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Paper Citation Record · LEDGER

BLADE: Enhancing Black-box Large Language Models with Small Domain-Specific Models

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2403.18365.

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

pith.paper-citation-record.v1
2403.18365 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 2026-08-17T06:30:58.91139+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:44:46.637637Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T19:08:53.912216Z

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 aea06b71-c147-48bd-b617-ce29827cde7a · inbound

LegalAgentBench: Evaluating LLM Agents in Legal Domain cites this paper.

LegalAgentBench: Evaluating LLM Agents in Legal Domain BLADE: Enhancing Black-box Large Language Models with Small Domain-Specific Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-11T05:43:30.995851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:43:30.995851Z digest=sha256:5b38f19b502cf303d41d236cf6b976e51601c510c25cda8af10b84d707da1dd0

Observation 236f4df2-8587-4123-8364-636c7759d3af · inbound

Foundations of GenIR cites this paper.

Foundations of GenIR BLADE: Enhancing Black-box Large Language Models with Small Domain-Specific Models

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.028210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.028210Z digest=sha256:4044e61cda8dcc223e5d77e7c57cd55705289abbc53ab5796b3c0bc85d2339c4

Observation 266fc36d-8068-40d6-b1d9-be4a37452f4f · inbound

Towards Harnessing the Collaborative Power of Large and Small Models for Domain Tasks cites this paper.

Towards Harnessing the Collaborative Power of Large and Small Models for Domain Tasks BLADE: Enhancing Black-box Large Language Models with Small Domain-Specific Models

Reference 148

Resolution
unresolved
no resolver link, observed 2026-08-16T10:44:46.637637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:44:46.637637Z digest=sha256:c296e2ce61a5da108d008ae3d3c8f6583dbfc7d707dd742bba41b29f0ae07702

Observation d2089229-b190-428e-a234-7b3d34aeaba7 · inbound

AI Agents for Conversational Patient Triage: Preliminary Simulation-Based Evaluation with Real-World EHR Data cites this paper.

AI Agents for Conversational Patient Triage: Preliminary Simulation-Based Evaluation with Real-World EHR Data BLADE: Enhancing Black-box Large Language Models with Small Domain-Specific Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T10:54:38.196663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:54:38.196663Z digest=sha256:73d7f99aab896cdacd6b17f8dbb9fea400b05dc6510920c7fc75335d50c37a8b

Observation cf47fdff-9059-4797-aba7-7360d97e7e59 · inbound

Exploring Task Performance with Interpretable Models via Sparse Auto-Encoders cites this paper.

Exploring Task Performance with Interpretable Models via Sparse Auto-Encoders BLADE: Enhancing Black-box Large Language Models with Small Domain-Specific Models

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-08-06T19:08:54.009071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-06T19:08:49.414283Z digest=sha256:359e580d4714c712613decb6b1b38ee0a3369bb3efe4d367e52e9e5d9fbf887a

Observation 07765743-dc68-461a-afd3-823c9bd0b019 · inbound

Large Language Models Meet Legal Artificial Intelligence: A Survey cites this paper.

Large Language Models Meet Legal Artificial Intelligence: A Survey BLADE: Enhancing Black-box Large Language Models with Small Domain-Specific Models

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-04T18:26:14.206564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T18:26:14.206564Z digest=sha256:334f833072195191abe02f0c86e382ae9c820a126209ced9d12613674c0d0b88