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Paper Citation Record · LEDGER

DynaSaur: Large Language Agents Beyond Predefined Actions

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2411.01747.

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

pith.paper-citation-record.v1
2411.01747 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T02:02:25.766495Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T17:02:40.815139Z

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 d5953828-a28e-40ca-8a1b-597be44116de · inbound

Foundational Design Principles and Patterns for Building Robust and Adaptive GenAI-Native Systems cites this paper.

Foundational Design Principles and Patterns for Building Robust and Adaptive GenAI-Native Systems DynaSaur: Large Language Agents Beyond Predefined Actions

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-18T22:11:52.722681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-18T22:11:00.992743Z digest=sha256:3fb0e323093c5278eeee8344e462992c9edb40531d606ee0f8d938acce6bcfec

Observation 7c8ab7bb-ff15-4f79-bf87-0bc2f5996161 · inbound

Reinforcement Learning for Self-Improving Agent with Skill Library cites this paper.

Reinforcement Learning for Self-Improving Agent with Skill Library DynaSaur: Large Language Agents Beyond Predefined Actions

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-17T20:05:30.606439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-17T20:05:30.593804Z digest=sha256:11b4753cb35ec2558f50a4736d45b6eb796ba7a2d6178cc2f6ca4aba4e328ac2

Observation c697fd44-8ede-44af-ba90-99095c8cf725 · inbound

CONDESION-BENCH: Conditional Decision-Making of Large Language Models in Compositional Action Space cites this paper.

CONDESION-BENCH: Conditional Decision-Making of Large Language Models in Compositional Action Space DynaSaur: Large Language Agents Beyond Predefined Actions

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T06:46:53.536398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T17:26:26.510057Z digest=sha256:89d36b970a728ed48dcf92e4731e61d6fbb4e5944e1d9bb1a36bb75fb0356c48

Observation c036c338-71e6-42b3-bbcb-27797916aa9d · inbound

Rethinking Agentic Reinforcement Learning In Large Language Models cites this paper.

Rethinking Agentic Reinforcement Learning In Large Language Models DynaSaur: Large Language Agents Beyond Predefined Actions

Reference 64

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:21:29.762285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-07T06:30:09.945371Z digest=sha256:114ef61aad54e480d8cf97a141d6c046ff5350aff57a54a4ef14229111a598cf

Observation 300d954c-bae1-4806-96ba-291006ff0146 · inbound

Rethinking Agentic Reinforcement Learning In Large Language Models cites this paper.

Rethinking Agentic Reinforcement Learning In Large Language Models DynaSaur: Large Language Agents Beyond Predefined Actions

Reference 64

Resolution
verified exact
arxiv_id, observed 2026-05-11T22:11:17.086441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-08T03:12:19.414358Z digest=sha256:389b1ede4ceb590edc44931b42d64c4ea777bfc9da67a537292cd7a9933d5e13

Observation ab08214f-0146-42c3-8f3a-170844968c15 · inbound

Rethinking Agentic Reinforcement Learning In Large Language Models cites this paper.

Rethinking Agentic Reinforcement Learning In Large Language Models DynaSaur: Large Language Agents Beyond Predefined Actions

Reference 64

Resolution
verified exact
arxiv_id, observed 2026-05-19T17:02:40.816706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-19T16:58:41.558250Z digest=sha256:e3ef6d6a08977cbdbf618c4a68c8ac2a030e7e978810d6fc8b4fc91c0a3ac828

Observation 8d0de780-2e84-4c8b-8943-948d521e306b · inbound

Do Self-Evolving Agents Forget? Capability Degradation and Preservation in Lifelong LLM Agent Adaptation cites this paper.

Do Self-Evolving Agents Forget? Capability Degradation and Preservation in Lifelong LLM Agent Adaptation DynaSaur: Large Language Agents Beyond Predefined Actions

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:31:29.272941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-12T04:10:31.784413Z digest=sha256:830f8037f4b64094bca017305fdbbea8f6c1b61bd695958227235685355e35df

Observation 14e41f65-5d2b-4709-8cfc-bdcb8e92980e · inbound

Workload-Aware Caching for Multi-Agent Systems cites this paper.

Workload-Aware Caching for Multi-Agent Systems DynaSaur: Large Language Agents Beyond Predefined Actions

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-02T11:22:59.122377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T11:22:59.122377Z digest=sha256:af7c67dba9bba79a0d44f152985e1ff15e27e73794a3f11b5a1a9ce5590d89a9

Observation d742f155-ebfa-4348-9c78-f6068e7a937b · inbound

CITBench: A Comprehensive Benchmark for Interactive Tabular Data Processing with LLMs cites this paper.

CITBench: A Comprehensive Benchmark for Interactive Tabular Data Processing with LLMs DynaSaur: Large Language Agents Beyond Predefined Actions

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-04T02:02:25.766495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T02:02:25.766495Z digest=sha256:a0c6ca85f6efcb2a7b9582f9c5ef1b3fc640f0054810388608f376d3c83622b3