Cover Image

AIRepr: An Analyst-Inspector Framework for Evaluating Reproducibility of LLMs in Data Science

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zeng, Qiuhai, Jin, Claire, Wang, Xinyue, Zheng, Yuhan, Li, Qunhua
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Computation and Language Human-Computer Interaction
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Evaluating Explanations: An Explanatory Virtues Framework for Mechanistic Interpretability -- The Strange Science Part I.ii
by: Ayonrinde, Kola, et al.
Published: (2025)

PREF: Reference-Free Evaluation of Personalised Text Generation in LLMs
by: Fu, Xiao, et al.
Published: (2025)

Model-in-the-Loop (MILO): Accelerating Multimodal AI Data Annotation with LLMs
by: Wang, Yifan, et al.
Published: (2024)

Evaluation of LLMs-based Hidden States as Author Representations for Psychological Human-Centered NLP Tasks
by: Soni, Nikita, et al.
Published: (2025)

DigiData: Training and Evaluating General-Purpose Mobile Control Agents
by: Sun, Yuxuan, et al.
Published: (2025)

Harmonic LLMs are Trustworthy
by: Kersting, Nicholas S., et al.
Published: (2024)

AutoMind: Adaptive Knowledgeable Agent for Automated Data Science
by: Ou, Yixin, et al.
Published: (2025)

Beyond Semantic Similarity: A Component-Wise Evaluation Framework for Medical Question Answering Systems with Health Equity Implications
by: Sakib, Abu Noman Md, et al.
Published: (2026)

Interaction Dynamics as a Reward Signal for LLMs
by: Gooding, Sian, et al.
Published: (2025)

LLMs for XAI: Future Directions for Explaining Explanations
by: Zytek, Alexandra, et al.
Published: (2024)

Generative UI: LLMs are Effective UI Generators
by: Leviathan, Yaniv, et al.
Published: (2026)

Multimodal Fusion with LLMs for Engagement Prediction in Natural Conversation
by: Ma, Cheng Charles, et al.
Published: (2024)

What Large Language Models Know and What People Think They Know
by: Steyvers, Mark, et al.
Published: (2024)

How Controllable Are Large Language Models? A Unified Evaluation across Behavioral Granularities
by: Xu, Ziwen, et al.
Published: (2026)

Probing the Multi-turn Planning Capabilities of LLMs via 20 Question Games
by: Zhang, Yizhe, et al.
Published: (2023)

Are You Being Tracked? Discover the Power of Zero-Shot Trajectory Tracing with LLMs!
by: Yang, Huanqi, et al.
Published: (2024)

Personalized Benchmarking: Evaluating LLMs by Individual Preferences
by: Garbacea, Cristina, et al.
Published: (2026)

Demo: Statistically Significant Results On Biases and Errors of LLMs Do Not Guarantee Generalizable Results
by: Liu, Jonathan, et al.
Published: (2025)

MotionTeller: Multi-modal Integration of Wearable Time-Series with LLMs for Health and Behavioral Understanding
by: Zhang, Aiwei, et al.
Published: (2025)

Comparing Exploration-Exploitation Strategies of LLMs and Humans: Insights from Standard Multi-armed Bandit Experiments
by: Zhang, Ziyuan, et al.
Published: (2025)

LingVarBench: Benchmarking LLMs on Entity Recognitions and Linguistic Verbalization Patterns in Phone-Call Transcripts
by: Mohammadi, Seyedali, et al.
Published: (2025)

Teaching According to Students' Aptitude: Personalized Mathematics Tutoring via Persona-, Memory-, and Forgetting-Aware LLMs
by: Wu, Yang, et al.
Published: (2025)

Heterogeneous Value Alignment Evaluation for Large Language Models
by: Zhang, Zhaowei, et al.
Published: (2023)

"Excuse me, may I say something..." CoLabScience, A Proactive AI Assistant for Biomedical Discovery and LLM-Expert Collaborations
by: Wu, Yang, et al.
Published: (2026)

Evaluating Large Language Models for Health-related Queries with Presuppositions
by: Kaur, Navreet, et al.
Published: (2023)

Think Like a Person Before Responding: A Multi-Faceted Evaluation of Persona-Guided LLMs for Countering Hate
by: Ngueajio, Mikel K., et al.
Published: (2025)

TICKing All the Boxes: Generated Checklists Improve LLM Evaluation and Generation
by: Cook, Jonathan, et al.
Published: (2024)

LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models
by: Kahng, Minsuk, et al.
Published: (2024)

If in a Crowdsourced Data Annotation Pipeline, a GPT-4
by: He, Zeyu, et al.
Published: (2024)

Detecting and Preventing Harmful Behaviors in AI Companions: Development and Evaluation of the SHIELD Supervisory System
by: Ben-Zion, Ziv, et al.
Published: (2025)

Building Trust in Mental Health Chatbots: Safety Metrics and LLM-Based Evaluation Tools
by: Park, Jung In, et al.
Published: (2024)

The Behavior Gap: Evaluating Zero-shot LLM Agents in Complex Task-Oriented Dialogs
by: Baidya, Avinash, et al.
Published: (2025)

Augmenting Human Evaluation with LLM Judges: How Many Human Reviews Do You Need?
by: Kim, Jane Paik
Published: (2026)

Large Language Models for Cancer Communication: Evaluating Linguistic Quality, Safety, and Accessibility in Generative AI
by: Saha, Agnik, et al.
Published: (2025)

PRECISE Framework: GPT-based Text For Improved Readability, Reliability, and Understandability of Radiology Reports For Patient-Centered Care
by: Tripathi, Satvik, et al.
Published: (2024)

Can Generative AI Support Patients' & Caregivers' Informational Needs? Towards Task-Centric Evaluation Of AI Systems
by: Rajagopal, Shreya, et al.
Published: (2024)

UniAutoML: A Human-Centered Framework for Unified Discriminative and Generative AutoML with Large Language Models
by: Guo, Jiayi, et al.
Published: (2024)

Prompting in the Dark: Assessing Human Performance in Prompt Engineering for Data Labeling When Gold Labels Are Absent
by: He, Zeyu, et al.
Published: (2025)

AutoGLM: Autonomous Foundation Agents for GUIs
by: Liu, Xiao, et al.
Published: (2024)

LLMs as Writing Assistants: Exploring Perspectives on Sense of Ownership and Reasoning
by: Wasi, Azmine Toushik, et al.
Published: (2024)