Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-12T03:29:00.463046Z
Paper Citation Record · LEDGER
Position: Avoid Overstretching LLMs for every Enterprise Task
As of 4 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2605.09365.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
37 of 37 outbound references displayed
- verified exact1
- verified fuzzy30
- unresolved5
- parse uncertain1
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 315db7cb-ff2d-47b6-a2ea-e491ba38b4c8 · outbound
This paper cites Reducing hallucination in structured outputs via retrieval-augmented generation.
Position: Avoid Overstretching LLMs for every Enterprise Task Reducing hallucination in structured outputs via retrieval-augmented generation
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.153669Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a3070595-a474-4128-9c0e-e1a560e356ff · outbound
This paper cites Separations in the representational capabilities of transformers and recurrent architectures.
Position: Avoid Overstretching LLMs for every Enterprise Task Separations in the representational capabilities of transformers and recurrent architectures
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.182994Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 30946eba-f215-415b-8583-76aa4eeeef0d · outbound
This paper cites Enterprise ai adoption: Balancing innovation and roi in 2026.
Position: Avoid Overstretching LLMs for every Enterprise Task Enterprise ai adoption: Balancing innovation and roi in 2026
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.233653Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 502fd679-0870-4ad3-83de-6c897d68ef2b · outbound
This paper cites an unresolved cited work.
Position: Avoid Overstretching LLMs for every Enterprise Task Unresolved cited work
Reference 4
- Resolution
- parse uncertain
- raw_fallback, observed 2026-05-12T19:36:48.134856Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 77bfc7ab-8e49-439a-a194-eb2ace4568ab · outbound
This paper cites Ai trends 2025: Adoption barriers and updated predictions.
Position: Avoid Overstretching LLMs for every Enterprise Task Ai trends 2025: Adoption barriers and updated predictions
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.188576Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 708797fc-a985-4780-8189-0c5fb8f8168b · outbound
This paper cites State of ai in the enterprise 2026.
Position: Avoid Overstretching LLMs for every Enterprise Task State of ai in the enterprise 2026
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.130408Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 524565ea-da3c-4e74-961b-6c9cb8621eb6 · outbound
This paper cites Fixing it in post: A comparative study of llm post-training data quality and model performance.
Position: Avoid Overstretching LLMs for every Enterprise Task Fixing it in post: A comparative study of llm post-training data quality and model performance
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.077352Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation fbf4c70d-6136-49dd-976f-6bba3932467c · outbound
This paper cites Ai adoption outpaces governance: Responsible ai pulse survey.
Position: Avoid Overstretching LLMs for every Enterprise Task Ai adoption outpaces governance: Responsible ai pulse survey
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.223812Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0f7a7144-a581-494a-b451-7dc8b2025758 · outbound
This paper cites Gartner predicts over 40% of agentic ai projects will be canceled by end of 2027.
Position: Avoid Overstretching LLMs for every Enterprise Task Gartner predicts over 40% of agentic ai projects will be canceled by end of 2027
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.193922Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation fbb28a29-9828-48ec-bc58-59db6193c1d5 · outbound
This paper cites Hána and B.
Position: Avoid Overstretching LLMs for every Enterprise Task Hána and B
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.202920Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 79620e82-9a8b-4670-a8e3-cf00badc0ce8 · outbound
This paper cites Overcoming the organizational barriers to ai adoption.
Position: Avoid Overstretching LLMs for every Enterprise Task Overcoming the organizational barriers to ai adoption
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.229104Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3d7f0d29-08e1-4907-81b3-836ea9792362 · outbound
This paper cites State of enterprise ai adoption report 2025.
Position: Avoid Overstretching LLMs for every Enterprise Task State of enterprise ai adoption report 2025
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.072039Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e4b9fb3b-c4ca-465d-9cf9-ac537c3c4201 · outbound
This paper cites an unresolved cited work.
Position: Avoid Overstretching LLMs for every Enterprise Task Unresolved cited work
Reference 13
- Resolution
- unresolved
- raw_fallback, observed 2026-05-12T19:36:48.112535Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f9053b29-c36a-468e-bfc2-0682225d5a06 · outbound
This paper cites Karakurt and A.
Position: Avoid Overstretching LLMs for every Enterprise Task Karakurt and A
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.083988Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6d4477ba-18fd-411d-b463-d78b3f3c3453 · outbound
This paper cites Foundation models for tabular data within systemic contexts need grounding.
Position: Avoid Overstretching LLMs for every Enterprise Task Foundation models for tabular data within systemic contexts need grounding
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.101057Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d815b2af-12f0-48ce-80d8-055d15b86ee0 · outbound
This paper cites Retrieval-augmented generation for knowledge-intensive nlp tasks.
Position: Avoid Overstretching LLMs for every Enterprise Task Retrieval-augmented generation for knowledge-intensive nlp tasks
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.091193Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b4898e5e-25f0-4bd3-9e94-dafb6f31e721 · outbound
This paper cites End-to-end ontology learning with large language models.Advances in Neural Information Processing Systems, 37:87184–87225.
Position: Avoid Overstretching LLMs for every Enterprise Task End-to-end ontology learning with large language models.Advances in Neural Information Processing Systems, 37:87184–87225
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.148627Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 82866899-e590-4ebe-81b0-bf04abf562d7 · outbound
This paper cites Canonical intermediate representation for llm-based optimization problem formulation and code generation.
Position: Avoid Overstretching LLMs for every Enterprise Task Canonical intermediate representation for llm-based optimization problem formulation and code generation
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T07:21:23.719766Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation af51d9ce-3661-4b5b-b149-375ba82a29b7 · outbound
This paper cites The state of ai: Global survey 2025.
Position: Avoid Overstretching LLMs for every Enterprise Task The state of ai: Global survey 2025
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.173535Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 41f36176-30cb-4ae8-972a-497e88755a9c · outbound
This paper cites 2025: The state of ai in healthcare.
Position: Avoid Overstretching LLMs for every Enterprise Task 2025: The state of ai in healthcare
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.218208Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4dc473a1-f1f4-4a1d-97f7-6be48570f750 · outbound
This paper cites The state of enterprise ai.
Position: Avoid Overstretching LLMs for every Enterprise Task The state of enterprise ai
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.126276Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2f0f2af6-7c12-45cd-b643-847eb58f5f56 · outbound
This paper cites merging worlds.
Position: Avoid Overstretching LLMs for every Enterprise Task merging worlds
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.213640Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e353ad5f-f67a-4224-80e1-5d4464104cbc · outbound
This paper cites The GenAI Divide: State of AI in Business 2025.
Position: Avoid Overstretching LLMs for every Enterprise Task The GenAI Divide: State of AI in Business 2025
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.059661Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation fca5bcd8-bba0-4ae8-a615-bad633a79785 · outbound
This paper cites Romeo and J.
Position: Avoid Overstretching LLMs for every Enterprise Task Romeo and J
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.096589Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6340b9f6-05ee-432d-9c32-ff098df187cb · outbound
This paper cites Ai adoption is soaring, but few companies are measuring its impact.
Position: Avoid Overstretching LLMs for every Enterprise Task Ai adoption is soaring, but few companies are measuring its impact
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.158672Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 97b7cebc-03fd-4502-9952-8ecd2a0fa4e5 · outbound
This paper cites What formal lan- guages can transformers express? a survey.Transactions of the Association for Computational Linguistics.
Position: Avoid Overstretching LLMs for every Enterprise Task What formal lan- guages can transformers express? a survey.Transactions of the Association for Computational Linguistics
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.208623Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8c8cf7d7-2ddf-4e08-ae5d-1414f249fe03 · outbound
This paper cites Claude ai agent deletes firm database in seconds.The Guardian, April 2026.
Position: Avoid Overstretching LLMs for every Enterprise Task Claude ai agent deletes firm database in seconds.The Guardian, April 2026
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.117453Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a7125268-32dc-434a-a82f-be2a0ff13c20 · outbound
This paper cites Enterprise ai adoption and roi: Three-year executive study.
Position: Avoid Overstretching LLMs for every Enterprise Task Enterprise ai adoption and roi: Three-year executive study
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.163495Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5b9724d1-edf7-4688-80e8-509c12b05ed4 · outbound
This paper cites The state of digital adoption 2025 (special ai edition).
Position: Avoid Overstretching LLMs for every Enterprise Task The state of digital adoption 2025 (special ai edition)
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.177958Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e76a89e3-638e-420a-993b-ffc474374a39 · outbound
This paper cites Lumina: Detecting hallucinations in rag system with context–knowledge signals.
Position: Avoid Overstretching LLMs for every Enterprise Task Lumina: Detecting hallucinations in rag system with context–knowledge signals
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.052931Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9e223bf5-0c49-4245-a8ba-bd788c6abd53 · outbound
This paper cites textbook-quality.
Position: Avoid Overstretching LLMs for every Enterprise Task textbook-quality
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.106902Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 764dce5c-09b4-4f6c-97a1-16df9571d0ae · outbound
This paper cites 6SLM surveys document systematic OOD failures.
Position: Avoid Overstretching LLMs for every Enterprise Task 6SLM surveys document systematic OOD failures
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.143410Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d947cd4d-56da-4a1c-a066-a397091b04db · outbound
This paper cites an unresolved cited work.
Position: Avoid Overstretching LLMs for every Enterprise Task Unresolved cited work
Reference 33
- Resolution
- unresolved
- raw_fallback, observed 2026-05-12T19:36:48.198338Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7eb87691-2286-45ab-ad4d-d68263aa61ea · outbound
This paper cites an unresolved cited work.
Position: Avoid Overstretching LLMs for every Enterprise Task Unresolved cited work
Reference 34
- Resolution
- unresolved
- raw_fallback, observed 2026-05-12T19:36:48.139033Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cfdb63b7-b0c9-4704-9be2-c2d6f87adde2 · outbound
This paper cites an unresolved cited work.
Position: Avoid Overstretching LLMs for every Enterprise Task Unresolved cited work
Reference 35
- Resolution
- unresolved
- raw_fallback, observed 2026-05-12T19:36:48.066812Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e59cce97-8041-4878-acdf-f4ca881334b8 · outbound
This paper cites an unresolved cited work.
Position: Avoid Overstretching LLMs for every Enterprise Task Unresolved cited work
Reference 36
- Resolution
- unresolved
- raw_fallback, observed 2026-05-12T19:36:48.121785Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 74906851-0442-4c0d-8ff2-b92c56832922 · outbound
This paper cites If the task requires high information complexity (e.g., many latent states or steps), this double compression tends to privilege superficial heuristics over algorithmic fidelity.
Position: Avoid Overstretching LLMs for every Enterprise Task If the task requires high information complexity (e.g., many latent states or steps), this double compression tends to privilege superficial heuristics over algorithmic fidelity
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:36:48.169106Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Pith citing papers
No inbound Pith citation observations are available.