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Paper Citation Record · LEDGER

LLMs in the Imaginarium: Tool Learning through Simulated Trial and Error

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2403.04746.

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

pith.paper-citation-record.v1
2403.04746 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:23:02.411676Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T12:18:41.756866Z

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 361c525c-c4ee-4040-813c-ead88b017d5b · inbound

Head-Specific Intervention Can Induce Misaligned AI Coordination in Large Language Models cites this paper.

Head-Specific Intervention Can Induce Misaligned AI Coordination in Large Language Models LLMs in the Imaginarium: Tool Learning through Simulated Trial and Error

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-08T17:23:02.411676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:23:02.411676Z digest=sha256:6cd86f680d1f67c3e44b0eb1184bd7159d7c14a1f217902ba812cb8208a6ec81

Observation 6366a98b-5479-49fb-bb1d-459f4419d489 · inbound

Large Language Models for Planning: A Comprehensive and Systematic Survey cites this paper.

Large Language Models for Planning: A Comprehensive and Systematic Survey LLMs in the Imaginarium: Tool Learning through Simulated Trial and Error

Reference 243

Resolution
unresolved
no resolver link, observed 2026-08-07T14:12:07.566575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:12:07.566575Z digest=sha256:fc87f41e61c4d5b009e774698742f710cfca28bbd93f5271b6d65f5b9d15eda2

Observation b0296d9b-3ab5-4a10-b7d2-f3c7d6351dd0 · inbound

Enhancing Tool Learning in Large Language Models with Hierarchical Error Checklists cites this paper.

Enhancing Tool Learning in Large Language Models with Hierarchical Error Checklists LLMs in the Imaginarium: Tool Learning through Simulated Trial and Error

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T13:21:43.105483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:21:43.105483Z digest=sha256:9ac0290b0d6e00b74d946c5c75e6e55efd3849ad2f039ae822cec1d7c8fa9c43

Observation 24dc9495-3c69-4b8c-aa3c-958bd5a0408e · inbound

The Curious Language Model: Strategic Test-Time Information Acquisition cites this paper.

The Curious Language Model: Strategic Test-Time Information Acquisition LLMs in the Imaginarium: Tool Learning through Simulated Trial and Error

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T04:58:46.936577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:58:46.936577Z digest=sha256:901fd616faa797ccc89cd469a623c42cc937004bb83ba37cd7c4d40d43bad0f3

Observation 3d2fe1c4-0a8c-4ee2-bfd4-ebe8f53cfd67 · inbound

MMAT-1M: A Large Reasoning Dataset for Multimodal Agent Tuning cites this paper.

MMAT-1M: A Large Reasoning Dataset for Multimodal Agent Tuning LLMs in the Imaginarium: Tool Learning through Simulated Trial and Error

Reference 62

Resolution
verified exact
local_arxiv, observed 2026-08-06T12:18:41.874604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T12:18:39.029360Z digest=sha256:f1004c5c7244cf62abdeeccb8331cf34b0595471a3f689d97c26e6b516eb42cd