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Paper Citation Record · LEDGER

Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2308.00675.

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

pith.paper-citation-record.v1
2308.00675 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:59:03.549295Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

9
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a55d8fee-3d8d-4d72-b278-8894a5f5ec6e · inbound

A Comprehensive Overview of Large Language Models cites this paper.

A Comprehensive Overview of Large Language Models Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

Reference 218

Resolution
verified exact
arxiv_id, observed 2026-05-19T20:32:45.599451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-19T20:28:38.900026Z digest=sha256:95317f15fa1eaa0617744a13fa952fca4c599779616dac26caa956097389457e

Observation 0a73dafa-4d5d-4f08-b440-36c1e563e015 · inbound

Bridging Language Models and Financial Analysis cites this paper.

Bridging Language Models and Financial Analysis Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-23T01:12:21.008074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-23T01:08:58.528533Z digest=sha256:683d903bf4efaf08abbda647d17deaa0a147d615b951fb76cefc674eebfd6613

Observation 891f559a-d704-4351-86c8-8344bece7880 · inbound

CODEMENV: Benchmarking Large Language Models on Code Migration cites this paper.

CODEMENV: Benchmarking Large Language Models on Code Migration Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T11:59:03.549295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:59:03.549295Z digest=sha256:0ac09bab7b6a0d767f75a28328aabc85477e2c938129ed32d1830c6925b2d145

Observation 57efea24-4caf-4dab-a0bd-6d95e2794cca · inbound

ASPERA: A Simulated Environment to Evaluate Planning for Complex Action Execution cites this paper.

ASPERA: A Simulated Environment to Evaluate Planning for Complex Action Execution Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T15:34:30.167233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:34:30.167233Z digest=sha256:b3974cf62773d304918d573d3658f165b67332e87cc7c426bc100bc83a505203

Observation ee6ba036-1b19-43eb-b496-43c18e9716e1 · inbound

From REST to MCP: An Empirical Study of API Wrapping and Automated Server Generation for LLM Agents cites this paper.

From REST to MCP: An Empirical Study of API Wrapping and Automated Server Generation for LLM Agents Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-19T03:27:01.199190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-19T03:24:00.804285Z digest=sha256:59da5bc21804efc7132e63c17d6f3ff2d6c8d1338a3be75f0928a3ce51148071

Observation fcee05e0-2bca-4e21-a978-d0b43612fd93 · inbound

Augmented Vision-Language Models: A Systematic Review cites this paper.

Augmented Vision-Language Models: A Systematic Review Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T14:33:33.565983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:33:33.565983Z digest=sha256:3b6e49e6c513639aeec086ef0171bb71ac8d327a4f7c8dad09293e5872f033eb

Observation 0bdaea96-8c3d-40f9-9a73-9a3cfd1a0c6f · inbound

ReQuestNet: A Foundational Learning model for Channel Estimation cites this paper.

ReQuestNet: A Foundational Learning model for Channel Estimation Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-05T21:24:03.314790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:24:03.314790Z digest=sha256:8400fdddf457bf5a5e915be23da7e6871298c4abc24def3dc6f744e537763450

Observation 55687e44-0335-4f2a-8f4a-b8aba726815b · inbound

ReQuestNet: A Foundational Learning model for Channel Estimation cites this paper.

ReQuestNet: A Foundational Learning model for Channel Estimation Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-05T21:24:03.386564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:24:03.386564Z digest=sha256:0b534740a2682b1078cd0fdba6332fba20074f0499bb483320cdac7afe69d5c4

Observation c77928b7-a854-44e7-8ef1-15cf9762ff06 · inbound

Feedback-Driven Tool-Use Improvements in Large Language Models via Automated Build Environments cites this paper.

Feedback-Driven Tool-Use Improvements in Large Language Models via Automated Build Environments Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-18T23:56:55.244152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T23:53:41.256273Z digest=sha256:d0aee51a361385172fe1a6faeaa02c790f5f1b9adf96543b50c9462d3ddd8344

Observation 13156922-a65d-422f-aa14-74db84b10448 · inbound

Feedback-Driven Tool-Use Improvements in Large Language Models via Automated Build Environments cites this paper.

Feedback-Driven Tool-Use Improvements in Large Language Models via Automated Build Environments Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

Reference 17

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T23:56:54.921074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T23:53:41.256273Z digest=sha256:534af37453086632ad55d7ace05eee4d9204fc70550ea7d7bda155827d70822c

Observation 21552fc6-285a-49c7-8477-c3e9c0d7ec92 · inbound

Extended Version: It Should Be Easy but... New Users Experiences and Challenges with Secret Management Tools cites this paper.

Extended Version: It Should Be Easy but... New Users Experiences and Challenges with Secret Management Tools Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-04T19:50:49.946691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:50:49.946691Z digest=sha256:dea38ac83930532c80f3015228d3bd4ef4dd40b25034d9fb0e005dd6d417b182

Observation 46132497-abed-4945-ab06-8561e81a549b · inbound

Agentic Reasoning for Large Language Models cites this paper.

Agentic Reasoning for Large Language Models Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

Reference 215

Resolution
verified exact
arxiv_id, observed 2026-05-17T15:14:26.246439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-17T15:14:25.558878Z digest=sha256:b1bc9b2caa555dad9865296259f24a5ef731e7c65d29dee0f6eea04f3da6b9fb

Observation 862e632c-8385-4a6f-a993-1489f8877df2 · inbound

Model Context Protocol (MCP) Tool Descriptions Are Smelly! Towards Improving AI Agent Efficiency with Augmented MCP Tool Descriptions cites this paper.

Model Context Protocol (MCP) Tool Descriptions Are Smelly! Towards Improving AI Agent Efficiency with Augmented MCP Tool Descriptions Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-02T23:04:30.321592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:04:30.321592Z digest=sha256:4b5aed47e6417d2fdfc7f96067568836f550d9dbe96194bb5b73945359df34d7

Observation 3f21d45f-e2c9-4d3c-9a6e-1368b42e3cfc · inbound

Both Ends Count! Just How Good are LLM Agents at "Text-to-Big SQL"? cites this paper.

Both Ends Count! Just How Good are LLM Agents at "Text-to-Big SQL"? Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-15T19:56:33.685845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-15T19:52:53.443887Z digest=sha256:c7cee5f39ce69c98a7f5940316c0141264a5f9beba83e51772c3dc63134c5dae

Observation adfb310d-62bc-45dd-abbe-e9015e727ef4 · inbound

S3Mem: Structured Spatiotemporal Scene-Event Memory for Long-Horizon Interactive Question Answering cites this paper.

S3Mem: Structured Spatiotemporal Scene-Event Memory for Long-Horizon Interactive Question Answering Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

Reference 2

Resolution
unresolved
no resolver link, observed 2026-07-12T23:31:35.459743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T23:31:35.459743Z digest=sha256:96f4553804b40fa46180842e9b10110c3840e208bb67adc479d2b40a216f75a0

Observation 3969cf2a-a116-4771-904d-61bf95757af8 · inbound

PyraMathBench: Evaluating and Improving Mathematical Capability in Large Language Models cites this paper.

PyraMathBench: Evaluating and Improving Mathematical Capability in Large Language Models Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T04:06:34.713405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T09:30:15.567469Z digest=sha256:f93d16ecff68bb5de8433f62c48a281e24ca8b61028fe46e7f45cb9f8f30beee

Observation f3c7f45d-2abf-434d-a2bf-eb2167804b0e · inbound

MoCA-Agent: A Market-of-Claims Code Agent for Financial and Numerical Reasoning cites this paper.

MoCA-Agent: A Market-of-Claims Code Agent for Financial and Numerical Reasoning Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

Reference 24

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T09:57:56.195171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-27T10:17:42.831128Z digest=sha256:a84e2af98c9523ea5be60065b3836662b9dbe1079aef18ae00d16b5069cda120

Observation a28a25c1-1c2d-458a-92d5-d267cbbab04e · inbound

ToolAtlas: Learning Once, Reusing Everywhere with Tool-Side Memory cites this paper.

ToolAtlas: Learning Once, Reusing Everywhere with Tool-Side Memory Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

Reference 1

Resolution
unresolved
no resolver link, observed 2026-07-14T06:53:39.552690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T06:53:39.552690Z digest=sha256:d4e9431b321812edc101266f87e437f9f9916e338e7f09e8a36781470f67cf01