Search Results for author:
Found 11 papers, 7 papers with code
The Generation Gap: Exploring Age Bias in the Value Systems of Large Language Models
We explore the alignment of values in Large Language Models (LLMs) with specific age groups, leveraging data from the World Value Survey across thirteen categories.
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.
ProSGNeRF: Progressive Dynamic Neural Scene Graph with Frequency Modulated Auto-Encoder in Urban Scenes
Implicit neural representation has demonstrated promising results in view synthesis for large and complex scenes.
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.
You Are What You Annotate: Towards Better Models through Annotator Representations
Annotator disagreement is ubiquitous in natural language processing (NLP) tasks.
EASE: An Easily-Customized Annotation System Powered by Efficiency Enhancement Mechanisms
Our results show that our system can meet the diverse needs of NLP researchers and significantly accelerate the annotation process.
Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Models
Not surprisingly, this has, in turn, made many NLP researchers -- especially those at the beginning of their careers -- worry about what NLP research area they should focus on.
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.
PsyQA: A Chinese Dataset for Generating Long Counseling Text for Mental Health Support
In this paper, we propose PsyQA, a Chinese dataset of psychological health support in the form of question and answer pair.
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.
SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge
To benefit the downstream tasks in sentiment analysis, we propose a novel language representation model called SentiLARE, which introduces word-level linguistic knowledge including part-of-speech tag and sentiment polarity (inferred from SentiWordNet) into pre-trained models.
