Mitigating Exaggerated Safety in Large Language Models
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | Ray, Ruchira, Bhalani, Ruchi |
|---|---|
| Format: | Preprint |
| Publié: |
2024
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models
par: Röttger, Paul, et autres
Publié: (2023)
par: Röttger, Paul, et autres
Publié: (2023)
Defining Knowledge: Bridging Epistemology and Large Language Models
par: Fierro, Constanza, et autres
Publié: (2024)
par: Fierro, Constanza, et autres
Publié: (2024)
Beyond Over-Refusal: Scenario-Based Diagnostics and Post-Hoc Mitigation for Exaggerated Refusals in LLMs
par: Yuan, Shuzhou, et autres
Publié: (2025)
par: Yuan, Shuzhou, et autres
Publié: (2025)
Evaluation Revisited: A Taxonomy of Evaluation Concerns in Natural Language Processing
par: Dhar, Ruchira, et autres
Publié: (2026)
par: Dhar, Ruchira, et autres
Publié: (2026)
Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models
par: Schaeffer, Rylan, et autres
Publié: (2025)
par: Schaeffer, Rylan, et autres
Publié: (2025)
RIGOURATE: Quantifying Scientific Exaggeration with Evidence-Aligned Claim Evaluation
par: James, Joseph, et autres
Publié: (2026)
par: James, Joseph, et autres
Publié: (2026)
Do Large Language Models Reflect Demographic Pluralism in Safety?
par: Naseem, Usman, et autres
Publié: (2026)
par: Naseem, Usman, et autres
Publié: (2026)
Hallucination Detection and Mitigation with Diffusion in Multi-Variate Time-Series Foundation Models
par: Wichitwechkarn, Vijja, et autres
Publié: (2025)
par: Wichitwechkarn, Vijja, et autres
Publié: (2025)
Understanding and Mitigating Over-refusal for Large Language Models via Safety Representation
par: Zhang, Junbo, et autres
Publié: (2025)
par: Zhang, Junbo, et autres
Publié: (2025)
Think in Safety: Unveiling and Mitigating Safety Alignment Collapse in Multimodal Large Reasoning Model
par: Lou, Xinyue, et autres
Publié: (2025)
par: Lou, Xinyue, et autres
Publié: (2025)
SafetyBench: Evaluating the Safety of Large Language Models
par: Zhang, Zhexin, et autres
Publié: (2023)
par: Zhang, Zhexin, et autres
Publié: (2023)
Diverse, but Divisive: LLMs Can Exaggerate Gender Differences in Opinion Related to Harms of Misinformation
par: Neumann, Terrence, et autres
Publié: (2024)
par: Neumann, Terrence, et autres
Publié: (2024)
Mitigating the Bias of Large Language Model Evaluation
par: Zhou, Hongli, et autres
Publié: (2024)
par: Zhou, Hongli, et autres
Publié: (2024)
From Words to Worlds: Compositionality for Cognitive Architectures
par: Dhar, Ruchira, et autres
Publié: (2024)
par: Dhar, Ruchira, et autres
Publié: (2024)
Mitigating Large Language Model Hallucination with Faithful Finetuning
par: Hu, Minda, et autres
Publié: (2024)
par: Hu, Minda, et autres
Publié: (2024)
Exploring and Mitigating Fawning Hallucinations in Large Language Models
par: Shangguan, Zixuan, et autres
Publié: (2025)
par: Shangguan, Zixuan, et autres
Publié: (2025)
Mitigating Label Length Bias in Large Language Models
par: Sanz-Guerrero, Mario, et autres
Publié: (2025)
par: Sanz-Guerrero, Mario, et autres
Publié: (2025)
When Models Outthink Their Safety: Unveiling and Mitigating Self-Jailbreak in Large Reasoning Models
par: Mao, Yingzhi, et autres
Publié: (2025)
par: Mao, Yingzhi, et autres
Publié: (2025)
Do Multilingual Large Language Models Mitigate Stereotype Bias?
par: Nie, Shangrui, et autres
Publié: (2024)
par: Nie, Shangrui, et autres
Publié: (2024)
Mitigating the Risk of Health Inequity Exacerbated by Large Language Models
par: Ji, Yuelyu, et autres
Publié: (2024)
par: Ji, Yuelyu, et autres
Publié: (2024)
Detection, Classification, and Mitigation of Gender Bias in Large Language Models
par: Cheng, Xiaoqing, et autres
Publié: (2025)
par: Cheng, Xiaoqing, et autres
Publié: (2025)
Mitigating Gambling-Like Risk-Taking Behaviors in Large Language Models: A Behavioral Economics Approach to AI Safety
par: Du, Y.
Publié: (2025)
par: Du, Y.
Publié: (2025)
Sycophancy in Large Language Models: Causes and Mitigations
par: Malmqvist, Lars
Publié: (2024)
par: Malmqvist, Lars
Publié: (2024)
An Evolutionary Large Language Model for Hallucination Mitigation
par: Boulesnane, Abdennour, et autres
Publié: (2024)
par: Boulesnane, Abdennour, et autres
Publié: (2024)
Towards Comprehensive Post Safety Alignment of Large Language Models via Safety Patching
par: Zhao, Weixiang, et autres
Publié: (2024)
par: Zhao, Weixiang, et autres
Publié: (2024)
Is Safety Standard Same for Everyone? User-Specific Safety Evaluation of Large Language Models
par: In, Yeonjun, et autres
Publié: (2025)
par: In, Yeonjun, et autres
Publié: (2025)
Mechanistic Understanding and Mitigation of Language Confusion in English-Centric Large Language Models
par: Nie, Ercong, et autres
Publié: (2025)
par: Nie, Ercong, et autres
Publié: (2025)
Controlled Training Data Generation with Diffusion Models
par: Yeo, Teresa, et autres
Publié: (2024)
par: Yeo, Teresa, et autres
Publié: (2024)
Unraveling and Mitigating Safety Alignment Degradation of Vision-Language Models
par: Liu, Qin, et autres
Publié: (2024)
par: Liu, Qin, et autres
Publié: (2024)
Vulnerability Mitigation for Safety-Aligned Language Models via Debiasing
par: Tran, Thien Q., et autres
Publié: (2025)
par: Tran, Thien Q., et autres
Publié: (2025)
Evaluating Psychological Safety of Large Language Models
par: Li, Xingxuan, et autres
Publié: (2022)
par: Li, Xingxuan, et autres
Publié: (2022)
Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models
par: Zhu, Didi, et autres
Publié: (2024)
par: Zhu, Didi, et autres
Publié: (2024)
Evaluating Adjective-Noun Compositionality in LLMs: Functional vs Representational Perspectives
par: Dhar, Ruchira, et autres
Publié: (2026)
par: Dhar, Ruchira, et autres
Publié: (2026)
KZ-SafetyPrompts: A Kazakh Safety Evaluation Prompt Dataset for Large Language Models
par: Zaghouani, Wajdi, et autres
Publié: (2026)
par: Zaghouani, Wajdi, et autres
Publié: (2026)
LongSafety: Evaluating Long-Context Safety of Large Language Models
par: Lu, Yida, et autres
Publié: (2025)
par: Lu, Yida, et autres
Publié: (2025)
Towards Resource Efficient and Interpretable Bias Mitigation in Large Language Models
par: Tong, Schrasing, et autres
Publié: (2024)
par: Tong, Schrasing, et autres
Publié: (2024)
Initialization of Large Language Models via Reparameterization to Mitigate Loss Spikes
par: Nishida, Kosuke, et autres
Publié: (2024)
par: Nishida, Kosuke, et autres
Publié: (2024)
MBIAS: Mitigating Bias in Large Language Models While Retaining Context
par: Raza, Shaina, et autres
Publié: (2024)
par: Raza, Shaina, et autres
Publié: (2024)
A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models
par: Tonmoy, S. M Towhidul Islam, et autres
Publié: (2024)
par: Tonmoy, S. M Towhidul Islam, et autres
Publié: (2024)
Unveiling and Mitigating Bias in Mental Health Analysis with Large Language Models
par: Wang, Yuqing, et autres
Publié: (2024)
par: Wang, Yuqing, et autres
Publié: (2024)
Documents similaires
-
XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models
par: Röttger, Paul, et autres
Publié: (2023) -
Defining Knowledge: Bridging Epistemology and Large Language Models
par: Fierro, Constanza, et autres
Publié: (2024) -
Beyond Over-Refusal: Scenario-Based Diagnostics and Post-Hoc Mitigation for Exaggerated Refusals in LLMs
par: Yuan, Shuzhou, et autres
Publié: (2025) -
Evaluation Revisited: A Taxonomy of Evaluation Concerns in Natural Language Processing
par: Dhar, Ruchira, et autres
Publié: (2026) -
Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models
par: Schaeffer, Rylan, et autres
Publié: (2025)