Search Results for author:
Found 12 papers, 10 papers with code
Human Decision-making is Susceptible to AI-driven Manipulation
Through a randomized controlled trial with 233 participants, we examined human susceptibility to such manipulation in financial (e. g., purchases) and emotional (e. g., conflict resolution) decision-making contexts.
Enhanced Large Language Models for Effective Screening of Depression and Anxiety
Depressive and anxiety disorders are widespread, necessitating timely identification and management.
EmoBench: Evaluating the Emotional Intelligence of Large Language Models
Recent advances in Large Language Models (LLMs) have highlighted the need for robust, comprehensive, and challenging benchmarks.
CharacterGLM: Customizing Chinese Conversational AI Characters with Large Language Models
In this paper, we present CharacterGLM, a series of models built upon ChatGLM, with model sizes ranging from 6B to 66B parameters.
Task-Adaptive Tokenization: Enhancing Long-Form Text Generation Efficacy in Mental Health and Beyond
We propose task-adaptive tokenization as a way to adapt the generation pipeline to the specifics of a downstream task and enhance long-form generation in mental health.
COKE: A Cognitive Knowledge Graph for Machine Theory of Mind
Theory of mind (ToM) refers to humans' ability to understand and infer the desires, beliefs, and intentions of others.
PAL: Persona-Augmented Emotional Support Conversation Generation
As previous studies have demonstrated that seekers' persona is an important factor for effective support, we investigate whether there are benefits to modeling such information in dialogue models for support.
Chatbots for Mental Health Support: Exploring the Impact of Emohaa on Reducing Mental Distress in China
In this study, we analyze the effectiveness of Emohaa in reducing symptoms of mental distress.
Rethinking and Refining the Distinct Metric
We provide both empirical and theoretical evidence to show that our method effectively removes the biases existing in the original distinct score.
AugESC: Dialogue Augmentation with Large Language Models for Emotional Support Conversation
Applying this approach, we construct AugESC, an augmented dataset for the ESC task, which largely extends the scale and topic coverage of the crowdsourced ESConv corpus.
CEM: Commonsense-aware Empathetic Response Generation
We evaluate our approach on EmpatheticDialogues, which is a widely-used benchmark dataset for empathetic response generation.
Towards Emotional Support Dialog Systems
Emotional support is a crucial ability for many conversation scenarios, including social interactions, mental health support, and customer service chats.
