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Paper Citation Record · LEDGER

Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2309.17249.

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

pith.paper-citation-record.v1
2309.17249 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:08:40.291059Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T07:23:13.334902Z

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 a67835a9-ec3e-43ae-8b8e-adb283d06fbb · inbound

CausalAbstain: Enhancing Multilingual LLMs with Causal Reasoning for Trustworthy Abstention cites this paper.

CausalAbstain: Enhancing Multilingual LLMs with Causal Reasoning for Trustworthy Abstention Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T12:08:40.291059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:08:40.291059Z digest=sha256:0100dfad0b1f8d9ee4ea797b15a7456a22c1d751c85f5ba7bc8f366be744d3b8

Observation dd0a2572-3b13-4d5e-b6f6-63bb63c60d06 · inbound

Surprise Calibration for Better In-Context Learning cites this paper.

Surprise Calibration for Better In-Context Learning Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T00:49:40.146988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:49:40.146988Z digest=sha256:9be102b558643732a8b8db7b5410c7ffcdc415e42e1042bf172e767fbbe6b9e4

Observation f5ead71a-a5d4-4e41-9921-12f9e18eb20a · inbound

From Words to Widgets for Controllable LLM Generation cites this paper.

From Words to Widgets for Controllable LLM Generation Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering

Reference 59

Resolution
verified exact
arxiv_id, observed 2026-05-11T08:45:59.221524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T16:30:39.143556Z digest=sha256:e85e9b9f37ed470cc7ea99d61888bd8a902ecadd32e35c4189037946649f13a4

Observation b5b2ad1e-3129-4425-9e40-d1010b402a79 · inbound

From Words to Widgets for Controllable LLM Generation cites this paper.

From Words to Widgets for Controllable LLM Generation Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering

Reference 59

Resolution
unresolved
no resolver link, observed 2026-07-14T19:46:03.847368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T19:46:03.847368Z digest=sha256:053a595e7fffe24482048fec0eae84718ba0f95205b424d1520dfd4959838c6b

Observation 63b9c43d-4894-4cb6-b2a1-79b8321ad539 · inbound

Harnessing non-adversarial robustness in large language models cites this paper.

Harnessing non-adversarial robustness in large language models Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-06-29T07:23:13.336581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-29T07:13:15.149708Z digest=sha256:cbe5a659a13a4bc01b0dbe160186b5eb24d55232b415982cd389dec0eccaff26

Observation a3b6951e-00db-42f4-ba82-794999956623 · inbound

Probabilistic Concept-Aware Steering for Trustworthy LLM Inference cites this paper.

Probabilistic Concept-Aware Steering for Trustworthy LLM Inference Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-02T13:56:50.725313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T13:56:50.725313Z digest=sha256:614e122403ea84b423da51ff46ce038f60d9ea0932fae363936b52b11a8ab540

Observation 62b1917c-548b-450f-96ae-fcb8dc5fefac · inbound

Lost in Context: Addressing Context Anxiety in Large Language Models cites this paper.

Lost in Context: Addressing Context Anxiety in Large Language Models Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-02T12:47:58.423957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T12:47:58.423957Z digest=sha256:2a6bffb01e5d3ed31285768a5572406110ed50f29129a08c9d7c3589d243d86d