Critical Confabulation: Can LLMs Hallucinate for Social Good?

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sui, Peiqi, Duede, Eamon, Long, Hoyt, So, Richard Jean
Format:	Preprint
Published:	2025
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Confabulation: The Surprising Value of Large Language Model Hallucinations
by: Sui, Peiqi, et al.
Published: (2024)

Spoiler Alert: Narrative Forecasting as a Metric for Tension in LLM Storytelling
by: Sui, Peiqi, et al.
Published: (2026)

Why Slop Matters
by: Kommers, Cody, et al.
Published: (2025)

LLMs Exhibit Significantly Lower Uncertainty in Creative Writing Than Professional Writers
by: Sui, Peiqi
Published: (2026)

The Representational Status of Deep Learning Models
by: Duede, Eamon
Published: (2023)

Deep Learning Opacity in Scientific Discovery
by: Duede, Eamon
Published: (2022)

Anchored Confabulation: Partial Evidence Non-Monotonically Amplifies Confident Hallucination in LLMs
by: Lathkar, Ashish Balkishan
Published: (2026)

Can LLMs Detect Their Confabulations? Estimating Reliability in Uncertainty-Aware Language Models
by: Zhou, Tianyi, et al.
Published: (2025)

Synthetic Fluency: Hallucinations, Confabulations, and the Creation of Irish Words in LLM-Generated Translations
by: Castilho, Sheila, et al.
Published: (2025)

Confabulations from ACL Publications (CAP): A Dataset for Scientific Hallucination Detection
by: Gamba, Federica, et al.
Published: (2025)

AI and the Decentering of Disciplinary Creativity
by: Duede, Eamon
Published: (2025)

Apriori Knowledge in an Era of Computational Opacity: The Role of AI in Mathematical Discovery
by: Duede, Eamon, et al.
Published: (2024)

Can LLMs Detect Their Own Hallucinations?
by: Kadotani, Sora, et al.
Published: (2025)

KRISTEVA: Close Reading as a Novel Task for Benchmarking Interpretive Reasoning
by: Sui, Peiqi, et al.
Published: (2025)

Predictable Confabulations: Factual Recall by LLMs Scales with Model Size and Topic Frequency
by: Smith, Matthew L., et al.
Published: (2026)

Can LLMs Ask Good Questions?
by: Zhang, Yueheng, et al.
Published: (2025)

Can GNN be Good Adapter for LLMs?
by: Huang, Xuanwen, et al.
Published: (2024)

The Paradox of Collective Certainty in Science
by: Duede, Eamon, et al.
Published: (2024)

ReFACT: A Benchmark for Scientific Confabulation Detection with Positional Error Annotations
by: Wang, Yindong, et al.
Published: (2025)

Can Hallucinations Help? Boosting LLMs for Drug Discovery
by: Yuan, Shuzhou, et al.
Published: (2025)

Can LLM be a Good Path Planner based on Prompt Engineering? Mitigating the Hallucination for Path Planning
by: Deng, Hourui, et al.
Published: (2024)

Position: LLMs Can be Good Tutors in English Education
by: Ye, Jingheng, et al.
Published: (2025)

Prompt-Guided Internal States for Hallucination Detection of Large Language Models
by: Zhang, Fujie, et al.
Published: (2024)

Can LLMs Detect Intrinsic Hallucinations in Paraphrasing and Machine Translation?
by: Gogoulou, Evangelia, et al.
Published: (2025)

Can Knowledge Graphs Reduce Hallucinations in LLMs? : A Survey
by: Agrawal, Garima, et al.
Published: (2023)

Bridging External and Parametric Knowledge: Mitigating Hallucination of LLMs with Shared-Private Semantic Synergy in Dual-Stream Knowledge
by: Sui, Yi, et al.
Published: (2025)

Can LLMs be Good Graph Judge for Knowledge Graph Construction?
by: Huang, Haoyu, et al.
Published: (2024)

Generative AI & Fictionality: How Novels Power Large Language Models
by: Roland, Edwin, et al.
Published: (2026)

A correspondence problem for mathematical proof
by: DeDeo, Simon, et al.
Published: (2026)

Reducing Hallucinations in Entity Abstract Summarization with Facts-Template Decomposition
by: Zhu, Fangwei, et al.
Published: (2024)

FoundationalASSIST: An Educational Dataset for Foundational Knowledge Tracing and Pedagogical Grounding of LLMs
by: Worden, Eamon, et al.
Published: (2026)

Persona Inconstancy in Multi-Agent LLM Collaboration: Conformity, Confabulation, and Impersonation
by: Baltaji, Razan, et al.
Published: (2024)

What Does AI Do for Cultural Interpretation? A Randomized Experiment on Close Reading Poems with Exposure to AI Interpretation
by: Zhi, Jiayin, et al.
Published: (2026)

When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs
by: Kamoi, Ryo, et al.
Published: (2024)

Can Knowledge Editing Really Correct Hallucinations?
by: Huang, Baixiang, et al.
Published: (2024)

Shared Imagination: LLMs Hallucinate Alike
by: Zhou, Yilun, et al.
Published: (2024)

Meaning Is Not A Metric: Using LLMs to make cultural context legible at scale
by: Kommers, Cody, et al.
Published: (2025)

TextQuests: How Good are LLMs at Text-Based Video Games?
by: Phan, Long, et al.
Published: (2025)

Can LLMs Generate Good Stories? Insights and Challenges from a Narrative Planning Perspective
by: Wang, Yi, et al.
Published: (2025)

Med-HEAL: Analyzing and Mitigating Hallucinations in Medical LLMs with Hallucination-Aware In-Context Learning
by: Liao, Yiming, et al.
Published: (2026)