplexing for Multiple LLM Serving

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T18:11:15.829163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa5dc71d-861b-48c0-9a3a-05f55e5e1dc4 · outbound

This paper cites CacheGen: KV Cache Compression and Streaming for Fast Large Language Model Serving.

On Evaluating Performance of LLM Inference Serving Systems CacheGen: KV Cache Compression and Streaming for Fast Large Language Model Serving

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T18:11:15.906010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ebb2090-66ea-44ff-9cb0-72c5a1ba1f84 · outbound

This paper cites Mooncake: A KVCache-centric Disaggregated Architecture for LLM Serving.

On Evaluating Performance of LLM Inference Serving Systems Mooncake: A KVCache-centric Disaggregated Architecture for LLM Serving

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T18:11:15.969489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dde8cc21-f904-417b-b360-f882410d750e · outbound

This paper cites Guan Wang, Sijie Cheng, Xianyuan Zhan, Xiangang Li, Sen Song, and Yang Liu.

On Evaluating Performance of LLM Inference Serving Systems Guan Wang, Sijie Cheng, Xianyuan Zhan, Xiangang Li, Sen Song, and Yang Liu

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T18:11:16.246971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9182bd48-f2ae-424d-a307-cd01d9864f44 · outbound

This paper cites LoongServe: Efficiently Serving Long-Context Large Language Models with Elastic Sequence Parallelism.

On Evaluating Performance of LLM Inference Serving Systems LoongServe: Efficiently Serving Long-Context Large Language Models with Elastic Sequence Parallelism

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T18:11:16.254256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites NanoFlow: Towards Optimal Large Language Model Serving Throughput.

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 · outbound

This paper cites NanoFlow: Towards Optimal Large Language Model Serving Throughput.

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 a9a0e147-24c3-4da7-9214-a9280e669f1b · outbound

This paper cites Parameter T uning (✓) In our judgment, the baselines don’t need parameter tuning.

On Evaluating Performance of LLM Inference Serving Systems Parameter T uning (✓) In our judgment, the baselines don’t need parameter tuning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:11:16.740082Z

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 c5d486c1-2b71-4d34-973c-666392469670 · outbound

This paper cites S-LoRA: Serving Thousands of Concurrent LoRA Adapters.

On Evaluating Performance of LLM Inference Serving Systems S-LoRA: Serving Thousands of Concurrent LoRA Adapters

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-06T18:11:16.146190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6861722a-35ce-4626-ab63-0f76e1044013 · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

On Evaluating Performance of LLM Inference Serving Systems Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-06T18:11:16.045289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 284a4b5b-dfb1-44f0-a2bb-a24dd331d451 · outbound

This paper cites Accelerating Large Language Model Decoding with Speculative Sampling.

On Evaluating Performance of LLM Inference Serving Systems Accelerating Large Language Model Decoding with Speculative Sampling

Reference 2023

Resolution: malformed identifier; no resolver link, observed 2026-08-06T18:11:15.769967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9afccbaa-727d-41b4-8f2c-29152b6b8767 · outbound

This paper cites Efficient LLM Scheduling by Learning to Rank.

On Evaluating Performance of LLM Inference Serving Systems Efficient LLM Scheduling by Learning to Rank

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T18:11:15.858434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation d3452ba6-8358-48f7-8b0e-968225f2155d · inbound

Specification and Detection of LLM Code Smells cites this paper.

Specification and Detection of LLM Code Smells On Evaluating Performance of LLM Inference Serving Systems

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T15:10:12.647037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e853f491-9ddf-45e8-957b-e4d986b6e523 · inbound

CodeOCR: On the Effectiveness of Vision Language Models in Code Understanding cites this paper.

CodeOCR: On the Effectiveness of Vision Language Models in Code Understanding On Evaluating Performance of LLM Inference Serving Systems

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-16T08:32:36.437742Z

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 9ad232a9-fc3f-4fd8-b1f5-c2238c852d2a · inbound

Characterizing Performance-Energy Trade-offs of Large Language Models in Multi-Request Workflows cites this paper.

Characterizing Performance-Energy Trade-offs of Large Language Models in Multi-Request Workflows On Evaluating Performance of LLM Inference Serving Systems

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-15T12:30:00.285701Z

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 8598cbcc-8abd-43f3-973d-68d1c2d75d7f · inbound

SAGE: Selective Attention-Guided Extraction for Token-Efficient Document Indexing cites this paper.

SAGE: Selective Attention-Guided Extraction for Token-Efficient Document Indexing On Evaluating Performance of LLM Inference Serving Systems

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-10T08:32:52.126778Z

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 9f3aa297-b3ea-47f7-8508-e3d155580047 · inbound

RTP-LLM: High-Performance Alibaba LLM Inference Engine cites this paper.

RTP-LLM: High-Performance Alibaba LLM Inference Engine On Evaluating Performance of LLM Inference Serving Systems

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-06-28T23:52:49.104862Z

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.