Fair in Mind, Fair in Action? A Synchronous Benchmark for Understanding and Generation in UMLLMs
Fuente:
arXiv
Saved in:
| Main Authors: | Zhao, Yiran, Zhou, Lu, Xu, Xiaogang, Liu, Zhe, Wu, Jiafei, Fang, Liming |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
HoloFair: Unified T2I Fairness Evaluation and Fair-GRPO Debiasing
by: Chen, Ruyi, et al.
Published: (2026)
by: Chen, Ruyi, et al.
Published: (2026)
GADT: Enhancing Transferable Adversarial Attacks through Gradient-guided Adversarial Data Transformation
by: Ma, Yating, et al.
Published: (2024)
by: Ma, Yating, et al.
Published: (2024)
Understanding Fairness Surrogate Functions in Algorithmic Fairness
by: Yao, Wei, et al.
Published: (2023)
by: Yao, Wei, et al.
Published: (2023)
Iter-AHMCL: Alleviate Hallucination for Large Language Model via Iterative Model-level Contrastive Learning
by: Wu, Huiwen, et al.
Published: (2024)
by: Wu, Huiwen, et al.
Published: (2024)
To Be Forgotten or To Be Fair: Unveiling Fairness Implications of Machine Unlearning Methods
by: Zhang, Dawen, et al.
Published: (2023)
by: Zhang, Dawen, et al.
Published: (2023)
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
by: Han, Xiaotian, et al.
Published: (2023)
by: Han, Xiaotian, et al.
Published: (2023)
From Thinker to Society: Security in Hierarchical Autonomy Evolution of AI Agents
by: Zhang, Xiaolei, et al.
Published: (2026)
by: Zhang, Xiaolei, et al.
Published: (2026)
DR-Encoder: Encode Low-rank Gradients with Random Prior for Large Language Models Differentially Privately
by: Wu, Huiwen, et al.
Published: (2024)
by: Wu, Huiwen, et al.
Published: (2024)
CG-FedLLM: How to Compress Gradients in Federated Fune-tuning for Large Language Models
by: Wu, Huiwen, et al.
Published: (2024)
by: Wu, Huiwen, et al.
Published: (2024)
Fùxì: A Benchmark for Evaluating Language Models on Ancient Chinese Text Understanding and Generation
by: Zhao, Shangqing, et al.
Published: (2025)
by: Zhao, Shangqing, et al.
Published: (2025)
FairDgcl: Fairness-aware Recommendation with Dynamic Graph Contrastive Learning
by: Chen, Wei, et al.
Published: (2024)
by: Chen, Wei, et al.
Published: (2024)
SimFair: Physics-Guided Fairness-Aware Learning with Simulation Models
by: Wang, Zhihao, et al.
Published: (2024)
by: Wang, Zhihao, et al.
Published: (2024)
FairDD: Fair Dataset Distillation
by: Zhou, Qihang, et al.
Published: (2024)
by: Zhou, Qihang, et al.
Published: (2024)
FairAgent: Democratizing Fairness-Aware Machine Learning with LLM-Powered Agents
by: Dai, Yucong, et al.
Published: (2025)
by: Dai, Yucong, et al.
Published: (2025)
FairStream: Fair Multimedia Streaming Benchmark for Reinforcement Learning Agents
by: Weil, Jannis, et al.
Published: (2024)
by: Weil, Jannis, et al.
Published: (2024)
Understanding What Affects the Generalization Gap in Visual Reinforcement Learning: Theory and Empirical Evidence
by: Lyu, Jiafei, et al.
Published: (2024)
by: Lyu, Jiafei, et al.
Published: (2024)
FairGU: Fairness-aware Graph Unlearning in Social Networks
by: Luo, Renqiang, et al.
Published: (2026)
by: Luo, Renqiang, et al.
Published: (2026)
Jailbreaking Commercial Black-Box LLMs with Explicitly Harmful Prompts
by: Zhang, Chiyu, et al.
Published: (2025)
by: Zhang, Chiyu, et al.
Published: (2025)
Mind the Model, Not the Agent: The Primacy Bias in Model-based RL
by: Qiao, Zhongjian, et al.
Published: (2023)
by: Qiao, Zhongjian, et al.
Published: (2023)
JustEva: A Toolkit to Evaluate LLM Fairness in Legal Knowledge Inference
by: Xue, Zongyue, et al.
Published: (2025)
by: Xue, Zongyue, et al.
Published: (2025)
FairBatching: Fairness-Aware Batch Formation for LLM Inference
by: Lyu, Hongtao, et al.
Published: (2025)
by: Lyu, Hongtao, et al.
Published: (2025)
FairNet: Dynamic Fairness Correction without Performance Loss via Contrastive Conditional LoRA
by: Zhou, Songqi, et al.
Published: (2025)
by: Zhou, Songqi, et al.
Published: (2025)
AFed: Algorithmic Fair Federated Learning
by: Chen, Huiqiang, et al.
Published: (2025)
by: Chen, Huiqiang, et al.
Published: (2025)
Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance?
by: Liu, Junhua, et al.
Published: (2024)
by: Liu, Junhua, et al.
Published: (2024)
Robust-R1: Degradation-Aware Reasoning for Robust Visual Understanding
by: Tang, Jiaqi, et al.
Published: (2025)
by: Tang, Jiaqi, et al.
Published: (2025)
Benchmarking Fairness in Spiking Neural Networks: Data Bias, Spurious Features, and Hardware Effects
by: He, Hudi, et al.
Published: (2026)
by: He, Hudi, et al.
Published: (2026)
The Illusion of Fairness: Auditing Fairness Interventions with Audit Studies
by: Sariola, Disa, et al.
Published: (2025)
by: Sariola, Disa, et al.
Published: (2025)
Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model
by: Liu, Yang, et al.
Published: (2025)
by: Liu, Yang, et al.
Published: (2025)
TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods
by: Qiu, Xiangfei, et al.
Published: (2024)
by: Qiu, Xiangfei, et al.
Published: (2024)
OpenDataArena: A Fair and Open Arena for Benchmarking Post-Training Dataset Value
by: Cai, Mengzhang, et al.
Published: (2025)
by: Cai, Mengzhang, et al.
Published: (2025)
Fairness in Graph Learning Augmented with Machine Learning: A Survey
by: Luo, Renqiang, et al.
Published: (2025)
by: Luo, Renqiang, et al.
Published: (2025)
Generating Synthetic Fair Syntax-agnostic Data by Learning and Distilling Fair Representation
by: Sikder, Md Fahim, et al.
Published: (2024)
by: Sikder, Md Fahim, et al.
Published: (2024)
The Neutrality Fallacy: When Algorithmic Fairness Interventions are (Not) Positive Action
by: Weerts, Hilde, et al.
Published: (2024)
by: Weerts, Hilde, et al.
Published: (2024)
FEED: Fairness-Enhanced Meta-Learning for Domain Generalization
by: Jiang, Kai, et al.
Published: (2024)
by: Jiang, Kai, et al.
Published: (2024)
FROG: Fair Removal on Graphs
by: Chen, Ziheng, et al.
Published: (2025)
by: Chen, Ziheng, et al.
Published: (2025)
FairSAM: Fair Classification on Corrupted Data Through Sharpness-Aware Minimization
by: Dai, Yucong, et al.
Published: (2025)
by: Dai, Yucong, et al.
Published: (2025)
FairTargetSim: An Interactive Simulator for Understanding and Explaining the Fairness Effects of Target Variable Definition
by: Gala, Dalia, et al.
Published: (2024)
by: Gala, Dalia, et al.
Published: (2024)
FairCauseSyn: Towards Causally Fair LLM-Augmented Synthetic Data Generation
by: Nagesh, Nitish, et al.
Published: (2025)
by: Nagesh, Nitish, et al.
Published: (2025)
Bridging the Fairness Gap: Enhancing Pre-trained Models with LLM-Generated Sentences
by: Yu, Liu, et al.
Published: (2025)
by: Yu, Liu, et al.
Published: (2025)
JobFair: A Framework for Benchmarking Gender Hiring Bias in Large Language Models
by: Wang, Ze, et al.
Published: (2024)
by: Wang, Ze, et al.
Published: (2024)
Similar Items
-
HoloFair: Unified T2I Fairness Evaluation and Fair-GRPO Debiasing
by: Chen, Ruyi, et al.
Published: (2026) -
GADT: Enhancing Transferable Adversarial Attacks through Gradient-guided Adversarial Data Transformation
by: Ma, Yating, et al.
Published: (2024) -
Understanding Fairness Surrogate Functions in Algorithmic Fairness
by: Yao, Wei, et al.
Published: (2023) -
Iter-AHMCL: Alleviate Hallucination for Large Language Model via Iterative Model-level Contrastive Learning
by: Wu, Huiwen, et al.
Published: (2024) -
To Be Forgotten or To Be Fair: Unveiling Fairness Implications of Machine Unlearning Methods
by: Zhang, Dawen, et al.
Published: (2023)