NeurIPS 2024PastSafety & alignment
Pluralistic Alignment Workshop at NeurIPS 2024
Pluralistic-Alignment 2024
- Submission deadline
- Sep 11, 2024, 11:59 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (48)
Fetched from OpenReview (v2) on 2026-06-10.
"There are no solutions, only trade-offs.'' Taking A Closer Look At Safety Data Annotations.
A Case Study in Plural Governance Design
Adaptive Alignment: Dynamic Preference Adjustments via Multi-Objective Reinforcement Learning for Pluralistic AI
AGR: Age Group fairness Reward for Bias Mitigation in LLMs
AI, Pluralism, and (Social) Compensation
Aligning LLMs using Reinforcement Learning from Market Feedback (RLMF) for Regime Adaptation
Aligning to Thousands of Preferences via System Message Generalization
Are Large Language Models Consistent over Value-laden Questions?
Being Considerate as a Pathway Towards Pluralistic Alignment for Agentic AI
Bottom-Up and Top-Down Analysis of Values, Agendas, and Observations in Corpora and LLMs
Can Language Models Reason about Individualistic Human Values and Preferences?
Chain of Alignment: Integrating Public Will with Expert Intelligence for Language Model Alignment
Conditional Language Policy: A General Framework For Steerable Multi-Objective Finetuning
Contrastive Learning Neuromotor Interface From Teacher
Controllable Safety Alignment: Adapting LLMs to Diverse Safety Requirements without Re-Training
Critique-out-Loud Reward Models
Diverging Preferences: When do Annotators Disagree and do Models Know?
Do Vision-Language Models Represent Space and How? Evaluating Spatial Frame of Reference under Ambiguities
Efficacy of the SAGE-RT Dataset for Model Safety Alignment: A Comparative Study
Evaluating the Prompt Steerability of Large Language Models
FairPlay: A Collaborative Approach to Mitigate Bias in Datasets for Improved AI Fairness
From Distributional to Overton Pluralism: Investigating Large Language Model Alignment
Group Robust Best-of-K Decoding of Language Models for Pluralistic Alignment
Intuitions of Compromise: Utilitarianism vs. Contractualism
Learning from Personal Preferences
Mallows-DPO: Fine-Tune Your LLM with Preference Dispersions
Mechanism Design for LLM Fine-tuning with Multiple Reward Models
MID-Space: Aligning Diverse Communities' Needs to Inclusive Public Spaces
Model Plurality: A Taxonomy for Pluralistic AI
Multi-objective Reinforcement Learning: A Tool for Pluralistic Alignment
Multilingual Trolley Problems for Language Models
PAL: Pluralistic Alignment Framework for Learning from Heterogeneous Preferences
Pareto-Optimal Learning from Preferences with Hidden Context
Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning
PersonalLLM: Tailoring LLMs to Individual Preferences
Pluralistic Alignment Over Time
Plurality of value pluralism and AI value alignment
Plurals: A system for pluralistic AI via simulated social ensembles
Policy Aggregation
Reinforcement Learning from Multi-role Debates as Feedback for Bias Mitigation in LLMs
Representative Social Choice: From Learning Theory to AI Alignment
Rules, Cases, and Reasoning: Positivist Legal Theory as a Framework for Pluralistic AI Alignment
Selective Preference Aggregation
Toward Democracy Levels for AI
Tractable Agreement Protocols
Value Alignment from Unstructured Text
Value-Aligned Imitation via focused Satisficing
Virtual Personas for Language Models via an Anthology of Backstories