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Found 7 papers, 0 papers with code
Multi-Level Feedback Generation with Large Language Models for Empowering Novice Peer Counselors
We further design a self-improvement method on top of large language models to enhance the automatic generation of feedback.
Catastrophic Interference is Mitigated in Naturalistic Power-Law Learning Environments
In addition, because our method is orthogonal to other methods, future research can combine training in power-law environments with other continual learning mechanisms.
Pre-training LLMs using human-like development data corpus
Pre-trained Large Language Models (LLMs) have shown success in a diverse set of language inference and understanding tasks.
Human Behavioral Benchmarking: Numeric Magnitude Comparison Effects in Large Language Models
This research shows the utility of understanding LLMs using behavioral benchmarks and points the way to future work on the number representations of LLMs and their cognitive plausibility.
Helping the Helper: Supporting Peer Counselors via AI-Empowered Practice and Feedback
Millions of users come to online peer counseling platforms to seek support on diverse topics ranging from relationship stress to anxiety.
Modeling Motivational Interviewing Strategies On An Online Peer-to-Peer Counseling Platform
This work provides a deeper understanding of the use of motivational interviewing techniques on peer-to-peer counselor platforms and sheds light on how to build better training programs for volunteer counselors on online platforms.
WHEN FLUE MEETS FLANG: Benchmarks and Large Pre-trained Language Model for Financial Domain
To this end, we contribute the Financial Language Understanding Evaluation (FLUE), an open-source comprehensive suite of benchmarks for the financial domain.
