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From the 1 of 5 linked papers with an AI index.

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5 papers

cs.CL2026

How Annotation Trains Annotators: Competence Development in Social Influence Recognition

Maciej Markiewicz, Beata Bajcar, Wiktoria Mieleszczenko-Kowszewicz +8

The paper studies how the process of annotating social influence techniques in dialogues can improve annotators' competence and confidence, and shows that these competence gains af…

cs.CL2026

IMPACTeen: Intentions, Manipulation, Persuasion, Annotations, and Consequences in Teen Communication Dataset

Aleksander Szczęsny, Wiktoria Mieleszczenko-Kowszewicz, Maciej Markiewicz +5

IMPACTeen is a dataset of textual social influence scenarios spanning interpersonal, media-based, and digital settings in an adolescent context. It contains 1,021 texts, 5,100 indi…

cs.CY2026

Sociodemographic Biases in Educational Counselling by Large Language Models

Tomasz Adamczyk, Wiktoria Mieleszczenko-Kowszewicz, Beata Bajcar +6

As Large Language Models (LLMs) are increasingly integrated into educational settings, understanding their potential biases is critical. This study examines sociodemographic biases…

cs.CL2025

Unraveling SITT: Social Influence Technique Taxonomy and Detection with LLMs

Wiktoria Mieleszczenko-Kowszewicz, Beata Bajcar, Aleksander Szczęsny +4

In this work we present the Social Influence Technique Taxonomy (SITT), a comprehensive framework of 58 empirically grounded techniques organized into nine categories, designed to…

cs.CL2025

Mind What You Ask For: Emotional and Rational Faces of Persuasion by Large Language Models

Wiktoria Mieleszczenko-Kowszewicz, Beata Bajcar, Jolanta Babiak +3

Be careful what you ask for, you just might get it. This saying fits with the way large language models (LLMs) are trained, which, instead of being rewarded for correctness, are in…