Article

Negative Preference Reduction in Large Language Model Unlearning: An Experimental Approach

2024-10-16

Abstract excerpt

Rapid growth in the size and complexity of language models has led to increased concerns about the presence of harmful biases and inaccuracies embedded in model outputs. Addressing these concerns autonomously, without human supervision, has become an essential challenge for improving model safety and ethical alignment. This paper introduces a novel unlearning framework that systematically reduces negative preferen...

Topics

Open a Topic to create a Post that cites this publication.

Uncategorized literature

Identifiers and source

Literature Corpus work: ac276f45-2f9a-51be-bee2-43bde962bd3a
DOI: 10.22541/au.172910500.09952481/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Negative Preference Reduction in Large Language Model Unlearning: An Experimental ApproachDOI 10.22541/au.172910500.09952481/v1Read

A Survey of Large Language Models: Evolution, Architectures, Adaptation, Benchmarking, Applications, Challenges, and Societal ImplicationsSemantic proximity Read

Fine-grained Debiasing for Large Language Modelsvia Bias Intensity and Probability DecouplingSemantic proximity Read

Basics of Large Language Models - transformers to LLMsSemantic proximity Read

Beyond Words: The Evolution of Large Language Models in Context-AwareSemantic proximity Read

Optimizing Human-Controlled Preference Alignment in Large Language Models via Dense Token Masking: A Methodological ApproachSemantic proximity Read

Dynamic Probabilistic Contextual Realignment in Transformer-Based Large Language Models for Semantic ConsistencySemantic proximity Read

The Optimization of the Inference Efficiency and Ethical Alignment of Large Language Models via Dynamic Token Flow MechanismSemantic proximity Read

Unified Efficient Fine-Tuning Techniques for Open-Source Large Language ModelsSemantic proximity Read

Adaptive Contextual Preference Alignment for Large Language ModelsSemantic proximity Read

Beyond Benchmarks: Dynamic, Automatic And Systematic Red-Teaming Agents For Trustworthy Medical Language ModelsSemantic proximity Read

On the Development of ToxicBias-Reasoning for Responsible Multicultural Bias Detection and ExplanationSemantic proximity Read

Noise-Robust Preference Alignment for Large Language Models via Confidence Estimation and Adaptive OptimizationSemantic proximity Read