Large Language Model
A Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models
However, existing MU evaluation systems present several key challenges that can result in incomplete and inaccurate assessments.
Improved Generation of Adversarial Examples Against Safety-aligned LLMs Qizhang Li
Yiwen Guo leads the project and serves as the corresponding author.
Data-Driven Discovery of Dynamical Systems in Pharmacology using Large Language Models Samuel Holt
The discovery of dynamical systems models plays a fundamental role across various domains, including pharmacology, epidemiology, and physical systems.
A distributional simplicity bias in the learning dynamics of transformers
The remarkable capability of over-parameterised neural networks to generalise effectively has been explained by invoking a "simplicity bias": neural networks prevent overfitting by initially learning simple classifiers before progressing to
ImageNet3D: Towards General-Purpose Object-Level 3D Understanding Wufei Ma
A vision model with general-purpose object-level 3D understanding should be capable of inferring both 2D ( e.g., class name and bounding box) and 3D information ( e.g., 3D location and 3D viewpoint) for arbitrary rigid objects in natural
Benchmarking Long-context Document Understanding with Visualizations
Moreover, 33.7% of the questions are cross-page questions
ContextCite: Attributing Model Generation to Context Benjamin Cohen-Wang
How do language models use information provided as context when generating a response?
A Additional Results
The acronym dataset is a QA task that requires models to decode financial acronyms. The FinMA7B-full model achieved the highest ROUGE-1 score of 0.12 and the B.1 Why was the datasheet created? B.2 Has the dataset been used already? If so, where are the results so others can compare (e.g., links to published papers)? Y es, the dataset has already been used. It was employed in the FinLLM Share Task during the FinNLP-AgentScen Workshop at IJCAI 2024, known as the FinLLM Challenge.