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Responsible AI

2,003 papers

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Papers

Cal-DPO: Calibrated Direct Preference Optimization for Language Model Alignment NIPS 2024
Calibrating Reasoning in Language Models with Internal Consistency NIPS 2024
FLAME : Factuality-Aware Alignment for Large Language Models NIPS 2024
A Synthetic Dataset for Personal Attribute Inference NIPS 2024
Accuracy is Not All You Need NIPS 2024
SafeWorld: Geo-Diverse Safety Alignment NIPS 2024
Attack-Aware Noise Calibration for Differential Privacy NIPS 2024
Thought of Search: Planning with Language Models Through The Lens of Efficiency NIPS 2024
Evaluating Copyright Takedown Methods for Language Models NIPS 2024
Enhancing Robustness of Last Layer Two-Stage Fair Model Corrections NIPS 2024
Probing Social Bias in Labor Market Text Generation by ChatGPT: A Masked Language Model Approach NIPS 2024
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models NIPS 2024
Learning to Unlearn: Instance-Wise Unlearning for Pre-trained Classifiers AAAI 2024
A Sequentially Fair Mechanism for Multiple Sensitive Attributes AAAI 2024
All Should Be Equal in the Eyes of LMs: Counterfactually Aware Fair Text Generation AAAI 2024
Mitigating Large Language Model Hallucinations via Autonomous Knowledge Graph-Based Retrofitting AAAI 2024
Detecting and Preventing Hallucinations in Large Vision Language Models AAAI 2024
Small Language Model Can Self-Correct AAAI 2024
Separate the Wheat from the Chaff: Model Deficiency Unlearning via Parameter-Efficient Module Operation AAAI 2024
Robust Evaluation Measures for Evaluating Social Biases in Masked Language Models AAAI 2024
Quantifying and Analyzing Entity-Level Memorization in Large Language Models AAAI 2024
Value Kaleidoscope: Engaging AI with Pluralistic Human Values, Rights, and Duties AAAI 2024
U-trustworthy Models. Reliability, Competence, and Confidence in Decision-Making AAAI 2024
ORES: Open-Vocabulary Responsible Visual Synthesis AAAI 2024
Identifying Reasons for Bias: An Argumentation-Based Approach AAAI 2024