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cs.CL2026

ODRA: Synthesizing Cognitive Behavioral Therapy Sessions with Structured Chain-Of-Thought and Dynamic Patient Resistance

Javier Rodriguez-Juan, Hiba Arnaout, Jose Garcia-Rodriguez +2

Synthetic generation of Cognitive Behavioral Therapy (CBT) sessions is challenged by two competing demands: adhering to strict therapeutic structure while modeling the resistant, u…

cs.CL2026

Expert Preference-based Evaluation of Automated Related Work Generation

Furkan Şahinuç, Subhabrata Dutta, Iryna Gurevych

Expert domain writing, such as scientific writing, typically demands extensive domain knowledge. Although large language models (LLMs) show promising potential in this task, evalua…

cs.CL2026

UKP_Psycontrol at SemEval-2026 Task 2: Modeling Valence and Arousal Dynamics from Text

Darya Hryhoryeva, Amaia Zurinaga, Hamidreza Jamalabadi +1

This paper presents our system developed for SemEval-2026 Task 2. The task requires modeling both current affect and short-term affective change in chronologically ordered user-gen…

cs.CL2026

Graph2Counsel: Clinically Grounded Synthetic Counseling Dialogue Generation from Client Psychological Graphs

Aishik Mandal, Hiba Arnaout, Clarissa W. Ong +5

Rising demand for mental health support has increased interest in using Large Language Models (LLMs) for counseling. However, adapting LLMs to this high-risk safety-critical domain…

cs.CL2026

LLMs as Cultural Archives: Cultural Commonsense Knowledge Graph Extraction

Junior Cedric Tonga, Chen Cecilia Liu, Iryna Gurevych +1

Large language models (LLMs) encode rich cultural knowledge learned from diverse web-scale data, offering an unprecedented opportunity to model cultural commonsense at scale. Yet t…

cs.CL2026

Tailored Emotional LLM-Supporter: Enhancing Cultural Sensitivity

Chen Cecilia Liu, Hiba Arnaout, Nils Kovačić +2

Large language models (LLMs) show promise in offering emotional support and generating empathetic responses for individuals in distress, but their ability to deliver culturally sen…