Paper Citation Record · LEDGER

GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2305.18752.

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

pith.paper-citation-record.v1
2305.18752 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 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 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T21:24:05.966887Z

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

33
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 903b87a8-1ebc-491f-864a-fa2b78611f31 · inbound

A Survey on Multimodal Large Language Models cites this paper.

A Survey on Multimodal Large Language Models GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction

Reference 109

Resolution: verified exact; arxiv_id, observed 2026-05-16T02:56:42.708345Z

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.

Observation ae71d144-eebb-42ac-8e84-6bc95c658227 · inbound

A Comprehensive Overview of Large Language Models cites this paper.

A Comprehensive Overview of Large Language Models GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-19T20:28:39.302356Z

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.

Observation b2e486eb-4209-47ef-acda-c40c6071d4ce · inbound

InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks cites this paper.

InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction

Reference 164

Resolution: verified exact; arxiv_id, observed 2026-05-13T22:46:10.198350Z

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.

Observation ae6ec38b-8fb3-4a98-a6e2-5d7f5006e8a8 · inbound

Mobile-Agent: Autonomous Multi-Modal Mobile Device Agent with Visual Perception cites this paper.

Mobile-Agent: Autonomous Multi-Modal Mobile Device Agent with Visual Perception GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-17T00:19:27.996686Z

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.

Observation 5b60a9cf-906d-4189-add3-abfa70093587 · inbound

Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models cites this paper.

Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-17T07:44:47.580531Z

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.

Observation 6dd69682-cfa9-4249-9239-8d326e2e8e48 · inbound

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

ReQuestNet: A Foundational Learning model for Channel Estimation GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-05T21:24:05.966887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbf364e9-4395-4070-b2b5-97ef4264001a · inbound

Querying Structured Data Through Natural Language Using Language Models cites this paper.

Querying Structured Data Through Natural Language Using Language Models GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-13T19:23:09.375378Z

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.

Observation fe5e9c68-2f08-4c25-be34-f261e515ac37 · inbound

AnchorSeg: Language Grounded Query Banks for Reasoning Segmentation cites this paper.

AnchorSeg: Language Grounded Query Banks for Reasoning Segmentation GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction

Reference 141

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T09:43:49.416849Z

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.

Observation 404f8d7f-c3f0-4ec2-8ddf-cca8b7967498 · inbound

GRAFT: Graph-Tokenized LLMs for Tool Planning cites this paper.

GRAFT: Graph-Tokenized LLMs for Tool Planning GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:22:28.290690Z

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.

Observation 721a390b-f609-42ac-8bd8-f858d719473f · inbound

Context-Fractured Decomposition Attacks on Tool-Using LLM Agents: Exploiting Artifact Provenance Gaps cites this paper.

Context-Fractured Decomposition Attacks on Tool-Using LLM Agents: Exploiting Artifact Provenance Gaps GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-06-27T16:41:03.004082Z

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.