Paper Citation Record · LEDGER

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models

As of 13 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2501.07815.

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

pith.paper-citation-record.v1
2501.07815 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:38:52.717542Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

28 of 28 outbound references displayed

verified exact4
verified fuzzy0
unresolved24
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6add0a04-565e-484e-93c3-8a45ccbba43a · outbound

This paper cites Graph of Thoughts: Solving Elaborate Problems with Large Language Models.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Graph of Thoughts: Solving Elaborate Problems with Large Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T20:38:52.579600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efa759ee-2609-4733-aa08-daf6ecc0ef3c · outbound

This paper cites Do large language models resemble humans in language use?.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Do large language models resemble humans in language use?

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:38:53.102984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 51103717-440d-46c8-b700-345050b93476 · outbound

This paper cites an unresolved cited work.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-10T20:38:53.268182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 762c1b1c-f186-49ed-8b73-7ee35c98b5ec · outbound

This paper cites an unresolved cited work.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-10T20:38:53.251570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 03e47ca4-d9ae-4c89-bb14-7f00c9e5c3fd · outbound

This paper cites Generative AI.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Generative AI

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:38:53.075900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 352fb25a-9922-4701-a2ce-4bba764ce3df · outbound

This paper cites Stream of Search (SoS): Learning to Search in Language.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Stream of Search (SoS): Learning to Search in Language

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T20:38:52.605152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33298443-6420-4a14-9dd1-8f6386433dd9 · outbound

This paper cites In-Context Learning Creates Task Vectors.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models In-Context Learning Creates Task Vectors

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T20:38:52.611390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13e98298-0258-44f4-8e57-b80da52d6099 · outbound

This paper cites MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T20:38:52.616621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb929e6c-54a6-48e3-9f07-39fec86f2aa1 · outbound

This paper cites Exploiting Asymmetry for Synthetic Training Data Generation: SynthIE and the Case of Information Extraction.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Exploiting Asymmetry for Synthetic Training Data Generation: SynthIE and the Case of Information Extraction

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:38:52.996626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a7a7b098-07fa-4932-93ae-8d49913ebe5f · outbound

This paper cites Large Language Models are Zero-Shot Reasoners.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Large Language Models are Zero-Shot Reasoners

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T20:38:52.627127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45163d45-fac9-4715-964a-78340b51e047 · outbound

This paper cites Large Language Models Understand and Can be Enhanced by Emotional Stimuli.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Large Language Models Understand and Can be Enhanced by Emotional Stimuli

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T20:38:52.632907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fdfe4939-70ed-428b-bb84-43a16ef400ca · outbound

This paper cites an unresolved cited work.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-10T20:38:53.233192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6512b1ca-58e3-4667-82b5-60f165edb258 · outbound

This paper cites Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T20:38:52.642415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4f47c10-edd7-40e8-8ba0-3ca0ac446637 · outbound

This paper cites Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T20:38:52.647929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46cf9c62-b9a7-4fe6-ae8d-43d27b915d6f · outbound

This paper cites an unresolved cited work.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-10T20:38:53.214835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7e7ead66-0636-4140-aa51-5fd6e3db65e8 · outbound

This paper cites an unresolved cited work.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-10T20:38:53.198192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a59cbe9b-c6e5-4573-85a3-816b2942b074 · outbound

This paper cites Branch-Solve-Merge Improves Large Language Model Evaluation and Generation.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Branch-Solve-Merge Improves Large Language Model Evaluation and Generation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T20:38:52.662127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00caaff1-5792-479b-89df-9369b03bcee0 · outbound

This paper cites Diagnostic Reasoning Prompts Reveal the Potential for Large Language Model Interpretability in Medicine.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Diagnostic Reasoning Prompts Reveal the Potential for Large Language Model Interpretability in Medicine

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:38:52.883156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 15ab0dd0-0d99-4441-afae-92eecf4c2626 · outbound

This paper cites SK-VQA: Synthetic Knowledge Generation at Scale for Training Context-Augmented Multimodal LLMs.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models SK-VQA: Synthetic Knowledge Generation at Scale for Training Context-Augmented Multimodal LLMs

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T20:38:52.672173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4474e9c1-929e-43e8-b3fd-2a03340d5d31 · outbound

This paper cites an unresolved cited work.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-10T20:38:53.178814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5ff6bd93-cc21-4c01-a03b-f70e6b9672fd · outbound

This paper cites Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T20:38:52.682341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c828e2b4-9b43-464e-bfe7-70c53322a3bb · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T20:38:52.687594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b14b0107-8ec5-4790-8c4e-618dee3fd901 · outbound

This paper cites AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T20:38:52.692610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b79d0b3d-8f90-4bfb-9d3d-7f051fa3e9e6 · outbound

This paper cites The Rise and Potential of Large Language Model Based Agents: A Survey.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models The Rise and Potential of Large Language Model Based Agents: A Survey

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T20:38:52.697530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f36fde06-346e-4141-99dd-ac39ef0c11db · outbound

This paper cites an unresolved cited work.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-10T20:38:53.161809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 59ae5a24-9f9c-4474-a7ff-b8ff9aecbadf · outbound

This paper cites Learning and Evaluating General Linguistic Intelligence.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Learning and Evaluating General Linguistic Intelligence

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T20:38:52.706199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f24a41f-6f12-427d-9d9d-e7fe4bde507a · outbound

This paper cites an unresolved cited work.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-10T20:38:53.141950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5c15bb68-e95a-42a8-af08-7213d403942d · outbound

This paper cites Universal and Transferable Adversarial Attacks on Aligned Language Models.

Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-10T20:38:52.717542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.