Scientific discovery in the age of artificial intelligence
Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment
and accelerate research, hel** scientists to generate hypotheses, design experiments …
and accelerate research, hel** scientists to generate hypotheses, design experiments …
The evolution of distributed systems for graph neural networks and their origin in graph processing and deep learning: A survey
Graph neural networks (GNNs) are an emerging research field. This specialized deep
neural network architecture is capable of processing graph structured data and bridges the …
neural network architecture is capable of processing graph structured data and bridges the …
Camel: Communicative agents for" mind" exploration of large language model society
The rapid advancement of chat-based language models has led to remarkable progress in
complex task-solving. However, their success heavily relies on human input to guide the …
complex task-solving. However, their success heavily relies on human input to guide the …
Datacomp: In search of the next generation of multimodal datasets
Multimodal datasets are a critical component in recent breakthroughs such as CLIP, Stable
Diffusion and GPT-4, yet their design does not receive the same research attention as model …
Diffusion and GPT-4, yet their design does not receive the same research attention as model …
Explainability for large language models: A survey
Large language models (LLMs) have demonstrated impressive capabilities in natural
language processing. However, their internal mechanisms are still unclear and this lack of …
language processing. However, their internal mechanisms are still unclear and this lack of …
A survey of machine unlearning
Today, computer systems hold large amounts of personal data. Yet while such an
abundance of data allows breakthroughs in artificial intelligence, and especially machine …
abundance of data allows breakthroughs in artificial intelligence, and especially machine …
Advances, challenges and opportunities in creating data for trustworthy AI
As artificial intelligence (AI) transitions from research to deployment, creating the appropriate
datasets and data pipelines to develop and evaluate AI models is increasingly the biggest …
datasets and data pipelines to develop and evaluate AI models is increasingly the biggest …
Counterfactual explanations and how to find them: literature review and benchmarking
R Guidotti - Data Mining and Knowledge Discovery, 2024 - Springer
Interpretable machine learning aims at unveiling the reasons behind predictions returned by
uninterpretable classifiers. One of the most valuable types of explanation consists of …
uninterpretable classifiers. One of the most valuable types of explanation consists of …
Trustworthy artificial intelligence: a review
Artificial intelligence (AI) and algorithmic decision making are having a profound impact on
our daily lives. These systems are vastly used in different high-stakes applications like …
our daily lives. These systems are vastly used in different high-stakes applications like …
Data-efficient Fine-tuning for LLM-based Recommendation
Leveraging Large Language Models (LLMs) for recommendation has recently garnered
considerable attention, where fine-tuning plays a key role in LLMs' adaptation. However, the …
considerable attention, where fine-tuning plays a key role in LLMs' adaptation. However, the …