Emotionqueen: A benchmark for evaluating empathy of large language models
Emotional intelligence in large language models (LLMs) is of great importance in Natural
Language Processing. However, the previous research mainly focus on basic sentiment …
Language Processing. However, the previous research mainly focus on basic sentiment …
Xmecap: Meme caption generation with sub-image adaptability
Humor, deeply rooted in societal meanings and cultural details, poses a unique challenge
for machines. While advances have been made in natural language processing, real-world …
for machines. While advances have been made in natural language processing, real-world …
Nevlp: Noise-robust framework for efficient vision-language pre-training
The success of Vision Language Models (VLMs) on various vision-language tasks heavily
relies on pre-training with large scale web-crawled datasets. However, the noisy and …
relies on pre-training with large scale web-crawled datasets. However, the noisy and …
Learning to reweight for generalizable graph neural network
Graph Neural Networks (GNNs) show promising results for graph tasks. However, existing
GNNs' generalization ability will degrade when there exist distribution shifts between testing …
GNNs' generalization ability will degrade when there exist distribution shifts between testing …
Hotvcom: Generating buzzworthy comments for videos
In the era of social media video platforms, popular``hot-comments''play a crucial role in
attracting user impressions of short-form videos, making them vital for marketing and …
attracting user impressions of short-form videos, making them vital for marketing and …
Recent advancement of emotion cognition in large language models
Emotion cognition in large language models (LLMs) is crucial for enhancing performance
across various applications, such as social media, human-computer interaction, and mental …
across various applications, such as social media, human-computer interaction, and mental …
Learning to Reweight for Graph Neural Network
Graph Neural Networks (GNNs) show promising results for graph tasks. However, existing
GNNs' generalization ability will degrade when there exist distribution shifts between testing …
GNNs' generalization ability will degrade when there exist distribution shifts between testing …
CUPID: Improving Battle Fairness and Position Satisfaction in Online MOBA Games with a Re-matchmaking System
The multiplayer online battle arena (MOBA) genre has gained significant popularity and
economic success, attracting considerable research interest within the Human-Computer …
economic success, attracting considerable research interest within the Human-Computer …
Enhancing Exchange Rate Forecasting with Explainable Deep Learning Models
S Meng, A Chen, C Wang, M Zheng… - 2024 4th …, 2024 - ieeexplore.ieee.org
Accurate exchange rate prediction is fundamental to financial stability and international
trade, positioning it as a critical focus in economic and financial research. Traditional …
trade, positioning it as a critical focus in economic and financial research. Traditional …
Aviary: training language agents on challenging scientific tasks
S Narayanan, JD Braza, RR Griffiths… - arXiv preprint arXiv …, 2024 - arxiv.org
Solving complex real-world tasks requires cycles of actions and observations. This is
particularly true in science, where tasks require many cycles of analysis, tool use, and …
particularly true in science, where tasks require many cycles of analysis, tool use, and …