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Paper Citation Record · LEDGER

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning

As of 10 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2506.16064.

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

pith.paper-citation-record.v1
2506.16064 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:49:28.160893Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

32 of 32 outbound references displayed

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External citation measurements

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Outbound references

Observation 28ea1356-663e-41cb-9525-3ed0e474facf · outbound

This paper cites GPT-4 Technical Report.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning GPT-4 Technical Report

Reference 1

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Observation 4ff0c8c8-be83-4ba8-8b6a-b68c897b9f97 · outbound

This paper cites The Llama 3 Herd of Models.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning The Llama 3 Herd of Models

Reference 2

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Observation 5efd11d7-5f3d-400f-8c5b-83a7558c6bb1 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning On the Opportunities and Risks of Foundation Models

Reference 3

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Observation 64ac7061-5aec-4d5e-9e5f-50fe864616af · outbound

This paper cites Aligning ai with shared human values,.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning Aligning ai with shared human values,

Reference 4

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Observation 14bb5523-c901-4ddc-8363-377d65810812 · outbound

This paper cites Hon- estllm: Toward an honest and helpful large language model,.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning Hon- estllm: Toward an honest and helpful large language model,

Reference 5

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Observation a5b4ac83-6b89-4b9f-9b4b-acdaeb5f7af0 · outbound

This paper cites AI Alignment: A Comprehensive Survey.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning AI Alignment: A Comprehensive Survey

Reference 6

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Observation 89ccfad5-a249-4a62-b4f2-1e0eaa2b2ccb · outbound

This paper cites A General Language Assistant as a Laboratory for Alignment.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning A General Language Assistant as a Laboratory for Alignment

Reference 7

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Observation 2c1a9a7e-b525-4735-b168-e2522d6f0b28 · outbound

This paper cites A Survey of Hallucination in Large Foundation Models.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning A Survey of Hallucination in Large Foundation Models

Reference 8

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Observation 8712f5f9-4c4e-492b-8b6d-989ca7ade56e · outbound

This paper cites Towards Understanding Sycophancy in Language Models.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning Towards Understanding Sycophancy in Language Models

Reference 9

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Observation d9891930-cd8c-4393-ae6f-98d9994f0a79 · outbound

This paper cites Language Models (Mostly) Know What They Know.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning Language Models (Mostly) Know What They Know

Reference 10

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Observation d9aca484-207e-47d6-b109-191c6d095f70 · outbound

This paper cites Emergent Abilities of Large Language Models.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning Emergent Abilities of Large Language Models

Reference 11

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Observation de5a92b4-f639-4ba0-8086-4247c877ddae · outbound

This paper cites I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench

Reference 12

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Observation 143078ab-b3ca-4d54-b8c7-eb76fae0b670 · outbound

This paper cites TrustLLM: Trustworthiness in Large Language Models.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning TrustLLM: Trustworthiness in Large Language Models

Reference 13

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Observation 3995264e-ac85-43b4-8c73-c5a42d2b2e2f · outbound

This paper cites When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour

Reference 14

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Observation 2723480f-5c91-4244-a750-d51f50295fd6 · outbound

This paper cites Simple synthetic data reduces sycophancy in large language models.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning Simple synthetic data reduces sycophancy in large language models

Reference 15

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Observation 6f0e755e-f9ff-47d8-a4e9-3d4ddf1288b5 · outbound

This paper cites Aligning language models to explicitly handle ambigu- ity,.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning Aligning language models to explicitly handle ambigu- ity,

Reference 16

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Source-reported events for the cited work

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Observation 89bbb8ac-2146-4d06-9967-12c84ee4ce37 · outbound

This paper cites MM- LLMs: Recent advances in MultiModal large language models,.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning MM- LLMs: Recent advances in MultiModal large language models,

Reference 17

Resolution
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Observation 0802d4cf-a322-40d8-a4f2-800a760f0ace · outbound

This paper cites Large language models are human-level prompt engi- neers,.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning Large language models are human-level prompt engi- neers,

Reference 18

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Observation 5aa7f312-9557-480a-baf5-1b643c67e2cc · outbound

This paper cites Promptchainer: Chaining large language model prompts through visual programming,.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning Promptchainer: Chaining large language model prompts through visual programming,

Reference 19

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Observation cc580e42-2705-4af1-88e9-bad736310cfe · outbound

This paper cites Least-to- most prompting enables complex reasoning in large language models,.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning Least-to- most prompting enables complex reasoning in large language models,

Reference 20

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Observation d280db7d-c7c9-40af-b87b-61aeb8fa92d5 · outbound

This paper cites Lan- guage models are few-shot learners,.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning Lan- guage models are few-shot learners,

Reference 21

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Observation 2d19535e-537b-44d3-a1c0-5baabd0dd41d · outbound

This paper cites Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?

Reference 22

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Observation 4de369e6-3632-407f-9402-c6034c701d3f · outbound

This paper cites BERT: Pre-training of deep bidi- rectional transformers for language under- standing,.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning BERT: Pre-training of deep bidi- rectional transformers for language under- standing,

Reference 23

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Observation 30dc1848-7242-49e6-b662-f1118945e35c · outbound

This paper cites A survey on in-context learning,.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning A survey on in-context learning,

Reference 24

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Source-reported events for the cited work

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Observation 2904bb10-59de-4e01-865a-18be881d076d · outbound

This paper cites Let’s verify step by step,.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning Let’s verify step by step,

Reference 25

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Observation 21dd06a7-6520-457c-af1c-3002e2791125 · outbound

This paper cites Self-refine: Iterative refinement with self- feedback,.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning Self-refine: Iterative refinement with self- feedback,

Reference 26

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Source-reported events for the cited work

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Observation 350ca5bf-1c98-4b0a-ad2e-bc24e37dffcf · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning,.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning Reflexion: Language agents with verbal reinforcement learning,

Reference 27

Resolution
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Observation 60ed9485-caa2-49ba-8bf8-81092e37f800 · outbound

This paper cites Self-criticism: Aligning large language models with their un- derstanding of helpfulness, honesty, and harm- lessness,.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning Self-criticism: Aligning large language models with their un- derstanding of helpfulness, honesty, and harm- lessness,

Reference 28

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Observation 99cd340a-6cc2-498e-83b3-4a484bf7edb4 · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning Constitutional AI: Harmlessness from AI Feedback

Reference 29

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Observation 72fc8101-bfff-4e66-bb0d-1963c01de7c0 · outbound

This paper cites Openai o3-mini system card,.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning Openai o3-mini system card,

Reference 31

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Source-reported events for the cited work

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Observation 19d01ae5-b8e9-44e1-b1b5-b287e2b049b6 · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning Gemma: Open Models Based on Gemini Research and Technology

Reference 32

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Observation 54c7797c-b599-4aa4-b584-1cb09805e80a · outbound

This paper cites GPT-4o System Card.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning GPT-4o System Card

Reference 2024

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Pith citing papers

No inbound Pith citation observations are available.