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THE IMPACT OF PREFERENCE LEARNING

Our latest blog entry discusses the impact of #PreferenceLearning in #LLMs, wraps up #MPREF2025, and gives an outlook on this year’s #PreferenceHandling events #DA2PL2026 and #ADT2026. ADT will be held in Paris on Nov. 16-18. Abstracts are due by May 4, papers by May 11.
mpref.org/the-impact-o...

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Problem Solving Through Human–AI Preference-based Cooperation Abstract. While there is a widespread belief that artificial general intelligence—or even superhuman AI—is imminent, complex problems in expert domains are far from being solved. We argue that such pr...

💻 Project page:
ukplab.github.io/arxiv2025-ex...

🔁 Both papers build on HAI-Co2 described in this position paper:
direct.mit.edu/coli/article...

#NLP #NLProc #LLMs #Evaluation #PreferenceLearning #ScientificWriting #HumanAI #HaiCo2 @tuda.bsky.social @cs-tudarmstadt.bsky.social

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CS329H: Machine Learning from Human Preferences Machine Learning from Human Preferences

7/ Materials:
Course website / syllabus / notes: web.stanford.edu/class/cs329h/
Living Textbook: mlhp.stanford.edu
#AIAlignment #MachineLearning #ResponsibleAI #Stanford #PreferenceLearning

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Algorithm Finds Best Policies with Trajectory Preference Feedback

Algorithm Finds Best Policies with Trajectory Preference Feedback

PSPL merges offline preference data with online exploration, using Thompson sampling to give Bayesian simple‑regret bounds for RL. Read more: getnews.me/algorithm-finds-best-pol... #preferencelearning #reinforcementlearning

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