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Related papers: Gemma Needs Help: Investigating and Mitigating Emo…

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Human emotions are often not expressed directly, but regulated according to internal processes and social display rules. For affective computing systems, an understanding of how users regulate their emotions can be highly useful, for…

Depression, anxiety, and stress are widespread mental health concerns that increasingly drive individuals to seek information from Large Language Models (LLMs). This study investigates how eight LLMs (Claude Sonnet, Copilot, Gemini Pro,…

Computation and Language · Computer Science 2025-08-18 Arya VarastehNezhad , Reza Tavasoli , Soroush Elyasi , MohammadHossein LotfiNia , Hamed Farbeh

Studies of human psychology have demonstrated that people are more motivated to extend empathy to in-group members than out-group members (Cikara et al., 2011). In this study, we investigate how this aspect of intergroup relations in humans…

Computation and Language · Computer Science 2025-03-04 Yu Hou , Hal Daumé , Rachel Rudinger

Automated sentiment analysis using Large Language Model (LLM)-based models like ChatGPT, Gemini or LLaMA2 is becoming widespread, both in academic research and in industrial applications. However, assessment and validation of their…

Computation and Language · Computer Science 2024-02-06 Alessio Buscemi , Daniele Proverbio

Evaluating Large Language Models' (LLMs) anthropomorphic capabilities has become increasingly important in contemporary discourse. Utilizing the emotion appraisal theory from psychology, we propose to evaluate the empathy ability of LLMs,…

Computation and Language · Computer Science 2024-10-08 Jen-tse Huang , Man Ho Lam , Eric John Li , Shujie Ren , Wenxuan Wang , Wenxiang Jiao , Zhaopeng Tu , Michael R. Lyu

With the emergence of large language models (LLMs), investigating if they can surpass humans in areas such as emotion recognition and empathetic responding has become a focal point of research. This paper presents a comprehensive study…

Computation and Language · Computer Science 2024-06-10 Anuradha Welivita , Pearl Pu

In this work, we conduct an analysis to examine the consistency of Large Language Models (LLMs) with respect to their own generated responses in an emotionally-driven conversational context. Specifically, the text generated by LLM is framed…

Computation and Language · Computer Science 2026-05-08 Sneha Oram , Ojaswita Bhushan , Pushpak Bhattacharyya

Large language models are increasingly used for mental health support, yet little is known about whether their responses are psychologically safe across different help-seeking styles. We examine a foundational distinction in emotional…

Human-Computer Interaction · Computer Science 2026-05-22 Vivienne Bihe Chi , Adithya V Ganesan , Ryan L Boyd , Lyle Ungar , Sharath Chandra Guntuku

This work introduces Gemma, a family of lightweight, state-of-the art open models built from the research and technology used to create Gemini models. Gemma models demonstrate strong performance across academic benchmarks for language…

Computation and Language · Computer Science 2024-04-17 Gemma Team , Thomas Mesnard , Cassidy Hardin , Robert Dadashi , Surya Bhupatiraju , Shreya Pathak , Laurent Sifre , Morgane Rivière , Mihir Sanjay Kale , Juliette Love , Pouya Tafti , Léonard Hussenot , Pier Giuseppe Sessa , Aakanksha Chowdhery , Adam Roberts , Aditya Barua , Alex Botev , Alex Castro-Ros , Ambrose Slone , Amélie Héliou , Andrea Tacchetti , Anna Bulanova , Antonia Paterson , Beth Tsai , Bobak Shahriari , Charline Le Lan , Christopher A. Choquette-Choo , Clément Crepy , Daniel Cer , Daphne Ippolito , David Reid , Elena Buchatskaya , Eric Ni , Eric Noland , Geng Yan , George Tucker , George-Christian Muraru , Grigory Rozhdestvenskiy , Henryk Michalewski , Ian Tenney , Ivan Grishchenko , Jacob Austin , James Keeling , Jane Labanowski , Jean-Baptiste Lespiau , Jeff Stanway , Jenny Brennan , Jeremy Chen , Johan Ferret , Justin Chiu , Justin Mao-Jones , Katherine Lee , Kathy Yu , Katie Millican , Lars Lowe Sjoesund , Lisa Lee , Lucas Dixon , Machel Reid , Maciej Mikuła , Mateo Wirth , Michael Sharman , Nikolai Chinaev , Nithum Thain , Olivier Bachem , Oscar Chang , Oscar Wahltinez , Paige Bailey , Paul Michel , Petko Yotov , Rahma Chaabouni , Ramona Comanescu , Reena Jana , Rohan Anil , Ross McIlroy , Ruibo Liu , Ryan Mullins , Samuel L Smith , Sebastian Borgeaud , Sertan Girgin , Sholto Douglas , Shree Pandya , Siamak Shakeri , Soham De , Ted Klimenko , Tom Hennigan , Vlad Feinberg , Wojciech Stokowiec , Yu-hui Chen , Zafarali Ahmed , Zhitao Gong , Tris Warkentin , Ludovic Peran , Minh Giang , Clément Farabet , Oriol Vinyals , Jeff Dean , Koray Kavukcuoglu , Demis Hassabis , Zoubin Ghahramani , Douglas Eck , Joelle Barral , Fernando Pereira , Eli Collins , Armand Joulin , Noah Fiedel , Evan Senter , Alek Andreev , Kathleen Kenealy

Large language models (LLMs) can be said to have preferences: they reliably pick certain tasks and outputs over others, and preferences shaped by post-training and system prompts appear to shape much of their behaviour. But models can also…

Computation and Language · Computer Science 2026-05-19 Oscar Gilg , Pierre Beckmann , Daniel Paleka , Patrick Butlin

Controlling the behavior of large language models (LLMs) at inference time is essential for aligning outputs with human abilities and safety requirements. \emph{Activation steering} provides a lightweight alternative to prompt engineering…

Artificial Intelligence · Computer Science 2026-01-30 Diaoulé Diallo , Katharina Dworatzyk , Sophie Jentzsch , Peer Schütt , Sabine Theis , Tobias Hecking

Large language models (LLMs) exhibit strikingly conflicting behaviors: they can appear steadfastly overconfident in their initial answers whilst at the same time being prone to excessive doubt when challenged. To investigate this apparent…

Large Language Models (LLMs) demonstrate remarkable capabilities in text generation, yet their emotional consistency and semantic coherence in social media contexts remain insufficiently understood. This study investigates how LLMs handle…

Computation and Language · Computer Science 2025-11-05 Wentao Xu , Wenlu Fan , Yuqi Zhu , Bin Wang

Emotional prompting - the use of specific emotional diction in prompt engineering - has shown increasing promise in improving large language model (LLM) performance, truthfulness, and responsibility. However these studies have been limited…

Machine Learning · Computer Science 2026-04-10 Ameen Patel , Felix Lee , Kyle Liang , Joseph Thomas

This paper investigates the challenges of affect control in large language models (LLMs), focusing on their ability to express appropriate emotional states during extended dialogues. We evaluated state-of-the-art open-weight LLMs to assess…

Artificial Intelligence · Computer Science 2025-03-05 Gino Franco Fazzi , Julie Skoven Hinge , Stefan Heinrich , Paolo Burelli

As a relative quality comparison of model responses, human and Large Language Model (LLM) preferences serve as common alignment goals in model fine-tuning and criteria in evaluation. Yet, these preferences merely reflect broad tendencies,…

Computation and Language · Computer Science 2024-02-20 Junlong Li , Fan Zhou , Shichao Sun , Yikai Zhang , Hai Zhao , Pengfei Liu

Emotions exert an immense influence over human behavior and cognition in both commonplace and high-stress tasks. Discussions of whether or how to integrate large language models (LLMs) into everyday life (e.g., acting as proxies for, or…

Artificial Intelligence · Computer Science 2025-08-21 Mattson Ogg , Chace Ashcraft , Ritwik Bose , Raphael Norman-Tenazas , Michael Wolmetz

As Large Language Models (LLMs) continue to gain popularity due to their human-like traits and the intimacy they offer to users, their societal impact inevitably expands. This leads to the rising necessity for comprehensive studies to fully…

Artificial Intelligence · Computer Science 2025-01-07 Bojana Bodroza , Bojana M. Dinic , Ljubisa Bojic

Large Language Models (LLMs) have demonstrated surprising performance on many tasks, including writing supportive messages that display empathy. Here, we had these models generate empathic messages in response to posts describing common…

Computation and Language · Computer Science 2024-03-28 Yoon Kyung Lee , Jina Suh , Hongli Zhan , Junyi Jessy Li , Desmond C. Ong

Effective emotional support hinges on understanding users' emotions and needs to provide meaningful comfort during multi-turn interactions. Large Language Models (LLMs) show great potential for expressing empathy; however, they often…

Computation and Language · Computer Science 2025-05-23 Jing Ye , Lu Xiang , Yaping Zhang , Chengqing Zong
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