GitHub

SafeEraser: Enhancing Safety in Multimodal Large Language Models through Multimodal Machine Unlearning

As Multimodal Large Language Models (MLLMs) develop, their potential security issues have become increasingly prominent. Machine Unlearning (MU), as an effective strategy for forgetting specific ...
IEEE

sQUlearn: A Python Library for Quantum Machine Learning [Focus: Quantum Software and Its Engineering]

Abstract: sQUlearn introduces a user-friendly, noisy intermediate-scale quantum (NISQ)-ready Python library for quantum machine learning (QML), designed for seamless integration with classical machine ...
GitHub

Belief in the Machine: Investigating Epistemological Blind Spots of Language Models

As language models (LMs) become integral to fields like healthcare, law, and journalism, their ability to differentiate between fact, belief, and knowledge is essential for reliable decision-making.
MIT Technology Review

Yann LeCun’s new venture is a contrarian bet against large language models

In an exclusive interview, the AI pioneer shares his plans for his new Paris-based company, AMI Labs. Yann LeCun is a Turing Award recipient and a top AI researcher, but he has long been a contrarian ...
IEEE

Toward Low-Resource Languages Machine Translation: A Language-Specific Fine-Tuning With LoRA for Specialized Large Language Models

Abstract: In the field of computational linguistics, addressing machine translation (MT) challenges for low-resource languages remains crucial, as these languages often lack extensive data compared to ...