Paper Citation Record · LEDGER

Forecasting LLM Inference Performance via Hardware-Agnostic Analytical Modeling

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2508.00904.

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

pith.paper-citation-record.v1
2508.00904 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:30:17.313864Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T23:19:03.318032Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 963fd96e-063e-45d4-8d5c-49b5fc406e8b · inbound

Mapping Stakeholder Needs to Multi-Sided Fairness in Candidate Recommendation for Algorithmic Hiring cites this paper.

Mapping Stakeholder Needs to Multi-Sided Fairness in Candidate Recommendation for Algorithmic Hiring Forecasting LLM Inference Performance via Hardware-Agnostic Analytical Modeling

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T12:30:17.313864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae773193-da29-4fe0-b64d-c2232310251a · inbound

Recover-LoRA for Aggressive Quantization: Reclaiming Accuracy in 2-Bit Language Models via Low-Rank Adaptation with Knowledge Distillation on Synthetic Data cites this paper.

Recover-LoRA for Aggressive Quantization: Reclaiming Accuracy in 2-Bit Language Models via Low-Rank Adaptation with Knowledge Distillation on Synthetic Data Forecasting LLM Inference Performance via Hardware-Agnostic Analytical Modeling

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-07-02T02:46:28.220672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation da74e49e-e797-4be7-9104-19f4161aaf68 · inbound

Latency Prediction for LLM Inference on NPU Systems cites this paper.

Latency Prediction for LLM Inference on NPU Systems Forecasting LLM Inference Performance via Hardware-Agnostic Analytical Modeling

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-07-03T23:19:03.320800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 712fe5e4-e43d-4265-bca8-6a5eaf630904 · inbound

WattGPU: Predicting Inference Power and Latency on Unseen GPUs and LLMs cites this paper.

WattGPU: Predicting Inference Power and Latency on Unseen GPUs and LLMs Forecasting LLM Inference Performance via Hardware-Agnostic Analytical Modeling

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-03T05:47:40.837796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 646c96d2-7810-4f44-bece-ab627e554d35 · inbound

FastTPS: An Optimized Method for LLM Token Phase for AI accelerators cites this paper.

FastTPS: An Optimized Method for LLM Token Phase for AI accelerators Forecasting LLM Inference Performance via Hardware-Agnostic Analytical Modeling

Reference 33

Resolution: unresolved; no resolver link, observed 2026-07-14T06:16:09.070414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e0c4e50-8999-48f0-9df5-1c39d60135f3 · inbound

Leaky Language Models: Stealing Architecture and Inference Optimizations via Per-Token Timing cites this paper.

Leaky Language Models: Stealing Architecture and Inference Optimizations via Per-Token Timing Forecasting LLM Inference Performance via Hardware-Agnostic Analytical Modeling

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-01T09:35:57.546394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 698ecdc0-510d-4e08-b85b-71d6fdff1ccc · inbound

TileSight: A First-Principles Tile-Centric Analytical GPU Performance Model from Cores to Clusters cites this paper.

TileSight: A First-Principles Tile-Centric Analytical GPU Performance Model from Cores to Clusters Forecasting LLM Inference Performance via Hardware-Agnostic Analytical Modeling

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-01T04:49:47.995962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.