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Paper Citation Record · LEDGER

Batch Prompting: Efficient Inference with Large Language Model APIs

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2301.08721.

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

pith.paper-citation-record.v1
2301.08721 v2

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 2026-08-16T06:30:59.297886+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:59:38.704939Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T22:34:24.187488Z

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 7084aeab-3df7-4e35-81ef-2ec4fe7bbceb · inbound

ReWOO: Decoupling Reasoning from Observations for Efficient Augmented Language Models cites this paper.

ReWOO: Decoupling Reasoning from Observations for Efficient Augmented Language Models Batch Prompting: Efficient Inference with Large Language Model APIs

Reference 42

Resolution
malformed identifier
arxiv_id, observed 2026-05-15T18:15:55.579424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-15T18:15:55.525596Z digest=sha256:6c07f64b2c215ba716d45456dc3500e5daee729f2c277066d733caca0aad0f71

Observation 74ed7e44-47f1-4bc6-ae90-1edde4585d15 · inbound

MAC-Tuning: LLM Multi-Compositional Problem Reasoning with Enhanced Knowledge Boundary Awareness cites this paper.

MAC-Tuning: LLM Multi-Compositional Problem Reasoning with Enhanced Knowledge Boundary Awareness Batch Prompting: Efficient Inference with Large Language Model APIs

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-16T04:59:38.704939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:59:38.704939Z digest=sha256:cc75ce7c387aba18138a3758aca4b362e3dd4a4271d48d411d41fffe16751558

Observation a0584331-f6f9-4d53-872d-dae2d6bb9602 · inbound

Tests as Prompt: A Test-Driven-Development Benchmark for LLM Code Generation cites this paper.

Tests as Prompt: A Test-Driven-Development Benchmark for LLM Code Generation Batch Prompting: Efficient Inference with Large Language Model APIs

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-15T21:47:07.610338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:47:07.610338Z digest=sha256:af5a9bafd712b283fc70703440c799b05972a72f560d08cf2f08250421378ddd

Observation 0a0004ad-4d77-4125-b298-0355ac986c19 · inbound

Can LLMs Replace Humans During Code Chunking? cites this paper.

Can LLMs Replace Humans During Code Chunking? Batch Prompting: Efficient Inference with Large Language Model APIs

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T23:10:14.989957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:10:14.989957Z digest=sha256:7e27485ae472204b3ad2305b27bad5829590c2a69cfe23ba765e6f6803b8bdd4

Observation 3ee0f25e-e6c4-41bd-87f2-755ce95ab77f · inbound

Access Paths for Efficient Ordering with Large Language Models cites this paper.

Access Paths for Efficient Ordering with Large Language Models Batch Prompting: Efficient Inference with Large Language Model APIs

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-21T22:34:24.189526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-21T22:32:23.352584Z digest=sha256:a8b4dcb6eb217c12eb4ad33bb17679a2dd479eb595db7926f6966f9289e80b31

Observation 8f857032-b4c5-4b60-bb82-890575dac240 · inbound

ONTO: A Token-Efficient Columnar Notation for LLM Input Optimization cites this paper.

ONTO: A Token-Efficient Columnar Notation for LLM Input Optimization Batch Prompting: Efficient Inference with Large Language Model APIs

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-10T09:23:37.778783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-10T05:21:56.826488Z digest=sha256:fcabeedc6d45b8c962721e2879896c2ed1c9ccf90147641d70a66f1fd4ea042c