Copertina

Hallucination or Creativity: How to Evaluate AI-Generated Scientific Stories?

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Argese, Alex, Lisena, Pasquale, Troncy, Raphaël
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Computation and Language Artificial Intelligence I.2.7
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Integrating Causal Reasoning into Automated Fact-Checking
di: Rebboud, Youssra, et al.
Pubblicazione: (2025)

Evaluating the Efficacy of Hybrid Deep Learning Models in Distinguishing AI-Generated Text
di: Oketunji, Abiodun Finbarrs
Pubblicazione: (2023)

How to Evaluate Medical AI
di: Kopanichuk, Ilia, et al.
Pubblicazione: (2025)

MedHal: An Evaluation Dataset for Medical Hallucination Detection
di: Mehenni, Gaya, et al.
Pubblicazione: (2025)

Detecting Hallucinations in Graph Retrieval-Augmented Generation via Attention Patterns and Semantic Alignment
di: Li, Shanghao, et al.
Pubblicazione: (2025)

Can AI Extract Antecedent Factors of Human Trust in AI? An Application of Information Extraction for Scientific Literature in Behavioural and Computer Sciences
di: McGrath, Melanie, et al.
Pubblicazione: (2024)

Listen to the Layers: Mitigating Hallucinations with Inter-Layer Disagreement
di: Subbalakshmi, Koduvayur, et al.
Pubblicazione: (2026)

RomanLens: The Role Of Latent Romanization In Multilinguality In LLMs
di: Saji, Alan, et al.
Pubblicazione: (2025)

Text-Based Approaches to Item Difficulty Modeling in Large-Scale Assessments: A Systematic Review
di: Peters, Sydney, et al.
Pubblicazione: (2025)

StyloAI: Distinguishing AI-Generated Content with Stylometric Analysis
di: Opara, Chidimma
Pubblicazione: (2024)

TRACE: Trajectory Correction from Cross-layer Evidence for Hallucination Reduction
di: Ranade, Tej Sanibh
Pubblicazione: (2026)

German also Hallucinates! Inconsistency Detection in News Summaries with the Absinth Dataset
di: Mascarell, Laura, et al.
Pubblicazione: (2024)

Red Teaming for Large Language Models At Scale: Tackling Hallucinations on Mathematics Tasks
di: Buszydlik, Aleksander, et al.
Pubblicazione: (2023)

Seeing Through the Fog: A Cost-Effectiveness Analysis of Hallucination Detection Systems
di: Thomas, Alexander, et al.
Pubblicazione: (2024)

PerCul: A Story-Driven Cultural Evaluation of LLMs in Persian
di: Monazzah, Erfan Moosavi, et al.
Pubblicazione: (2025)

Detecting AI-Generated Texts in Cross-Domains
di: Zhou, You, et al.
Pubblicazione: (2024)

PrivacyBench: A Conversational Benchmark for Evaluating Privacy in Personalized AI
di: Mukhopadhyay, Srija, et al.
Pubblicazione: (2025)

Fine-Tuned Large Language Models for Logical Translation: Reducing Hallucinations with Lang2Logic
di: Pan, Muyu, et al.
Pubblicazione: (2025)

Machine Translation Hallucination Detection for Low and High Resource Languages using Large Language Models
di: Benkirane, Kenza, et al.
Pubblicazione: (2024)

Spotlights and Blindspots: Evaluating Machine-Generated Text Detection
di: Stowe, Kevin, et al.
Pubblicazione: (2026)

On the Effectiveness of LLM-Specific Fine-Tuning for Detecting AI-Generated Text
di: Gromadzki, Michał, et al.
Pubblicazione: (2026)

Blessing or curse? A survey on the Impact of Generative AI on Fake News
di: Loth, Alexander, et al.
Pubblicazione: (2024)

Enigme: Generative Text Puzzles for Evaluating Reasoning in Language Models
di: Hawkins, John
Pubblicazione: (2025)

AEyeDE: An Attention-Based Attribution Framework for AI-Generated Text Detection
di: Nourbakhsh, Aria, et al.
Pubblicazione: (2026)

Evaluating Explainable AI Attribution Methods in Neural Machine Translation via Attention-Guided Knowledge Distillation
di: Nourbakhsh, Aria, et al.
Pubblicazione: (2026)

Generative Active Testing: Efficient LLM Evaluation via Proxy Task Adaptation
di: Ramakrishnan, Aashish Anantha, et al.
Pubblicazione: (2026)

Cetvel: A Unified Benchmark for Evaluating Language Understanding, Generation and Cultural Capacity of LLMs for Turkish
di: Er, Yakup Abrek, et al.
Pubblicazione: (2025)

Fine-Tuned 'Small' LLMs (Still) Significantly Outperform Zero-Shot Generative AI Models in Text Classification
di: Bucher, Martin Juan José, et al.
Pubblicazione: (2024)

How Clued up are LLMs? Evaluating Multi-Step Deductive Reasoning in a Text-Based Game Environment
di: Ansell, Rebecca, et al.
Pubblicazione: (2026)

Reducing Hallucinations in Summarization via Reinforcement Learning with Entity Hallucination Index
di: Katwe, Praveenkumar, et al.
Pubblicazione: (2025)

Vibe Code Bench: Evaluating AI Models on End-to-End Web Application Development
di: Tran, Hung, et al.
Pubblicazione: (2026)

Towards Lighter and Robust Evaluation for Retrieval Augmented Generation
di: Ispas, Alex-Razvan, et al.
Pubblicazione: (2025)

Presumed Cultural Identity: How Names Shape LLM Responses
di: Pawar, Siddhesh, et al.
Pubblicazione: (2025)

Exploring the Structure of AI-Induced Language Change in Scientific English
di: Galpin, Riley, et al.
Pubblicazione: (2025)

Detecting Hallucinations in Large Language Model Generation: A Token Probability Approach
di: Quevedo, Ernesto, et al.
Pubblicazione: (2024)

Old Habits Die Hard: How Conversational History Geometrically Traps LLMs
di: Simhi, Adi, et al.
Pubblicazione: (2026)

A Multi-Task, Multi-Modal Approach for Predicting Categorical and Dimensional Emotions
di: Ispas, Alex-Răzvan, et al.
Pubblicazione: (2023)

Serialisation Strategy Matters: How FHIR Data Format Affects LLM Medication Reconciliation
di: Pator, Sanjoy
Pubblicazione: (2026)

How Instruction-Tuning Imparts Length Control: A Cross-Lingual Mechanistic Analysis
di: Rocchetti, Elisabetta, et al.
Pubblicazione: (2025)

UA-Legal-Bench: A Benchmark for Evaluating Large Language Models on Ukrainian Legal Reasoning
di: Ovcharov, Volodymyr
Pubblicazione: (2026)