Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution | Paper Citation Record

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

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This paper cites STaR-GATE: Teaching Language Models to Ask Clarifying Questions.

Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution STaR-GATE: Teaching Language Models to Ask Clarifying Questions

Reference 2

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

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This paper cites Levendowski, Michelle N.

Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Levendowski, Michelle N

Reference 4

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

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This paper cites Koretsky, Maya Willey, Chelsea X.

Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Koretsky, Maya Willey, Chelsea X

Reference 6

Resolution: verified exact; doi, observed 2026-08-06T00:20:38.376524Z

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

Reference 7

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This paper cites Language Models are Few-Shot Learners.

Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Language Models are Few-Shot Learners

Reference 8

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This paper cites A Systematic Review on Prompt Engineering in Large Language Models for K-12 STEM Education.

Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution A Systematic Review on Prompt Engineering in Large Language Models for K-12 STEM Education

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T00:20:35.403847Z

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This paper cites A Survey on LLM-based Multi-Agent System: Recent Advances and New Frontiers in Application.

Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution A Survey on LLM-based Multi-Agent System: Recent Advances and New Frontiers in Application

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T00:20:35.517079Z

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This paper cites an unresolved cited work.

Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

Reference 11

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Observation 10ed5fe0-b13a-4616-94cc-6b6afd4f2145 · outbound

This paper cites Reasoning While Asking: Transforming Reasoning Large Language Models from Passive Solvers to Proactive Inquirers.

Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Reasoning While Asking: Transforming Reasoning Large Language Models from Passive Solvers to Proactive Inquirers

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-06T00:20:38.242625Z

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This paper cites an unresolved cited work.

Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

Reference 13

Resolution: verified exact; doi, observed 2026-08-06T00:20:38.230973Z

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This paper cites 1988.Statistical Power Analysis for the Behavioral Sciences(2nd ed.).

Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution 1988.Statistical Power Analysis for the Behavioral Sciences(2nd ed.)

Reference 14

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This paper cites Towards Detecting Prompt Knowledge Gaps for Improved LLM-guided Issue Resolution.

Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Towards Detecting Prompt Knowledge Gaps for Improved LLM-guided Issue Resolution

Reference 15

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

Reference 16

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This paper cites ChatGPT produces more "lazy" thinkers: Evidence of cognitive engagement decline.

Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution ChatGPT produces more "lazy" thinkers: Evidence of cognitive engagement decline

Reference 17

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

Reference 18

Resolution: verified exact; doi, observed 2026-08-06T00:20:38.207134Z

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This paper cites Smith, Harrison Leong, Linda McEvoy, Susan Whitfield, Robert Du, and Georgia Rush.

Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Smith, Harrison Leong, Linda McEvoy, Susan Whitfield, Robert Du, and Georgia Rush

Reference 19

Resolution: verified exact; doi, observed 2026-08-06T00:20:38.198584Z

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This paper cites Engemann, Daniel Strohmeier, Christian Brodbeck, Lauri Parkkonen, and Matti S.

Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Engemann, Daniel Strohmeier, Christian Brodbeck, Lauri Parkkonen, and Matti S

Reference 20

Resolution: verified exact; doi, observed 2026-08-06T00:20:38.190337Z

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This paper cites Chawla, Olaf Wiest, and Xiangliang Zhang.

Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Chawla, Olaf Wiest, and Xiangliang Zhang

Reference 21

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Hart and Lowell E

Reference 23

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework

Reference 24

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Large Language Models are Zero-Shot Reasoners

Reference 29

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task

Reference 31

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution LLMs Get Lost In Multi-Turn Conversation

Reference 32

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution ALFA: Aligning LLMs to Ask Good Questions A Case Study in Clinical Reasoning

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Effects of Prompt Length on Domain-specific Tasks for Large Language Models

Reference 37

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Self-Refine: Iterative Refinement with Self-Feedback

Reference 39

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Learning to Ask Informative Questions: Enhancing LLMs with Preference Optimization and Expected Information Gain

Reference 40

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Training language models to follow instructions with human feedback

Reference 41

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution O’Brien, Carrie J

Reference 42

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Thinking Assistants: LLM-Based Conversational Assistants that Help Users Think By Asking rather than Answering

Reference 43

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

Reference 44

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Pope, Edward H

Reference 45

Resolution: verified exact; doi, observed 2026-08-06T00:20:38.039835Z

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This paper cites Automatic Prompt Optimization with "Gradient Descent" and Beam Search.

Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Automatic Prompt Optimization with "Gradient Descent" and Beam Search

Reference 46

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

Reference 47

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This paper cites A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications.

Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications

Reference 48

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution 2011.A Practical Guide to the System Usability Scale: Background, Benchmarks and Best Practices

Reference 49

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution The Prompt Report: A Systematic Survey of Prompt Engineering Techniques

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-06T00:20:37.219863Z

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

Reference 51

Resolution: verified exact; doi, observed 2026-08-06T00:20:38.007634Z

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

Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Multi-Agent Collaboration Mechanisms: A Survey of LLMs

Reference 52

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution A Survey of Prompt Engineering Methods in Large Language Models for Different NLP Tasks

Reference 53

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Learning to Ask: When LLM Agents Meet Unclear Instruction

Reference 54

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 55

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 56

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Observation 6439b56e-27ff-4135-b9f2-ada3c97ed64b · outbound

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

Reference 57

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Observation e420672b-62c2-476d-8ba5-d7c7c9659494 · outbound

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Williams, Genevieve M

Reference 58

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-06T00:20:37.245463Z

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Observation ea04091a-e0ec-4567-b5ac-e2922337ad2f · outbound

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-06T00:20:37.254299Z

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Observation 624b2d22-cde5-4cb8-8157-573dcaf8aaad · outbound

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Large Language Models as Optimizers

Reference 61

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Observation a9295706-658f-4a9b-b10b-01cee6bc71d0 · outbound

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution A Survey of Large Language Model Agents for Question Answering

Reference 62

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Observation 61b6ceab-bf2a-42c4-8dde-cd4473a16abe · outbound

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution ReAct: Synergizing Reasoning and Acting in Language Models

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-06T00:20:37.257303Z

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Dumais, Nick Craswell, Paul N

Reference 64

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Observation 6126bc71-7260-4827-8df7-70d94a39e5b0 · outbound

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution TextGrad: Automatic "Differentiation" via Text

Reference 65

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Source-reported events for the cited work

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Observation 05acbba8-9c78-4ed7-a154-24f63d8042fb · outbound

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Ask-before-Plan: Proactive Language Agents for Real-World Planning

Reference 66

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Zamfirescu-Pereira, Richmond Y

Reference 67

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Least-to-Most Prompting Enables Complex Reasoning in Large Language Models

Reference 68

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Observation ecc422df-f879-43b4-b52d-453a57a8568f · outbound

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Unresolved cited work

Reference 69

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Observation 5461a5c5-295f-4476-b25e-701b4c4bcb1a · outbound

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution A Survey of Large Language Models

Reference 70

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Large Language Models Are Human-Level Prompt Engineers

Reference 72

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Observation d6bc15b1-4a8d-483e-8281-4c0205229f2b · outbound

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Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution Universal Self-Consistency for Large Language Model Generation

Reference 2023

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