ICML 2025PastSafety & alignment
2nd Workshop on Models of Human Feedback for AI Alignment
MoFA
- Submission deadline
- May 28, 2025, 13:00 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (68)
Fetched from OpenReview (v2) on 2026-06-10.
A Unified Perspective on Reward Distillation Through Ratio Matching
ActiveDPO: Active Direct Preference Optimization for Sample-Efficient Alignment
Advancing LLM Safe Alignment with Safety Representation Ranking
Aggregated Individual Reporting for Post-Deployment Evaluation
Aligned Textual Scoring Rule
Aligning Neural Style Representations for Style-based Clustering
Alignment as Distribution Learning: Your Preference Model is Explicitly a Language Model
Alignment of Large Language Models with Constrained Learning
Angular Steering: Behavior Control via Rotation in Activation Space
Auto-Guideline Alignment: Probing and Simulating Human Ideological Preferences in LLMs via Prompt Engineering
BiasLab: Toward Explainable Political Bias Detection with Dual-Axis Human Annotations and Rationale Indicators
Composition and Alignment of Diffusion Models using Constrained Learning
Configurable Preference Tuning with Rubric-Guided Synthetic Data
Copilot Arena: A Platform for Code LLM Evaluation in the Wild
CUDA: Capturing Uncertainty and Diversity in Preference Feedback Augmentation
Cultivating Pluralism In Algorithmic Monoculture: The Community Alignment Dataset
CulturalFrames: Assessing Cultural Expectation Alignment in Text-to-Image Models and Evaluation Metrics
Deep Context-Dependent Choice Model
Do Language Models Understand Discrimination? Testing Alignment with Human Legal Reasoning under the ECHR
Doctor Approved: Generating Medically Accurate Skin Disease Images through AI–Expert Feedback
Doubly Robust Alignment for Large Language Models
Dropping Just a Handful of Preferences Can Change Top Large Language Model Rankings
Dynamic Guardian Models: Realtime Content Moderation With User-Defined Policies
EconEvals: Benchmarks and Litmus Tests for LLM Agents in Unknown Environments
Efficient Generative Models Personalization via Optimal Experimental Design
Empirical Studies on the Limitations of Direct Preference Optimization, and a Possible Quick Fix
Enhancing Personalized Multi-Turn Dialogue with Curiosity Reward
Entropy Controllable Direct Preference Optimization
Expected Reward Prediction, with Applications to Model Routing
Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes
Fine-Tuning Next-Scale Visual Autoregressive Models with Group Relative Policy Optimization
FSPO: Few-Shot Preference Optimization of Synthetic Preference Data Elicits LLM Personalization to Real Users
Full-Stack Alignment: Co-Aligning AI and Institutions with Thicker Models of Value
Geometry-Aware Preference Learning for 3D Texture Generation
Human Feedback Guided Reinforcement Learning for Unknown Temporal Tasks via Weighted Finite Automata
Implicit User Feedback in Human-LLM Dialogues: Informative to Understand Users yet Noisy as a Learning Signal
Improvement-Guided Iterative DPO for Diffusion Models
In-Context Alignment at Scale: When More is Less
In-Context Personalized Alignment with Feedback History under Counterfactual Evaluation
Inference-Time Reward Hacking in Large Language Models
KL-Regularised Q-Learning: A Token-level Action-Value perspective on Online RLHF
Language Model Personalization via Reward Factorization
Learning interpretable descriptions of human preferences
LoRe: Personalizing LLMs via Low-Rank Reward Modeling
Mechanism Design for Alignment via Human Feedback
Mimicking Human Intuition: Cognitive Belief-Driven Reinforcement Learning
Mitigating Fine-tuning Risks in LLMs via Safety-Aware Probing Optimization
Multi-Task Reward Learning from Human Ratings
On the strength of goodhart's law
Online Learning and Equilibrium Computation with Ranking Feedback
Playing the Data: Video Games as a Tool to Annotate and Train Models on Large Datasets
Reasoning Isn't Enough: Examining Truth-Bias and Sycophancy in LLMs
ReDit: Reward Dithering for Improved LLM Policy Optimization
Rewrite-to-Rank: Optimizing Ad Visibility via Retrieval-Aware Text Rewriting
Robust Multi-Objective Controlled Decoding of Large Language Models
Robust Reinforcement Learning from Human Feedback for Large Language Models Fine-Tuning
Robust Reward Modeling via Causal Rubrics
Scalable Defense against In-the-wild Jailbreaking Attacks with Safety Context Retrieval
Selective Preference Aggregation
Self-Concordant Preference Learning from Noisy Labels
The Strong, weak and benign Goodhart’s law. An independence-free and paradigm-agnostic formalisation
Theoretical Analysis of KL-regularized RLHF with Multiple Reference Models
Towards a Sharp Analysis of Offline Policy Learning for $f$-Divergence-Regularized Contextual Bandits
Tracing Human-like Traits in LLMs: Origins, Real-World Manifestation, and Controllability
Unanchoring the Mind: DAE-Guided Counterfactual Reasoning for Rare Disease Diagnosis
Understanding Likelihood Over-optimisation in Direct Alignment Algorithms
Vertical Moral Growth: A Novel Developmental Framework for Human Feedback Quality in AI Alignment
What Matters when Modeling Human Behavior using Imitation Learning?