Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Ask Me Anything: A simple strategy for prompting language models
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2210.02441.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T17:20:32.278457Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T06:57:40.125720Z
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 864c92e4-f26c-4ced-9cfd-c20d113d2245 · inbound
Emergent Abilities of Large Language Models cites this paper.
Emergent Abilities of Large Language Models Ask Me Anything: A simple strategy for prompting language models
Reference 5
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T07:38:38.006224Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 7934065c-4cf0-41db-8e9a-75fa2ab4e361 · inbound
ART: Automatic multi-step reasoning and tool-use for large language models cites this paper.
ART: Automatic multi-step reasoning and tool-use for large language models Ask Me Anything: A simple strategy for prompting language models
Reference 137
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-16T19:03:06.197700Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation bb91a987-19ce-4e3d-8c75-3bb16ff32ce0 · inbound
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes cites this paper.
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes Ask Me Anything: A simple strategy for prompting language models
Reference 63
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T20:50:09.378763Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 65617d68-2cb2-49f0-9ef3-0a4197a80279 · inbound
FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance cites this paper.
FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance Ask Me Anything: A simple strategy for prompting language models
Reference 1
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T19:56:45.450814Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 075e787e-d5bd-4e8c-b9f3-35e0e17f0f78 · inbound
FDM-Bench: A Comprehensive Benchmark for Evaluating Large Language Models in Additive Manufacturing Tasks cites this paper.
FDM-Bench: A Comprehensive Benchmark for Evaluating Large Language Models in Additive Manufacturing Tasks Ask Me Anything: A simple strategy for prompting language models
Reference 43
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T06:57:40.128690Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 71b64f25-b7c8-48d6-96f7-d7f510cf0c43 · inbound
Automatic Labelling with Open-source LLMs using Dynamic Label Schema Integration cites this paper.
Automatic Labelling with Open-source LLMs using Dynamic Label Schema Integration Ask Me Anything: A simple strategy for prompting language models
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:20:32.278457Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8f1f1dc1-ba6e-4397-8965-1e37547302d9 · inbound
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems cites this paper.
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems Ask Me Anything: A simple strategy for prompting language models
Reference 116
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-22T21:42:10.870414Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 7ad3d959-c4a9-4b84-a672-e3baedad3c0d · inbound
Enhancing the Safety of Medical Vision-Language Models by Synthetic Demonstrations cites this paper.
Enhancing the Safety of Medical Vision-Language Models by Synthetic Demonstrations Ask Me Anything: A simple strategy for prompting language models
Reference 3
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-19T10:57:16.494064Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 42834d90-8dac-4fca-9426-09d3162565ad · inbound
In-Context Learning as an Effective Estimator of Functional Correctness of LLM-Generated Code cites this paper.
In-Context Learning as an Effective Estimator of Functional Correctness of LLM-Generated Code Ask Me Anything: A simple strategy for prompting language models
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:34:34.401058Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a7e47833-38d1-4aa7-9982-e4fe12197f44 · inbound
The Fourier Spectral Transformer Networks For Efficient and Generalizable Nonlinear PDEs Prediction cites this paper.
The Fourier Spectral Transformer Networks For Efficient and Generalizable Nonlinear PDEs Prediction Ask Me Anything: A simple strategy for prompting language models
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:27:46.651835Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b775d29f-7162-4589-b7eb-43e426c3fb62 · inbound
Power and Limitations of Aggregation in Compound AI Systems cites this paper.
Power and Limitations of Aggregation in Compound AI Systems Ask Me Anything: A simple strategy for prompting language models
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T21:09:48.568672Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 89803ffe-7c3e-4d9a-a082-7e9ea0825dd2 · inbound
C-TRAIL: A Commonsense World Framework for Trajectory Planning in Autonomous Driving cites this paper.
C-TRAIL: A Commonsense World Framework for Trajectory Planning in Autonomous Driving Ask Me Anything: A simple strategy for prompting language models
Reference 25
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T23:28:26.040988Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 4015d234-027c-441a-8fed-8f406d2a3a3c · inbound
How Language Models Process Out-of-Distribution Inputs: A Two-Pathway Framework cites this paper.
How Language Models Process Out-of-Distribution Inputs: A Two-Pathway Framework Ask Me Anything: A simple strategy for prompting language models
Reference 31
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T15:31:20.984585Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.