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Paper Citation Record · LEDGER

On the Brittle Foundations of ReAct Prompting for Agentic Large Language Models

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2405.13966.

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

pith.paper-citation-record.v1
2405.13966 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:41:57.799140Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:49:51.482854Z

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 f263fa38-64f8-4c51-b96a-16b20e64ef22 · inbound

Towards Action Hijacking of Large Language Model-based Agent cites this paper.

Towards Action Hijacking of Large Language Model-based Agent On the Brittle Foundations of ReAct Prompting for Agentic Large Language Models

Reference 121

Resolution
unresolved
no resolver link, observed 2026-08-11T15:41:57.799140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:41:57.799140Z digest=sha256:50c302e25732e52ad479bd8ae9c65f05e2348fa62b6d33cd22f6c3bfa2fefdc4

Observation f5d2c2d7-13e9-4188-b4e8-92ef5ead0439 · inbound

Iterative Deepening Sampling as Efficient Test-Time Scaling cites this paper.

Iterative Deepening Sampling as Efficient Test-Time Scaling On the Brittle Foundations of ReAct Prompting for Agentic Large Language Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-08T19:23:26.537298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:23:26.537298Z digest=sha256:aaf7b2bcd4026944b19d969dd09ce0a8807aa0ca47a885c8a9b4551d9b7fa647

Observation 8f2391b4-430e-431d-99e2-b22e3839129b · inbound

Toolsuite for Implementing Multiagent Systems Based on Communication Protocols cites this paper.

Toolsuite for Implementing Multiagent Systems Based on Communication Protocols On the Brittle Foundations of ReAct Prompting for Agentic Large Language Models

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-06T17:40:07.703593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:40:07.703593Z digest=sha256:59da7033e1b828b8f65de8dbb68166dbae00b482ccf545437870fec5b5386357

Observation 036d0c42-8ede-4a02-808b-426da32e951c · inbound

RIMRULE: Improving Tool-Using Language Agents via MDL-Guided Rule Learning cites this paper.

RIMRULE: Improving Tool-Using Language Agents via MDL-Guided Rule Learning On the Brittle Foundations of ReAct Prompting for Agentic Large Language Models

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-03T13:12:19.525462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T13:12:19.525462Z digest=sha256:8e70331f44187f6b06305ce4486fc4b361c5741b5ad4a5023f31e5cde0c556ed

Observation 17aaf3ba-e309-40b1-a0d6-7878edda0584 · inbound

Novelty-based Tree-of-Thought Search for LLM Reasoning and Planning cites this paper.

Novelty-based Tree-of-Thought Search for LLM Reasoning and Planning On the Brittle Foundations of ReAct Prompting for Agentic Large Language Models

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-11T19:56:08.668203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-08T10:41:59.816073Z digest=sha256:c8256bd06d9ec8aa5f083362c373cf651eba9726ed12db69400c43a28f75674c

Observation 012118f4-e8e4-4f42-8860-f77f9551f490 · inbound

Where Do CoT Training Gains Land in LLM based Agents? cites this paper.

Where Do CoT Training Gains Land in LLM based Agents? On the Brittle Foundations of ReAct Prompting for Agentic Large Language Models

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-07-04T13:49:51.484296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-06-26T04:55:14.293452Z digest=sha256:9b67f8689fd373283b87c98764f742ca2f8af4ed0a175ef6a31ee3ea79fa7aea

Observation f4ae28bc-bc2e-4213-be3a-9ad27387f66b · inbound

Consistent but Miscalibrated: Evaluating LLM Limitations for Risk Communication in Natural Language cites this paper.

Consistent but Miscalibrated: Evaluating LLM Limitations for Risk Communication in Natural Language On the Brittle Foundations of ReAct Prompting for Agentic Large Language Models

Reference 147

Resolution
unresolved
no resolver link, observed 2026-07-11T23:16:58.545731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T23:16:58.545731Z digest=sha256:4aa232b1eea38b04214a0fb7567cda93731e19b07d730af7254371b434749a5a

Observation 5f8c6917-1562-40ab-b980-aa551f6efd6b · inbound

Consistent but Miscalibrated: Evaluating LLM Limitations for Risk Communication in Natural Language cites this paper.

Consistent but Miscalibrated: Evaluating LLM Limitations for Risk Communication in Natural Language On the Brittle Foundations of ReAct Prompting for Agentic Large Language Models

Reference 147

Resolution
unresolved
no resolver link, observed 2026-07-13T07:02:13.140334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T07:02:13.140334Z digest=sha256:1e1f3e0dd8cd77f66443cb1dc71bde8be9c08ce2d6abfce4c6cc83cad757a380

Observation dfc9d78e-65cc-404c-ad7d-aa43e9077a8e · inbound

CogniConsole: Externalizing Inference-Time Control as a Formal Abstraction for Reliable LLM Interactions cites this paper.

CogniConsole: Externalizing Inference-Time Control as a Formal Abstraction for Reliable LLM Interactions On the Brittle Foundations of ReAct Prompting for Agentic Large Language Models

Reference 17

Resolution
unresolved
no resolver link, observed 2026-07-13T08:11:52.254741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T08:11:52.254741Z digest=sha256:a4f9bfd6fe4d8b8f2542fbe8ca71f730e329f0ccf9a8504783a4777756c94910

Observation 44db3b7e-17b3-4b7c-9b35-36f2d0d52537 · inbound

NeSyFS: A Neuro-symbolic Fast-Slow Thinking Framework for LLM Agent under Partial Observability cites this paper.

NeSyFS: A Neuro-symbolic Fast-Slow Thinking Framework for LLM Agent under Partial Observability On the Brittle Foundations of ReAct Prompting for Agentic Large Language Models

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-03T16:55:02.726677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T16:55:02.726677Z digest=sha256:deb00a15940316c4e15e615e9817cc1010fa5ea2860ccdc4174ba7eef7ef81bd

Observation c63a16c6-d13e-4576-8264-d7ceb57db401 · inbound

NeSyFS: A Neuro-symbolic Fast-Slow Thinking Framework for LLM Agent under Partial Observability cites this paper.

NeSyFS: A Neuro-symbolic Fast-Slow Thinking Framework for LLM Agent under Partial Observability On the Brittle Foundations of ReAct Prompting for Agentic Large Language Models

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-05T04:24:56.697811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T04:24:56.697811Z digest=sha256:efcd0a9800917dec5720049279096ea07101237bb8d95c522904cbd89006cf56