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Paper Citation Record · LEDGER

Agentic AI-Driven Technical Troubleshooting for Enterprise Systems: A Novel Weighted Retrieval-Augmented Generation Paradigm

As of 14 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2412.12006.

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

pith.paper-citation-record.v1
2412.12006 v2

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:25:38.563676Z

measured 14 of 14 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

14 of 14 outbound references displayed

  • verified exact0
  • verified fuzzy3
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e8216082-2c00-410a-9da9-e208479c4379 · outbound

This paper cites E., Walker, S., Jones, S., Hancock-Beaulieu , M., & Gatford, M.

Agentic AI-Driven Technical Troubleshooting for Enterprise Systems: A Novel Weighted Retrieval-Augmented Generation Paradigm E., Walker, S., Jones, S., Hancock-Beaulieu , M., & Gatford, M

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:25:38.677035Z

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.

source=pdf_text observed=2026-08-11T14:25:38.526864Z digest=sha256:f4139972b5e843ccf62131bbe181d7b257cece01f2e1d9d73617ee44d4d8b431

Observation c0133878-584a-4e63-b45c-85831b522d1a · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Agentic AI-Driven Technical Troubleshooting for Enterprise Systems: A Novel Weighted Retrieval-Augmented Generation Paradigm BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-11T14:25:38.530559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:25:38.530559Z digest=sha256:30c428c8af5245d63df79bd4a86b15742bc2113027e43836130fffb749b34940

Observation 0364d475-cd95-4c12-b5e3-7280912ce46c · outbound

This paper cites MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers.

Agentic AI-Driven Technical Troubleshooting for Enterprise Systems: A Novel Weighted Retrieval-Augmented Generation Paradigm MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-11T14:25:38.533403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:25:38.533403Z digest=sha256:d44fdaa3585697027fa2754c0480ba643fbaeeede2740c67afd7a8b87e1b7ca0

Observation 9c1cc2a7-b4bd-409b-a842-dcc594a44fe1 · outbound

This paper cites Billion-scale similarity search with GPUs.

Agentic AI-Driven Technical Troubleshooting for Enterprise Systems: A Novel Weighted Retrieval-Augmented Generation Paradigm Billion-scale similarity search with GPUs

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-11T14:25:38.536358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:25:38.536358Z digest=sha256:45cf32fa39c0cf058c039363bbaafbb338d1df0c077d84d7b5af4ec707b43659

Observation 09a60544-2ec5-42b1-939a-793f35517052 · outbound

This paper cites an unresolved cited work.

Agentic AI-Driven Technical Troubleshooting for Enterprise Systems: A Novel Weighted Retrieval-Augmented Generation Paradigm Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-11T14:25:38.668800Z

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.

source=pdf_text observed=2026-08-11T14:25:38.539182Z digest=sha256:9fb49ebbe97018caf871019dee6fa3d1cfb8ef1170e7a774830214b66cd3cf95

Observation 94c7b8d4-8dd7-48e1-bb50-79ed070cec15 · outbound

This paper cites B., Mann, B., Ryder, N., et al.

Agentic AI-Driven Technical Troubleshooting for Enterprise Systems: A Novel Weighted Retrieval-Augmented Generation Paradigm B., Mann, B., Ryder, N., et al

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:25:38.661319Z

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.

source=pdf_text observed=2026-08-11T14:25:38.542050Z digest=sha256:5f7982c9e448c23d0fd9d46458388a1f472a8dba290b328603819f2cba8f6990

Observation aa58b931-dabf-4001-a54e-7b389db084c2 · outbound

This paper cites Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.

Agentic AI-Driven Technical Troubleshooting for Enterprise Systems: A Novel Weighted Retrieval-Augmented Generation Paradigm Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-11T14:25:38.544838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:25:38.544838Z digest=sha256:86c6974b1c3dc2cf6b0f33b7102bdc027df2f55c588c246294401cd2f13646e0

Observation 3d44665a-88a5-43b7-9986-4aa2b9580b3d · outbound

This paper cites Dense Passage Retrieval for Open-Domain Question Answering.

Agentic AI-Driven Technical Troubleshooting for Enterprise Systems: A Novel Weighted Retrieval-Augmented Generation Paradigm Dense Passage Retrieval for Open-Domain Question Answering

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-11T14:25:38.547845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:25:38.547845Z digest=sha256:06c304aaee093a22bc7fc37ec526a0f62ddc141fd944ada7ad488e7b9a6fb5d5

Observation f972222a-1935-4b8e-a5a9-6977307aee96 · outbound

This paper cites an unresolved cited work.

Agentic AI-Driven Technical Troubleshooting for Enterprise Systems: A Novel Weighted Retrieval-Augmented Generation Paradigm Unresolved cited work

Reference 9

Resolution
unresolved
raw_fallback, observed 2026-08-11T14:25:38.653543Z

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.

source=pdf_text observed=2026-08-11T14:25:38.550704Z digest=sha256:acde65ff8e2a8abaa88012f6788842d3c399f1179b7bc87a110574743423afb3

Observation c277862f-a8f1-4094-920d-ff05b2ca1116 · outbound

This paper cites Self-Taught Evaluators.

Agentic AI-Driven Technical Troubleshooting for Enterprise Systems: A Novel Weighted Retrieval-Augmented Generation Paradigm Self-Taught Evaluators

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-11T14:25:38.553228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:25:38.553228Z digest=sha256:dfef05fdf58e3d8eb0c1eec2d872bd072b9a73d72300f4be615a1085f0fd99d0

Observation 0dab2e9f-2cb7-4fa1-b890-a7dc93e44d18 · outbound

This paper cites Optimizing Query Generation for Enhanced Document Retrieval in RAG.

Agentic AI-Driven Technical Troubleshooting for Enterprise Systems: A Novel Weighted Retrieval-Augmented Generation Paradigm Optimizing Query Generation for Enhanced Document Retrieval in RAG

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-11T14:25:38.556024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:25:38.556024Z digest=sha256:02f8fa98494e10a0dd9e1a23da5ba49a38e61f1ae4717396346b8a41eb2746a2

Observation a4230a81-33ee-492e-b264-38a441497128 · outbound

This paper cites A BERT Baseline for the Natural Questions.

Agentic AI-Driven Technical Troubleshooting for Enterprise Systems: A Novel Weighted Retrieval-Augmented Generation Paradigm A BERT Baseline for the Natural Questions

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-11T14:25:38.558656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:25:38.558656Z digest=sha256:ecedd34807f4a6ffafaf2a9651995f904f7734d7c631cea0e72c496e2615c491

Observation c8cb4071-99bc-4be7-9554-41fb0edff46e · outbound

This paper cites N., Jones, L., Chang, M., Dai, A., Uszkoreit, J., Le, Q., & Petrov, S.

Agentic AI-Driven Technical Troubleshooting for Enterprise Systems: A Novel Weighted Retrieval-Augmented Generation Paradigm N., Jones, L., Chang, M., Dai, A., Uszkoreit, J., Le, Q., & Petrov, S

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:25:38.645605Z

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.

source=pdf_text observed=2026-08-11T14:25:38.561340Z digest=sha256:e1e102bac1b25903981bb591cd7e15e1272fca1c5e01d8e9dbb9f835a3daecdf

Observation e6b081df-6b45-4413-bdab-7f5d6f2bc7c8 · outbound

This paper cites an unresolved cited work.

Agentic AI-Driven Technical Troubleshooting for Enterprise Systems: A Novel Weighted Retrieval-Augmented Generation Paradigm Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-08-11T14:25:38.636685Z

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.

source=pdf_text observed=2026-08-11T14:25:38.563676Z digest=sha256:96d8df44062cd4f3e0e72f492e08178cfafc2077ff1bbe4c92247068adb8ca9b

Pith citing papers

No inbound Pith citation observations are available.