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Paper Citation Record · LEDGER

Bridging Interpretability and Robustness Using LIME-Guided Model Refinement

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2412.18952.

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

pith.paper-citation-record.v1
2412.18952 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T16:41:06.246606Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T15:47:23.204411Z

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 fc88bb5e-57f7-4d73-b767-021850e64cc1 · inbound

Analyzing Fairness of Computer Vision and Natural Language Processing Models cites this paper.

Analyzing Fairness of Computer Vision and Natural Language Processing Models Bridging Interpretability and Robustness Using LIME-Guided Model Refinement

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-11T16:41:06.246606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T16:41:06.246606Z digest=sha256:01d62eeb2eb77687a09643959d1eba5f0fc45812d9d054d1897ec7c5a307b8e7

Observation daa13812-8fc3-4a8b-8efd-6933f9b9f083 · inbound

Explainable Novel Category Discovery in Semantic Concept Space cites this paper.

Explainable Novel Category Discovery in Semantic Concept Space Bridging Interpretability and Robustness Using LIME-Guided Model Refinement

Reference 12

Resolution
unresolved
no resolver link, observed 2026-07-11T17:32:24.547251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T17:32:24.547251Z digest=sha256:99167f56566784590adca739d58568c7858d88a5c3ac96606aeaaeea7041e6d5

Observation 1b58cf5e-ea7b-4e69-8c94-62bf1c701a03 · inbound

Mechanistic Interpretability of LLM Jailbreaks via Internal Attribution Graphs cites this paper.

Mechanistic Interpretability of LLM Jailbreaks via Internal Attribution Graphs Bridging Interpretability and Robustness Using LIME-Guided Model Refinement

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-07-10T15:47:23.205521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-07-10T15:42:46.392593Z digest=sha256:446824a363a8794d728d31ea7fb346f067aa809e20d95c325ce856b9501956b6

Observation 109a6632-d89e-494b-b2a4-75a58f1c3e0a · inbound

Learning to Transmit: Volatility-Aware Predictive Communication for Energy-Efficient IoT Networks cites this paper.

Learning to Transmit: Volatility-Aware Predictive Communication for Energy-Efficient IoT Networks Bridging Interpretability and Robustness Using LIME-Guided Model Refinement

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-01T12:21:51.914461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:21:51.914461Z digest=sha256:c67aea64070d874e5d35675d255d359d619d3b2232b7bf6e7f854988ac4d355f

Observation ab4b7cd1-98af-4c8b-86b5-c5fb39433cfc · inbound

Grad-CAM for Vision Transformers: A Systematic Taxonomy and Audit of Methodological Ambiguity in Explainable AI cites this paper.

Grad-CAM for Vision Transformers: A Systematic Taxonomy and Audit of Methodological Ambiguity in Explainable AI Bridging Interpretability and Robustness Using LIME-Guided Model Refinement

Reference 266

Resolution
unresolved
no resolver link, observed 2026-08-08T16:59:12.012886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T16:59:12.012886Z digest=sha256:4a418e00944eec310955da401517c6c4de642fc1767682940a5401ad8ac8f8b9