Paper Citation Record · LEDGER

Efficient Prompting Methods for Large Language Models: A Survey

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 25 inbound Pith citation observations for arXiv:2404.01077.

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

pith.paper-citation-record.v1
2404.01077 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 25 of 25 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:08:52.411025Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T09:59:45.539148Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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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 f934b144-9853-40ae-86b3-7094c03a3f45 · inbound

From Cool Demos to Production-Ready FMware: Core Challenges and a Technology Roadmap cites this paper.

From Cool Demos to Production-Ready FMware: Core Challenges and a Technology Roadmap Efficient Prompting Methods for Large Language Models: A Survey

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-23T19:08:20.945968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 309ee8fd-f074-4d17-a9db-64bfc3904c7d · inbound

Probing the limitations of multimodal language models for chemistry and materials research cites this paper.

Probing the limitations of multimodal language models for chemistry and materials research Efficient Prompting Methods for Large Language Models: A Survey

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-12T12:45:35.752716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7bb2421c-4cee-4721-ba00-14ddf82b905f · inbound

Understanding the Fundamental Design Decisions of Retrieval-Augmented Generation Systems cites this paper.

Understanding the Fundamental Design Decisions of Retrieval-Augmented Generation Systems Efficient Prompting Methods for Large Language Models: A Survey

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T10:14:22.056479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f7284e3-cf36-430e-a4a4-07174ad2e3d4 · inbound

Knowledge Graphs are all you need: Leveraging KGs in Physics Question Answering cites this paper.

Knowledge Graphs are all you need: Leveraging KGs in Physics Question Answering Efficient Prompting Methods for Large Language Models: A Survey

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T20:46:15.340211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 890121e3-c6d7-4dea-bd4c-dd7f6212de87 · inbound

Eliciting Causal Abilities in Large Language Models for Reasoning Tasks cites this paper.

Eliciting Causal Abilities in Large Language Models for Reasoning Tasks Efficient Prompting Methods for Large Language Models: A Survey

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T11:44:33.004953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62b1c3a9-b2da-4963-9c58-738f6d1cc788 · inbound

Foundations of Large Language Models cites this paper.

Foundations of Large Language Models Efficient Prompting Methods for Large Language Models: A Survey

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T20:14:58.617622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 801e1e14-6cfa-4c15-8837-ade8c9730517 · inbound

When Dimensionality Hurts: The Role of LLM Embedding Compression for Noisy Regression Tasks cites this paper.

When Dimensionality Hurts: The Role of LLM Embedding Compression for Noisy Regression Tasks Efficient Prompting Methods for Large Language Models: A Survey

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-09T13:02:53.117215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e6e00ad-ff19-4ae1-a808-b64054722cf7 · inbound

CODEPROMPTZIP: Code-specific Prompt Compression for Retrieval-Augmented Generation in Coding Tasks with LMs cites this paper.

CODEPROMPTZIP: Code-specific Prompt Compression for Retrieval-Augmented Generation in Coding Tasks with LMs Efficient Prompting Methods for Large Language Models: A Survey

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-23T02:02:23.065100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ec35c364-ecb8-402f-9f8c-6f8adb7a59e4 · inbound

Balancing Content Size in RAG-Text2SQL System cites this paper.

Balancing Content Size in RAG-Text2SQL System Efficient Prompting Methods for Large Language Models: A Survey

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.870841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90d314b5-2de2-4124-bc0d-dc933dc81e8b · inbound

Give LLMs a Security Course: Securing Retrieval-Augmented Code Generation via Knowledge Injection cites this paper.

Give LLMs a Security Course: Securing Retrieval-Augmented Code Generation via Knowledge Injection Efficient Prompting Methods for Large Language Models: A Survey

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-16T11:08:52.411025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a60ca776-5527-44d1-9f42-342092d3dbba · inbound

Beyond Hard and Soft: Hybrid Context Compression for Balancing Local and Global Information Retention cites this paper.

Beyond Hard and Soft: Hybrid Context Compression for Balancing Local and Global Information Retention Efficient Prompting Methods for Large Language Models: A Survey

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T15:15:52.359951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7e33eb9-ae13-4d9e-abf5-7371e8ae0dae · inbound

Improved Representation Steering for Language Models cites this paper.

Improved Representation Steering for Language Models Efficient Prompting Methods for Large Language Models: A Survey

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T13:51:28.142183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89b38246-6a44-40ee-8285-e49792d6e606 · inbound

MAARTA:Multi-Agentic Adaptive Radiology Teaching Assistant cites this paper.

MAARTA:Multi-Agentic Adaptive Radiology Teaching Assistant Efficient Prompting Methods for Large Language Models: A Survey

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T23:59:04.118839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fc4d2e9-804c-448a-a848-083968139365 · inbound

A Modular Taxonomy for Hate Speech Definitions and Its Impact on Zero-Shot LLM Classification Performance cites this paper.

A Modular Taxonomy for Hate Speech Definitions and Its Impact on Zero-Shot LLM Classification Performance Efficient Prompting Methods for Large Language Models: A Survey

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-06T23:21:35.925270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5fca162a-3463-441f-8eb9-a4c88a2b70b0 · inbound

SI-Agent: An Agentic Framework for Feedback-Driven Generation and Tuning of Human-Readable System Instructions for Large Language Models cites this paper.

SI-Agent: An Agentic Framework for Feedback-Driven Generation and Tuning of Human-Readable System Instructions for Large Language Models Efficient Prompting Methods for Large Language Models: A Survey

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T20:21:21.987576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0888cbf8-91aa-4517-a4cf-70e55c111605 · inbound

Step-level Verifier-guided Hybrid Test-Time Scaling for Large Language Models cites this paper.

Step-level Verifier-guided Hybrid Test-Time Scaling for Large Language Models Efficient Prompting Methods for Large Language Models: A Survey

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T15:37:24.863525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be3248ae-9467-4c0a-8a4d-dc2942555d09 · inbound

From Prompt to Pipeline: Large Language Models for Scientific Workflow Development in Bioinformatics cites this paper.

From Prompt to Pipeline: Large Language Models for Scientific Workflow Development in Bioinformatics Efficient Prompting Methods for Large Language Models: A Survey

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-15T17:52:52.700374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f454de97-b3ee-4342-982d-cf58491fce0f · inbound

Assessing Coherency and Consistency of Code Execution Reasoning by Large Language Models cites this paper.

Assessing Coherency and Consistency of Code Execution Reasoning by Large Language Models Efficient Prompting Methods for Large Language Models: A Survey

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-18T06:00:57.265483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6276c615-b950-4740-8e91-c94d9da3544e · inbound

Knowing How to Edit: Reliable Evaluation Signals for Diagnosing and Optimizing Prompts at Query Level cites this paper.

Knowing How to Edit: Reliable Evaluation Signals for Diagnosing and Optimizing Prompts at Query Level Efficient Prompting Methods for Large Language Models: A Survey

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T20:29:13.345645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44ac342f-3907-4345-818d-5e929550c85a · inbound

Towards Efficient and Robust Linguistic Emotion Diagnosis for Mental Health via Multi-Agent Instruction Refinement cites this paper.

Towards Efficient and Robust Linguistic Emotion Diagnosis for Mental Health via Multi-Agent Instruction Refinement Efficient Prompting Methods for Large Language Models: A Survey

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T09:35:18.428819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2d0ff71-b605-4517-bd5b-e4a14f828eab · inbound

PragLocker: Protecting Agent Intellectual Property in Untrusted Deployments via Non-Portable Prompts cites this paper.

PragLocker: Protecting Agent Intellectual Property in Untrusted Deployments via Non-Portable Prompts Efficient Prompting Methods for Large Language Models: A Survey

Reference 120

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:21:10.847340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ff6ee498-8da4-4b7c-bf8c-178e807aaf37 · inbound

PragLocker: Protecting Agent Intellectual Property in Untrusted Deployments via Non-Portable Prompts cites this paper.

PragLocker: Protecting Agent Intellectual Property in Untrusted Deployments via Non-Portable Prompts Efficient Prompting Methods for Large Language Models: A Survey

Reference 120

Resolution: verified exact; arxiv_id, observed 2026-05-20T23:33:50.569226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 145e7b85-72ff-48b1-8e19-bc0ca9040d65 · inbound

Understanding Conversational Patterns in Multi-agent Programming: A Case Study on Fibonacci Game Development cites this paper.

Understanding Conversational Patterns in Multi-agent Programming: A Case Study on Fibonacci Game Development Efficient Prompting Methods for Large Language Models: A Survey

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-06-30T15:04:46.355124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation de4f85ee-2045-4e64-9417-a30294b2e586 · inbound

CRAFT: Cost-aware Refinement And Front-aware Tuning of Prompts cites this paper.

CRAFT: Cost-aware Refinement And Front-aware Tuning of Prompts Efficient Prompting Methods for Large Language Models: A Survey

Reference 220

Resolution: verified exact; arxiv_id, observed 2026-07-02T07:46:46.418282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d5647f70-ad13-453d-b760-939a6784146d · inbound

MAS-PromptBench: When Does Prompt Optimization Improve Multi-Agent LLM Systems? cites this paper.

MAS-PromptBench: When Does Prompt Optimization Improve Multi-Agent LLM Systems? Efficient Prompting Methods for Large Language Models: A Survey

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-07-04T09:59:45.541220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.