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From the 1 of 52 linked papers with an AI index.

activity
20242026
most citedA Survey of Reinforcement Learning from Human Feedback

36 citations · 39 across the 25 of their papers we have counts for

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5 papers · 1 filter

cs.CL2025

Feedback Forensics: A Toolkit to Measure AI Personality

Arduin Findeis, Timo Kaufmann, Eyke Hüllermeier +1

Some traits making a "good" AI model are hard to describe upfront. For example, should responses be more polite or more casual? Such traits are sometimes summarized as model charac…

cs.CL2025

Investigating Co-Constructive Behavior of Large Language Models in Explanation Dialogues

Leandra Fichtel, Maximilian Spliethöver, Eyke Hüllermeier +9

The ability to generate explanations that are understood by explainees is the quintessence of explainable artificial intelligence. Since understanding depends on the explainee's ba…

cs.CL2025

Inverse Constitutional AI: Compressing Preferences into Principles

Arduin Findeis, Timo Kaufmann, Eyke Hüllermeier +2

Feedback data is widely used for fine-tuning and evaluating state-of-the-art AI models. Pairwise text preferences, where human or AI annotators select the "better" of two options,…

cs.CL2025

Adaptive Prompting: Ad-hoc Prompt Composition for Social Bias Detection

Maximilian Spliethöver, Tim Knebler, Fabian Fumagalli +4

Recent advances on instruction fine-tuning have led to the development of various prompting techniques for large language models, such as explicit reasoning steps. However, the suc…

cs.CL2024

Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction

Stefan Heid, Marcel Wever, Eyke Hüllermeier

Syntactic annotation of corpora in the form of part-of-speech (POS) tags is a key requirement for both linguistic research and subsequent automated natural language processing (NLP…