PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability | Paper Citation Record

Observation 51b05c06-dacf-4552-8786-93e3f6698fbf · outbound

This paper cites Language models are few-shot learners,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Language models are few-shot learners,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.184383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a54c30fe-3cc4-4341-b89a-6cd2fd771d9a · outbound

This paper cites Privacy- preserving synthetic data generation for healthcare applications,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Privacy- preserving synthetic data generation for healthcare applications,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.190658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9685191d-7864-4341-99b6-d94564395fb5 · outbound

This paper cites Synthea: An approach, method, and software mechanism for generating synthetic patients and the synthetic electronic health care record,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Synthea: An approach, method, and software mechanism for generating synthetic patients and the synthetic electronic health care record,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.196090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation badb1f64-3409-4cb4-a19e-defab045c81b · outbound

This paper cites On the dangers of stochastic parrots: Can language models be too big?.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability On the dangers of stochastic parrots: Can language models be too big?

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.202215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 855dc877-0463-4e20-96c1-e710ae0c6554 · outbound

This paper cites Algorithmic injustice: A relational ethics approach,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Algorithmic injustice: A relational ethics approach,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.207541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7953dfe-78f6-416f-ad03-67c6114dbbe3 · outbound

This paper cites Ai4peoplean ethical framework for a good ai society: Opportunities, risks, principles, and recommendations,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Ai4peoplean ethical framework for a good ai society: Opportunities, risks, principles, and recommendations,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.212269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01e8756f-a79f-4ec2-be56-8d08bfd064ae · outbound

This paper cites Livingstone, G.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Livingstone, G

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.217488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 242acd1c-16c2-4620-a516-be2eef641e4a · outbound

This paper cites Eubanks,Automating Inequality: How High-Tech Tools Profile, Po- lice, and Punish the Poor.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Eubanks,Automating Inequality: How High-Tech Tools Profile, Po- lice, and Punish the Poor

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.221937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a6c2bb9-1950-4c52-bccf-548a6acdd5ea · outbound

This paper cites The misgendering machines: Trans/hci implications of automatic gender recognition,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability The misgendering machines: Trans/hci implications of automatic gender recognition,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.226849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d89cff6b-5ae7-4873-b4d6-ab0ae472b5d6 · outbound

This paper cites Technocolonialism: Digital innovation and data practices in the humanitarian response to refugee crises,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Technocolonialism: Digital innovation and data practices in the humanitarian response to refugee crises,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.231363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7dd72c37-7c2c-4269-bc35-5e1f8c422247 · outbound

This paper cites Under- standing social media disclosures of sexual abuse through the lenses of support seeking and anonymity,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Under- standing social media disclosures of sexual abuse through the lenses of support seeking and anonymity,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.236782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e530ed93-6d07-42c8-adaa-c26d5ac7bc2d · outbound

This paper cites an unresolved cited work.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.241348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f20be303-24d2-401c-93f0-aa9fb875066a · outbound

This paper cites Kukutai and J.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Kukutai and J

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.245953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dde1c9bf-806b-483d-8426-b5da58b6e447 · outbound

This paper cites Language (technology) is power: A critical survey of.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Language (technology) is power: A critical survey of

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.250125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b546674b-8f15-4f28-af94-7e0be6d97025 · outbound

This paper cites Realtoxicityprompts: Evaluating neural toxic degeneration in language models,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Realtoxicityprompts: Evaluating neural toxic degeneration in language models,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.256657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c5c4f04-30de-4a33-80dd-ff244314a268 · outbound

This paper cites Ethical and social risks of harm from Language Models.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Ethical and social risks of harm from Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.262910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52917745-8184-444f-adf8-d4c7b45d9910 · outbound

This paper cites Automated hate speech detection and the problem of offensive language,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Automated hate speech detection and the problem of offensive language,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.268949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab4e8985-104c-4f4c-ae79-43759b328545 · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Constitutional AI: Harmlessness from AI Feedback

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.273817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8bc796a-5bfd-4c8a-ad22-9e2d0045680e · outbound

This paper cites Ethically aligned design: A vision for prioritizing human well-being with autonomous and intelligent systems,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Ethically aligned design: A vision for prioritizing human well-being with autonomous and intelligent systems,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.279135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f8ae808-d8e3-4a2b-8348-c9a6c935103b · outbound

This paper cites Russell and P.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Russell and P

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.283255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ff0a8ba-feb7-46f4-816e-394b1fb332a7 · outbound

This paper cites Training language models to follow instructions with human feedback,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Training language models to follow instructions with human feedback,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.287989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e46a0b3-6614-4f0c-95df-78acbf3ab0da · outbound

This paper cites DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.293716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 998289f1-9afa-408d-a612-374fcf8d94d9 · outbound

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

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Chain-of-thought prompting elicits reasoning in large language models,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.301606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e0c98c7-d38f-4ed4-935c-8331b01171f9 · outbound

This paper cites Tree of thoughts: Deliberate problem solving with large language models,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Tree of thoughts: Deliberate problem solving with large language models,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.307002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 783d4722-f542-4da3-8f32-9cdc05625efe · outbound

This paper cites Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.311700Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f9db9fd-b9b4-46b7-b25d-e707c5a59bf7 · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability ReAct: Synergizing Reasoning and Acting in Language Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.317190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60d7822b-1b20-4a43-b07d-22018ed151d6 · outbound

This paper cites Self-critiquing models for assisting human evaluators.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Self-critiquing models for assisting human evaluators

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.322589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b846f34-1cfc-4503-9748-02ebaccb41ac · outbound

This paper cites Self-Refine: Iterative Refinement with Self-Feedback.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Self-Refine: Iterative Refinement with Self-Feedback

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.327259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 501f1d9a-93f8-455a-8bff-5cac58f1c3b9 · outbound

This paper cites A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.340747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9af085ab-320e-4d79-9102-0e7c1d4dc082 · outbound

This paper cites Prompt programming for large language models: Beyond the few-shot paradigm,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Prompt programming for large language models: Beyond the few-shot paradigm,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.346703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85b3fb20-e237-4f96-862b-49360b356886 · outbound

This paper cites Calibrating noise to sensitivity in private data analysis,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Calibrating noise to sensitivity in private data analysis,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.351865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95dc3264-bf43-40d7-8fd8-0ea8b1cee6f2 · outbound

This paper cites Extracting training data from large language models,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Extracting training data from large language models,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.356428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b9f5122-6fda-4e51-9711-2fa47248fe6b · outbound

This paper cites An empirical survey of the effectiveness of debiasing techniques for pre-trained language models,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability An empirical survey of the effectiveness of debiasing techniques for pre-trained language models,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.360626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2315fb1e-8226-4267-a954-2feebbd3a997 · outbound

This paper cites Racial microaggressions in everyday life: Implications for clinical practice,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Racial microaggressions in everyday life: Implications for clinical practice,

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.365014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f4d94e5-1e06-4269-bffa-274b1927004f · outbound

This paper cites Machine ethics: Creating an ethical intelligent agent,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Machine ethics: Creating an ethical intelligent agent,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.369970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f28054cc-b33b-4899-9b8d-e6fb921efe20 · outbound

This paper cites Wallach and C.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Wallach and C

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.377246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67944279-ae8c-47b7-bdd4-4a310f6221cc · outbound

This paper cites Microsoft presidio,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Microsoft presidio,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.382165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c95aa2a6-219d-414c-a6dd-9816ee7d358f · outbound

This paper cites $W$ state is not the unique ground state of any local Hamiltonian.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability $W$ state is not the unique ground state of any local Hamiltonian

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.386632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ecb638af-6f2a-4645-b199-67e14e93e5fe · outbound

This paper cites A survey on content moderation and its challenges in social media,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability A survey on content moderation and its challenges in social media,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.391550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a87dd40e-6cac-4cfc-a932-52e9933b5091 · outbound

This paper cites k-anonymity: A model for protecting privacy,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability k-anonymity: A model for protecting privacy,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.396368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b75534ac-38b1-41e1-95e5-590746af5290 · outbound

This paper cites Perspective API,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Perspective API,

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.400799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8259be97-7aa6-4e26-b87f-483c48fe1f0c · outbound

This paper cites Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.405226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 329f2ac3-a9f7-49b9-ba73-f5b1f659669b · outbound

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

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Large Language Models Understand and Can be Enhanced by Emotional Stimuli

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.410105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e835d3a-b31c-4dc0-8f4b-10af00bedfe7 · outbound

This paper cites Schuler and A.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Schuler and A

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.414818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7526675e-e85e-4b9e-a12f-c7a100663e37 · outbound

This paper cites Self-Instruct: Aligning Language Models with Self-Generated Instructions.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Self-Instruct: Aligning Language Models with Self-Generated Instructions

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.420262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation acaf6066-a989-4f36-a0c1-9be7e6465d6a · outbound

This paper cites [Online].

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability [Online]

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.424591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f772696a-15cf-43b0-9900-4f8309dda46d · outbound

This paper cites UNHCR refugee data finder,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability UNHCR refugee data finder,

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.428931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebb5df7e-0994-4eae-9426-4809a1b65e8a · outbound

This paper cites Aequitas: A Bias and Fairness Audit Toolkit.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Aequitas: A Bias and Fairness Audit Toolkit

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.432970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ebb927b-ff45-4caf-9299-c4daeac18be9 · outbound

This paper cites Active Retrieval Augmented Generation.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Active Retrieval Augmented Generation

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.437442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 963681bd-0677-4864-9bc4-8c316c747d66 · outbound

This paper cites Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.442012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e43ecbfb-f179-439d-802f-be5b4065a4af · outbound

This paper cites Larger language models do in-context learning differently.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Larger language models do in-context learning differently

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.447841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce84cee4-4bbd-4e1d-b3ce-45d4de16c1af · outbound

This paper cites What Makes Good In-Context Examples for GPT-$3$?.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability What Makes Good In-Context Examples for GPT-$3$?

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.453557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 430ff536-1bce-411d-8c66-33d2efcf0485 · outbound

This paper cites Seer: A knapsack approach to exemplar selection for in-context learning,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Seer: A knapsack approach to exemplar selection for in-context learning,

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.459842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 004dc40c-41cf-49a9-b57a-882d48e8477c · outbound

This paper cites Measuring and Narrowing the Compositionality Gap in Language Models.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Measuring and Narrowing the Compositionality Gap in Language Models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.464769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bb2851b-5e29-465a-85ac-f21a5c917497 · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.469812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c7c7268-8507-4382-bb22-6e070eda3d25 · outbound

This paper cites Large Language Models as Analogical Reasoners.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Large Language Models as Analogical Reasoners

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.474609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0f62acb-81b0-4cbb-bb8d-90eabee4d37d · outbound

This paper cites A Survey of Large Language Models.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability A Survey of Large Language Models

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.479147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae3f27c0-2c16-4194-a6d7-9d9d3c64bf07 · outbound

This paper cites On measuring social biases in sentence encoders,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability On measuring social biases in sentence encoders,

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.483619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f58a9775-2855-4e8a-8fe6-3a6116b2ded1 · outbound

This paper cites Semantics derived au- tomatically from language corpora contain human-like biases,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Semantics derived au- tomatically from language corpora contain human-like biases,

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.488107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f2a04ec-0ce2-4fee-b2fb-aa8238f2e2a8 · outbound

This paper cites Bertscore: Evaluating text generation with bert,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Bertscore: Evaluating text generation with bert,

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.492787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c748baf-4c32-4048-a1f8-97ddbb2867c4 · outbound

This paper cites Co-creation and the new landscapes of design,.

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability Co-creation and the new landscapes of design,

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-04T20:04:29.497733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers