Cover Image

Defining and Evaluating Physical Safety for Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tang, Yung-Chen, Chen, Pin-Yu, Ho, Tsung-Yi
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Computers and Society
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Gradient Cuff: Detecting Jailbreak Attacks on Large Language Models by Exploring Refusal Loss Landscapes
by: Hu, Xiaomeng, et al.
Published: (2024)

GREAT Score: Global Robustness Evaluation of Adversarial Perturbation using Generative Models
by: Li, Zaitang, et al.
Published: (2023)

PropensityBench: Evaluating Latent Safety Risks in Large Language Models via an Agentic Approach
by: Sehwag, Udari Madhushani, et al.
Published: (2025)

Fundamental Safety-Capability Trade-offs in Fine-tuning Large Language Models
by: Chen, Pin-Yu, et al.
Published: (2025)

Foundational Challenges in Assuring Alignment and Safety of Large Language Models
by: Anwar, Usman, et al.
Published: (2024)

Evaluating Large Language Models for Fair and Reliable Organ Allocation
by: Kim, Brian Hyeongseok, et al.
Published: (2025)

GreedLlama: Performance of Financial Value-Aligned Large Language Models in Moral Reasoning
by: Yu, Jeffy, et al.
Published: (2024)

Reducing Large Language Model Safety Risks in Women's Health using Semantic Entropy
by: Penny-Dimri, Jahan C., et al.
Published: (2025)

Evaluating Retrieval-Augmented Generation Strategies for Large Language Models in Travel Mode Choice Prediction
by: Xu, Yiming, et al.
Published: (2025)

Defining AI Models and AI Systems: A Framework to Resolve the Boundary Problem
by: Sun, Yuanyuan, et al.
Published: (2026)

On Catastrophic Inheritance of Large Foundation Models
by: Chen, Hao, et al.
Published: (2024)

LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models
by: Faiz, Ahmad, et al.
Published: (2023)

NaNa and MiGu: Semantic Data Augmentation Techniques to Enhance Protein Classification in Graph Neural Networks
by: Lan, Yi-Shan, et al.
Published: (2024)

Attacks, Defenses and Evaluations for LLM Conversation Safety: A Survey
by: Dong, Zhichen, et al.
Published: (2024)

Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models
by: Zhang, Yue, et al.
Published: (2023)

Assessing Large Language Models on Climate Information
by: Bulian, Jannis, et al.
Published: (2023)

Holistically Evaluating the Environmental Impact of Creating Language Models
by: Morrison, Jacob, et al.
Published: (2025)

AXOLOTL: Fairness through Assisted Self-Debiasing of Large Language Model Outputs
by: Ebrahimi, Sana, et al.
Published: (2024)

On Defining Smart Cities using Transformer Neural Networks
by: Khurshudov, Andrei
Published: (2024)

AI Companies Should Report Pre- and Post-Mitigation Safety Evaluations
by: Bowen, Dillon, et al.
Published: (2025)

Cleansing Jewel: A Neural Spelling Correction Model Built On Google OCR-ed Tibetan Manuscripts
by: Luo, Queenie, et al.
Published: (2023)

Existential Conversations with Large Language Models: Content, Community, and Culture
by: Shanahan, Murray, et al.
Published: (2024)

Democratizing Diplomacy: A Harness for Evaluating Any Large Language Model on Full-Press Diplomacy
by: Duffy, Alexander, et al.
Published: (2025)

A Behavioural and Representational Evaluation of Goal-Directedness in Language Model Agents
by: Arghal, Raghu, et al.
Published: (2026)

BiasFreeBench: a Benchmark for Mitigating Bias in Large Language Model Responses
by: Xu, Xin, et al.
Published: (2025)

Bias and Fairness in Large Language Models: A Survey
by: Gallegos, Isabel O., et al.
Published: (2023)

Participatory Assessment of Large Language Model Applications in an Academic Medical Center
by: Carra, Giorgia, et al.
Published: (2024)

Leveraging Large Language Models for Tacit Knowledge Discovery in Organizational Contexts
by: Zuin, Gianlucca, et al.
Published: (2025)

CarBoN: Calibrated Best-of-N Sampling Improves Test-time Reasoning
by: Tang, Yung-Chen, et al.
Published: (2025)

Harnessing Large Language Models for Mental Health: Opportunities, Challenges, and Ethical Considerations
by: Pandey, Hari Mohan
Published: (2024)

Hypothesis Generation with Large Language Models
by: Zhou, Yangqiaoyu, et al.
Published: (2024)

Large Language Models are Geographically Biased
by: Manvi, Rohin, et al.
Published: (2024)

The LLM Has Left The Chat: Evidence of Bail Preferences in Large Language Models
by: Ensign, Danielle, et al.
Published: (2025)

Mechanistic Interpretability with SAEs: Probing Religion, Violence, and Geography in Large Language Models
by: Simbeck, Katharina, et al.
Published: (2025)

Unraveling the cognitive patterns of Large Language Models through module communities
by: Bhandari, Kushal Raj, et al.
Published: (2025)

Correlated Errors in Large Language Models
by: Kim, Elliot, et al.
Published: (2025)

Subtle Biases Need Subtler Measures: Dual Metrics for Evaluating Representative and Affinity Bias in Large Language Models
by: Kumar, Abhishek, et al.
Published: (2024)

An Approach to Technical AGI Safety and Security
by: Shah, Rohin, et al.
Published: (2025)

The Impact of Large Language Models in Academia: from Writing to Speaking
by: Geng, Mingmeng, et al.
Published: (2024)

Machine Learners Should Acknowledge the Legal Implications of Large Language Models as Personal Data
by: Nolte, Henrik, et al.
Published: (2025)