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Paper Citation Record · LEDGER

Enabling Calibration In The Zero-Shot Inference of Large Vision-Language Models

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2303.12748.

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

pith.paper-citation-record.v1
2303.12748 v4

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 2026-08-10T15:24:42.271028Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T22:13:46.933698Z

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 9de05a0e-2fb9-4c1c-9d71-77166867c066 · inbound

SelfPrompt: Confidence-Aware Semi-Supervised Tuning for Robust Vision-Language Model Adaptation cites this paper.

SelfPrompt: Confidence-Aware Semi-Supervised Tuning for Robust Vision-Language Model Adaptation Enabling Calibration In The Zero-Shot Inference of Large Vision-Language Models

Reference 2013

Resolution
unresolved
no resolver link, observed 2026-08-10T15:24:42.271028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:24:42.271028Z digest=sha256:160cc47ca3d9d402c3ff6cd486837c46685c50bd9e9f0e3464b46e2a5112474e

Observation 73c17108-190e-4d7c-aa90-7f6360a2d78f · inbound

Interpretable Failure Detection with Human-Level Concepts cites this paper.

Interpretable Failure Detection with Human-Level Concepts Enabling Calibration In The Zero-Shot Inference of Large Vision-Language Models

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-08T20:00:02.343363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:00:02.343363Z digest=sha256:4a2bb878031b3f26341120b57e996e3e8c65c6a6074563f402031bb7182d0ef2

Observation 773bbd09-4484-4218-be89-fefda40de718 · inbound

Prompting without Panic: Attribute-aware, Zero-shot, Test-Time Calibration cites this paper.

Prompting without Panic: Attribute-aware, Zero-shot, Test-Time Calibration Enabling Calibration In The Zero-Shot Inference of Large Vision-Language Models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-06T22:04:42.107573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:04:42.107573Z digest=sha256:6ebf43ad63701eb003eeba7598679e0520a5b3cd45219d1b607e47bb8f09dc75

Observation dced7f5c-923d-41a1-8534-89eecc32b5c7 · inbound

RubricRefine: Improving Tool-Use Agent Reliability with Training-Free Pre-Execution Refinement cites this paper.

RubricRefine: Improving Tool-Use Agent Reliability with Training-Free Pre-Execution Refinement Enabling Calibration In The Zero-Shot Inference of Large Vision-Language Models

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:11:26.641897Z

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=2026-05-12T03:37:09.000442Z digest=sha256:3c866da8d917b0945c4edb33de4128150b89550c18317f9b74ccbd8daf61ddf4

Observation bb8d0319-e50c-49d0-acd0-d372645421b2 · inbound

RubricRefine: Improving Tool-Use Agent Reliability with Training-Free Pre-Execution Refinement cites this paper.

RubricRefine: Improving Tool-Use Agent Reliability with Training-Free Pre-Execution Refinement Enabling Calibration In The Zero-Shot Inference of Large Vision-Language Models

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-15T05:29:47.941793Z

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=2026-05-15T05:25:43.890367Z digest=sha256:65e51b8d4cdd99c23f1a187287849988409a4865a8d795056d01e9d23e2b3604

Observation 2265549c-5571-4181-8322-96506af50edf · inbound

RubricRefine: Improving Tool-Use Agent Reliability with Training-Free Pre-Execution Refinement cites this paper.

RubricRefine: Improving Tool-Use Agent Reliability with Training-Free Pre-Execution Refinement Enabling Calibration In The Zero-Shot Inference of Large Vision-Language Models

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:13:46.938183Z

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=2026-05-20T22:12:23.680155Z digest=sha256:acf3c2b1ed02380812833defcfac9776231edc23794af289ca51979963c34961