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Paper Citation Record · LEDGER

Accuracy is Not All You Need

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2407.09141.

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

pith.paper-citation-record.v1
2407.09141 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T14:11:08.501659Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T16:25:49.793833Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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 440c5def-e338-4dbd-9525-9723b82b009e · inbound

Weight Pruning Amplifies Bias: A Multi-Method Study of Compressed LLMs for Edge AI cites this paper.

Weight Pruning Amplifies Bias: A Multi-Method Study of Compressed LLMs for Edge AI Accuracy is Not All You Need

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-12T02:51:17.638728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-12T02:50:17.302744Z digest=sha256:41554a7ae99e058bffe87b689cb9240a585a33ea9a47009651e5d4677561d7b9

Observation 0f1e3dc1-6919-4ef8-9d56-4592b38885cf · inbound

Quantization Undoes Alignment: Bias Emergence in Compressed LLMs Across Models and Precision Levels cites this paper.

Quantization Undoes Alignment: Bias Emergence in Compressed LLMs Across Models and Precision Levels Accuracy is Not All You Need

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-19T17:57:42.525569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-19T17:55:35.764347Z digest=sha256:28f0b7582afa28c15976343b36c5922ca9c8c23585624fcf24ac03c03bae1e51

Observation b78facdd-f7c4-4af8-8ffd-89a3652fa00c · inbound

Cassandra: Enabling Reasoning LLMs at Edge via Self-Speculative Decoding cites this paper.

Cassandra: Enabling Reasoning LLMs at Edge via Self-Speculative Decoding Accuracy is Not All You Need

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-07-01T16:25:49.795262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-07-01T16:19:54.910430Z digest=sha256:4c30fb3ea79156882c9fd0c33dce92c3883ddd1dfb615ade7fa4f51990122882

Observation 9d004b53-0b49-480b-ab1b-681f1022046d · inbound

Variable Bit-width Quantization: Learning Per-Group Precision for "Bigger-but-Smaller" Language Models cites this paper.

Variable Bit-width Quantization: Learning Per-Group Precision for "Bigger-but-Smaller" Language Models Accuracy is Not All You Need

Reference 10

Resolution
unresolved
no resolver link, observed 2026-07-12T06:20:07.112455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T06:20:07.112455Z digest=sha256:d6f5fd1c3889191ee93e480c3545af7c1942bcf43aaca136383bb854a5e5152f

Observation 226d6b61-c446-4243-a378-67f3159a5caf · inbound

Reliability Scaling Laws for Quantized Large Language Models cites this paper.

Reliability Scaling Laws for Quantized Large Language Models Accuracy is Not All You Need

Reference 74

Resolution
unresolved
no resolver link, observed 2026-07-14T08:45:52.855783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T08:45:52.855783Z digest=sha256:116d3c397b9125c9dbd7f75d316aed92f0050d8c72a65bd675c4b93f6621b75f

Observation b52f2067-7f30-41f7-b43a-93d9acdc4c1a · inbound

HindsightBench: A Black-Box Behavioral Audit Protocol for Parametric Hindsight in Time-Indexed LLM Decision Tasks cites this paper.

HindsightBench: A Black-Box Behavioral Audit Protocol for Parametric Hindsight in Time-Indexed LLM Decision Tasks Accuracy is Not All You Need

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-01T14:11:08.501659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:11:08.501659Z digest=sha256:9b96835c4a08ba5e20e608600d0d55ff19a9d4a546d5a3382e976787246ade00