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Paper Citation Record · LEDGER

LP-Spec: Leveraging LPDDR PIM for Efficient LLM Mobile Speculative Inference with Architecture-Dataflow Co-Optimization

As of 23 August 2026, this Paper Citation Record lists 1 of 1 outbound references and 6 inbound Pith citation observations for arXiv:2508.07227.

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

pith.paper-citation-record.v1
2508.07227 v3

Coverage vector

measured 1 of 1 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:17:46.781173Z

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:17:46.781173Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T07:35:28.747502Z

Reference resolution

1 of 1 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 73489d65-e951-4f7c-9b3c-24bc0b69b6af · outbound

This paper cites LP-Spec: Leveraging LPDDR PIM for Efficient LLM Mobile Speculative Inference with Architecture-Dataflow Co-Optimization.

LP-Spec: Leveraging LPDDR PIM for Efficient LLM Mobile Speculative Inference with Architecture-Dataflow Co-Optimization LP-Spec: Leveraging LPDDR PIM for Efficient LLM Mobile Speculative Inference with Architecture-Dataflow Co-Optimization

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-05T22:17:46.781173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:17:46.781173Z digest=sha256:d9f3a052af5e103768f9171cd9231c7683da4c6ffa23d18490db9347fce853fa

Pith citing papers

Observation 73489d65-e951-4f7c-9b3c-24bc0b69b6af · inbound

LP-Spec: Leveraging LPDDR PIM for Efficient LLM Mobile Speculative Inference with Architecture-Dataflow Co-Optimization cites this paper.

LP-Spec: Leveraging LPDDR PIM for Efficient LLM Mobile Speculative Inference with Architecture-Dataflow Co-Optimization LP-Spec: Leveraging LPDDR PIM for Efficient LLM Mobile Speculative Inference with Architecture-Dataflow Co-Optimization

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-05T22:17:46.781173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:17:46.781173Z digest=sha256:d9f3a052af5e103768f9171cd9231c7683da4c6ffa23d18490db9347fce853fa

Observation e7dbf547-c60b-422e-872a-cc64c4858b35 · inbound

DCC: Data-Centric Compilation of Machine Learning Kernels for Processing-In-Memory Architectures cites this paper.

DCC: Data-Centric Compilation of Machine Learning Kernels for Processing-In-Memory Architectures LP-Spec: Leveraging LPDDR PIM for Efficient LLM Mobile Speculative Inference with Architecture-Dataflow Co-Optimization

Reference 60

Resolution
verified exact
arxiv_id, observed 2026-05-25T07:35:28.750923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-25T07:33:14.330957Z digest=sha256:1a0d322978a2a46d9e6e0c5bd235d2ddee241cc9bf4e5031d2781aa90837c29e

Observation b98d2f22-d34b-4b61-9f13-68cd8426cf27 · inbound

DCC: Data-Centric Compilation of Machine Learning Kernels for Processing-In-Memory Architectures cites this paper.

DCC: Data-Centric Compilation of Machine Learning Kernels for Processing-In-Memory Architectures LP-Spec: Leveraging LPDDR PIM for Efficient LLM Mobile Speculative Inference with Architecture-Dataflow Co-Optimization

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-03T21:25:18.192583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T21:25:18.192583Z digest=sha256:d3329c140b59a6a88c7ab6d8f2bdde78ce8e69f761ee0b30b5bb2c28ba2f811f

Observation 04f7a272-f590-49a9-ad94-0a1e15c2c138 · inbound

DCC: Data-Centric Compilation of Machine Learning Kernels for Processing-In-Memory Architectures cites this paper.

DCC: Data-Centric Compilation of Machine Learning Kernels for Processing-In-Memory Architectures LP-Spec: Leveraging LPDDR PIM for Efficient LLM Mobile Speculative Inference with Architecture-Dataflow Co-Optimization

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-04T06:48:39.044499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:48:39.044499Z digest=sha256:cf522165580974c8361b38dd049a06dde57def65adc91edf698f6c43dd1323ac

Observation 0160d136-5218-44bd-b5e7-bc144b3ae529 · inbound

TokenStack: A Heterogeneous HBM-PIM Architecture and Runtime for Efficient LLM Inference cites this paper.

TokenStack: A Heterogeneous HBM-PIM Architecture and Runtime for Efficient LLM Inference LP-Spec: Leveraging LPDDR PIM for Efficient LLM Mobile Speculative Inference with Architecture-Dataflow Co-Optimization

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-11T21:36:18.213506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-08T04:43:41.912918Z digest=sha256:d3ba1b48eddfb5deb2db7101e34502a1379e06a3b5ec35d073082c6c03f647a3

Observation b5af5529-7805-41fd-8bed-8300b481a626 · inbound

Is Your NPU Ready for LLMs? Dissecting the Hidden Efficiency Bottlenecks in Mobile LLM Inference cites this paper.

Is Your NPU Ready for LLMs? Dissecting the Hidden Efficiency Bottlenecks in Mobile LLM Inference LP-Spec: Leveraging LPDDR PIM for Efficient LLM Mobile Speculative Inference with Architecture-Dataflow Co-Optimization

Reference 49

Resolution
unresolved
no resolver link, observed 2026-07-11T12:14:57.342551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T12:14:57.342551Z digest=sha256:7a8c29f9506d13770998bab7938e27906c4c5b884505a7056fa461deebce54f5