Saved in:
| Main Authors: | Chataigner, Cléa, Taïk, Afaf, Farnadi, Golnoosh |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.18270 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Say It Another Way: Auditing LLMs with a User-Grounded Automated Paraphrasing Framework
by: Chataigner, Cléa, et al.
Published: (2025)
by: Chataigner, Cléa, et al.
Published: (2025)
Fairness in Federated Learning: Fairness for Whom?
by: Taik, Afaf, et al.
Published: (2025)
by: Taik, Afaf, et al.
Published: (2025)
Differentially Private Clustered Federated Learning
by: Malekmohammadi, Saber, et al.
Published: (2024)
by: Malekmohammadi, Saber, et al.
Published: (2024)
Promoting Fair Vaccination Strategies Through Influence Maximization: A Case Study on COVID-19 Spread
by: Neophytou, Nicola, et al.
Published: (2024)
by: Neophytou, Nicola, et al.
Published: (2024)
Enhancing Privacy in the Early Detection of Sexual Predators Through Federated Learning and Differential Privacy
by: Chehbouni, Khaoula, et al.
Published: (2025)
by: Chehbouni, Khaoula, et al.
Published: (2025)
Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning
by: Ganesh, Prakhar, et al.
Published: (2025)
by: Ganesh, Prakhar, et al.
Published: (2025)
From Representational Harms to Quality-of-Service Harms: A Case Study on Llama 2 Safety Safeguards
by: Chehbouni, Khaoula, et al.
Published: (2024)
by: Chehbouni, Khaoula, et al.
Published: (2024)
Fairness Incentives in Response to Unfair Dynamic Pricing
by: Thibodeau, Jesse, et al.
Published: (2024)
by: Thibodeau, Jesse, et al.
Published: (2024)
Understanding Intrinsic Socioeconomic Biases in Large Language Models
by: Arzaghi, Mina, et al.
Published: (2024)
by: Arzaghi, Mina, et al.
Published: (2024)
Hallucination Detox: Sensitivity Dropout (SenD) for Large Language Model Training
by: Mohammadzadeh, Shahrad, et al.
Published: (2024)
by: Mohammadzadeh, Shahrad, et al.
Published: (2024)
Balancing Profit and Fairness in Risk-Based Pricing Markets
by: Thibodeau, Jesse, et al.
Published: (2025)
by: Thibodeau, Jesse, et al.
Published: (2025)
LoRA Provides Differential Privacy by Design via Random Sketching
by: Malekmohammadi, Saber, et al.
Published: (2024)
by: Malekmohammadi, Saber, et al.
Published: (2024)
Intrinsic Meets Extrinsic Fairness: Assessing the Downstream Impact of Bias Mitigation in Large Language Models
by: Arzaghi', 'Mina, et al.
Published: (2025)
by: Arzaghi', 'Mina, et al.
Published: (2025)
Multilingual Amnesia: On the Transferability of Unlearning in Multilingual LLMs
by: Farashah, Alireza Dehghanpour, et al.
Published: (2026)
by: Farashah, Alireza Dehghanpour, et al.
Published: (2026)
Crossing Boundaries: Leveraging Semantic Divergences to Explore Cultural Novelty in Cooking Recipes
by: Carichon, Florian, et al.
Published: (2025)
by: Carichon, Florian, et al.
Published: (2025)
Towards More Realistic Extraction Attacks: An Adversarial Perspective
by: More, Yash, et al.
Published: (2024)
by: More, Yash, et al.
Published: (2024)
Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing
by: Kassem, Aly M., et al.
Published: (2025)
by: Kassem, Aly M., et al.
Published: (2025)
Trust No Bot: Discovering Personal Disclosures in Human-LLM Conversations in the Wild
by: Mireshghallah, Niloofar, et al.
Published: (2024)
by: Mireshghallah, Niloofar, et al.
Published: (2024)
Neither Valid nor Reliable? Investigating the Use of LLMs as Judges
by: Chehbouni, Khaoula, et al.
Published: (2025)
by: Chehbouni, Khaoula, et al.
Published: (2025)
Beyond the Safety Bundle: Auditing the Helpful and Harmless Dataset
by: Chehbouni, Khaoula, et al.
Published: (2024)
by: Chehbouni, Khaoula, et al.
Published: (2024)
Mitigating Multilingual Hallucination in Large Vision-Language Models
by: Qu, Xiaoye, et al.
Published: (2024)
by: Qu, Xiaoye, et al.
Published: (2024)
Rethinking Hallucinations: Correctness, Consistency, and Prompt Multiplicity
by: Ganesh, Prakhar, et al.
Published: (2026)
by: Ganesh, Prakhar, et al.
Published: (2026)
Mechanics of Bias and Reasoning: Interpreting the Impact of Chain-of-Thought Prompting on Gender Bias in LLMs
by: Pearman, Edie, et al.
Published: (2026)
by: Pearman, Edie, et al.
Published: (2026)
Poly-FEVER: A Multilingual Fact Verification Benchmark for Hallucination Detection in Large Language Models
by: Zhang, Hanzhi, et al.
Published: (2025)
by: Zhang, Hanzhi, et al.
Published: (2025)
Multilingual Large Language Models and Curse of Multilinguality
by: Gurgurov, Daniil, et al.
Published: (2024)
by: Gurgurov, Daniil, et al.
Published: (2024)
Position: Cracking the Code of Cascading Disparity Towards Marginalized Communities
by: Farnadi, Golnoosh, et al.
Published: (2024)
by: Farnadi, Golnoosh, et al.
Published: (2024)
Once Correct, Still Wrong: Counterfactual Hallucination in Multilingual Vision-Language Models
by: Mousi, Basel, et al.
Published: (2026)
by: Mousi, Basel, et al.
Published: (2026)
Pruning Multilingual Large Language Models for Multilingual Inference
by: Kim, Hwichan, et al.
Published: (2024)
by: Kim, Hwichan, et al.
Published: (2024)
The Hallucinations Leaderboard -- An Open Effort to Measure Hallucinations in Large Language Models
by: Hong, Giwon, et al.
Published: (2024)
by: Hong, Giwon, et al.
Published: (2024)
Causal Fair Metric: Bridging Causality, Individual Fairness, and Adversarial Robustness
by: Ehyaei, Ahmad-Reza, et al.
Published: (2023)
by: Ehyaei, Ahmad-Reza, et al.
Published: (2023)
CLAIM: Mitigating Multilingual Object Hallucination in Large Vision-Language Models with Cross-Lingual Attention Intervention
by: Ye, Zekai, et al.
Published: (2025)
by: Ye, Zekai, et al.
Published: (2025)
Language Surgery in Multilingual Large Language Models
by: Lopo, Joanito Agili, et al.
Published: (2025)
by: Lopo, Joanito Agili, et al.
Published: (2025)
Alleviating Hallucinations of Large Language Models through Induced Hallucinations
by: Zhang, Yue, et al.
Published: (2023)
by: Zhang, Yue, et al.
Published: (2023)
CCNU at SemEval-2025 Task 3: Leveraging Internal and External Knowledge of Large Language Models for Multilingual Hallucination Annotation
by: Liu, Xu, et al.
Published: (2025)
by: Liu, Xu, et al.
Published: (2025)
AILS-NTUA at SemEval-2025 Task 3: Leveraging Large Language Models and Translation Strategies for Multilingual Hallucination Detection
by: Karkani, Dimitra, et al.
Published: (2025)
by: Karkani, Dimitra, et al.
Published: (2025)
Dictionary Insertion Prompting for Multilingual Reasoning on Multilingual Large Language Models
by: Lu, Hongyuan, et al.
Published: (2024)
by: Lu, Hongyuan, et al.
Published: (2024)
How Much Do LLMs Hallucinate across Languages? On Realistic Multilingual Estimation of LLM Hallucination
by: Islam, Saad Obaid ul, et al.
Published: (2025)
by: Islam, Saad Obaid ul, et al.
Published: (2025)
Mitigating Hallucinations in Large Vision-Language Models by Self-Injecting Hallucinations
by: Lu, Yifan, et al.
Published: (2025)
by: Lu, Yifan, et al.
Published: (2025)
Quantifying Language Disparities in Multilingual Large Language Models
by: Hu, Songbo, et al.
Published: (2025)
by: Hu, Songbo, et al.
Published: (2025)
XTRUST: On the Multilingual Trustworthiness of Large Language Models
by: Li, Yahan, et al.
Published: (2024)
by: Li, Yahan, et al.
Published: (2024)
Similar Items
-
Say It Another Way: Auditing LLMs with a User-Grounded Automated Paraphrasing Framework
by: Chataigner, Cléa, et al.
Published: (2025) -
Fairness in Federated Learning: Fairness for Whom?
by: Taik, Afaf, et al.
Published: (2025) -
Differentially Private Clustered Federated Learning
by: Malekmohammadi, Saber, et al.
Published: (2024) -
Promoting Fair Vaccination Strategies Through Influence Maximization: A Case Study on COVID-19 Spread
by: Neophytou, Nicola, et al.
Published: (2024) -
Enhancing Privacy in the Early Detection of Sexual Predators Through Federated Learning and Differential Privacy
by: Chehbouni, Khaoula, et al.
Published: (2025)