Pith. sign in

Paper Citation Record · LEDGER

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences

As of 8 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2506.11681.

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

pith.paper-citation-record.v1
2506.11681 v2

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:07:20.752825Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

23 of 23 outbound references displayed

  • verified exact0
  • verified fuzzy11
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f4d56378-7bbd-4e86-b23f-d7b4f3ac01f7 · outbound

This paper cites Saggion and G.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences Saggion and G

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:07:21.065744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:07:20.682020Z digest=sha256:d54e14e7314aa12cb51e3a81030f543ee5b87cacf7b9f3410d697e3b7f7865fe

Observation ecc6c88d-8cc1-4ed9-89d0-570420917c2c · outbound

This paper cites Data-Driven Sentence Simplification: Survey and Benchmark,.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences Data-Driven Sentence Simplification: Survey and Benchmark,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:07:21.056032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:07:20.685586Z digest=sha256:9611d056f759eda4faa85a63834e5646341799460b970cd166bee5315d8b0318

Observation fd430b44-6b67-4863-a96a-dddc8a8310f3 · outbound

This paper cites Sentence Simplification via Large Language Models.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences Sentence Simplification via Large Language Models

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T04:07:20.689089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:07:20.689089Z digest=sha256:ab9b4f596143cec0aed2dcc82f6a83d341b79f8d0795521c40c11383448165ac

Observation a572c798-71eb-4b46-8727-88ff71b32cc8 · outbound

This paper cites GPT-4o: Multimodal Language Model,.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences GPT-4o: Multimodal Language Model,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:07:21.045726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:07:20.692618Z digest=sha256:1217cae35d7d715acc9223bbc325f414278d309c3d113896c19d241b753c299a

Observation 37903acd-02da-4a57-a138-f025a2051102 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences Gemini: A Family of Highly Capable Multimodal Models

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T04:07:20.695753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:07:20.695753Z digest=sha256:04df4c87bed0f50cdc25e605461ee47e24816acaccfab942c7022a321b2dc852

Observation a065aee9-d31d-4af3-b823-7ba40d46f3ad · outbound

This paper cites Introducing Perplexity Deep Research,.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences Introducing Perplexity Deep Research,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:07:21.035974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:07:20.699524Z digest=sha256:38cb97251841ae68dd99cc1a995f70e4096700363753cb0e0cbdda00c4512bf0

Observation 49c51ea4-edee-4977-80bc-455b7e3bd732 · outbound

This paper cites The Prompt Report: A Systematic Survey of Prompt Engineering Techniques.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences The Prompt Report: A Systematic Survey of Prompt Engineering Techniques

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T04:07:20.702857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:07:20.702857Z digest=sha256:f3b2c9f9ed4ec2db567ebe49780ae8a1c09cf0dec717e049df097ceefb3a6ad7

Observation b0c474b0-8ec8-40d5-aa34-16241a01a799 · outbound

This paper cites Self-Adaptive In-Context Learning: An Information Compression Perspective for In-Context Example Selection and Ordering.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences Self-Adaptive In-Context Learning: An Information Compression Perspective for In-Context Example Selection and Ordering

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T04:07:20.706134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:07:20.706134Z digest=sha256:2b5a2eaab8fe247b7bb455138cef0a7315b64d8624b6fb9d28b6e04e66fa8443

Observation 06e3e99c-a91e-45d3-bfc8-bf4c689c6649 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models,.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences Chain-of-thought prompting elicits reasoning in large language models,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:07:21.024991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:07:20.709141Z digest=sha256:c4c8f28f2ee48a3d1a8363df7dc949a3a70edb798a6fa6bdbd1592e4db9930fd

Observation 89c3f0a4-dab9-4733-9e95-06b0435d734a · outbound

This paper cites A Survey on In-context Learning.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences A Survey on In-context Learning

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T04:07:20.711774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:07:20.711774Z digest=sha256:6d38b32cc80801254ae3166dc16b01a67a305a01f962297db1c8aed7499b7542

Observation 06ab692b-3399-4020-a5a0-c0ed5e735a2d · outbound

This paper cites Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T04:07:20.715124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:07:20.715124Z digest=sha256:e1d6f2476c623c5d9eb0ea71d0d817f787fc7bdf888b97f9c09097c88fd48466

Observation 35532825-4ccf-412c-b91e-c92d29b9ed6f · outbound

This paper cites Meta-in-context learning in large language models,.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences Meta-in-context learning in large language models,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:07:21.012249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:07:20.718308Z digest=sha256:e94035b1491dd9117af02cc2d560931add894e0f2b62f9762e1886d918f48cc7

Observation e8aec661-d4a1-4a37-8eaa-da9e4866179b · outbound

This paper cites Large Language Model based Multi-Agents: A Survey of Progress and Challenges.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences Large Language Model based Multi-Agents: A Survey of Progress and Challenges

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T04:07:20.721584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:07:20.721584Z digest=sha256:9b46275203b56b801b1343d20ff5248262027083590b32ff03b9023924c5dc32

Observation ccf76b2d-4a6e-490b-acca-e0f70eeafdea · outbound

This paper cites Marked Personas: Using Natural Language Prompts to Measure Stereotypes in Language Models.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences Marked Personas: Using Natural Language Prompts to Measure Stereotypes in Language Models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T04:07:20.724941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:07:20.724941Z digest=sha256:f8a771b411dced1092870e6315dd48cfc9daa27ad6c8303c134c4a68a36793cb

Observation ac392171-0ad0-4c85-a993-5aacf3404329 · outbound

This paper cites Multi-Stage Prompting for Next Best Agent Recommendations in Adaptive Workflows,.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences Multi-Stage Prompting for Next Best Agent Recommendations in Adaptive Workflows,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:07:20.998161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:07:20.728311Z digest=sha256:afbf8c952916666419f3bedc4b1aee66da004c49c3fd5ad0cfc7dde9dcb26aa0

Observation f7b04c6d-bf80-4b09-a7b8-a17ac92af637 · outbound

This paper cites Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T04:07:20.731350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:07:20.731350Z digest=sha256:e0ffee180c8b0079eca41bb8968b268bdfbaa964d20b60a481415f03bce98b63

Observation cd95191b-5292-40de-ba17-104aaca2da7c · outbound

This paper cites Multi-Agent Collaboration Mechanisms: A Survey of LLMs.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences Multi-Agent Collaboration Mechanisms: A Survey of LLMs

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T04:07:20.734462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:07:20.734462Z digest=sha256:5e7e1b7e1816451c0cdb1fce6a54c490829b70c24f1c93f9429da82a370f8cf8

Observation e0ed1dcd-24cc-492b-a63d-c55a136f8fd0 · outbound

This paper cites LLM Multi-Agent Systems: Challenges and Open Problems.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences LLM Multi-Agent Systems: Challenges and Open Problems

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T04:07:20.737667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:07:20.737667Z digest=sha256:dc37bf56bee8f2e7903626defae0cb3d46992f5746d1d60ae04307a294d2e0c7

Observation e0266041-d159-46df-a022-dfcc99a9d8cd · outbound

This paper cites Talk Structurally, Act Hierarchically: A Collaborative Framework for LLM Multi-Agent Systems.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences Talk Structurally, Act Hierarchically: A Collaborative Framework for LLM Multi-Agent Systems

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T04:07:20.740761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:07:20.740761Z digest=sha256:283d5b6ba5f8fed89bd69d6511a6f8c9a559b78a7bd18a75c0bb8c3831ed1f0c

Observation 74f86f1e-7733-49ef-81a5-09f40a5129f8 · outbound

This paper cites Automated program synthesis from object-oriented natural language for computer games,.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences Automated program synthesis from object-oriented natural language for computer games,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:07:20.986806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:07:20.743897Z digest=sha256:8dc7a89c79f265b6fb5484889c1a70be22377b320e40f244915219a6a13bf3f1

Observation 2cc26027-c466-4356-bd4b-2a246adaac46 · outbound

This paper cites Multi-phase context vectors for generating feedback for natural-language based programming,.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences Multi-phase context vectors for generating feedback for natural-language based programming,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:07:20.974563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:07:20.746985Z digest=sha256:3781ebb3d0e38627d046a93e02f6ccc02d2fb0fb020a76c635cc0f22e2246944

Observation 633044bd-0897-40ec-a5c0-9d8e8f566d00 · outbound

This paper cites On the ethical considerations of text simplification,.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences On the ethical considerations of text simplification,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:07:20.954845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:07:20.749972Z digest=sha256:f2b9b5f3ac0b5ab4664eb987be49fd4ee21b934f54338f90d2850263a1295b2a

Observation 08d28c22-7f9f-4d74-bd0a-99b51cd40e36 · outbound

This paper cites Can knowledge graphs reduce hallucinations in LLMs? A survey,.

A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentences Can knowledge graphs reduce hallucinations in LLMs? A survey,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:07:20.919987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:07:20.752825Z digest=sha256:95576c36bc7fb10f147593a255b5ed543dce153c17b03f10238f714c6ec097b0

Pith citing papers

No inbound Pith citation observations are available.