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Found 10 papers, 4 papers with code
Event Schema Induction with Double Graph Autoencoders
To induce event schemas from historical events, previous work uses an event-by-event scheme, ignoring the global structure of the entire schema graph.
RESIN-11: Schema-guided Event Prediction for 11 Newsworthy Scenarios
We introduce RESIN-11, a new schema-guided event extraction&prediction framework that can be applied to a large variety of newsworthy scenarios.
Synthia: Novel Concept Design with Affordance Composition
Text-to-image (T2I) models enable rapid concept design, making them widely used in AI-driven design.
Contrastive Visual Data Augmentation
Large multimodal models (LMMs) often struggle to recognize novel concepts, as they rely on pre-trained knowledge and have limited ability to capture subtle visual details.
LUME: LLM Unlearning with Multitask Evaluations
Unlearning aims to remove copyrighted, sensitive, or private content from large language models (LLMs) without a full retraining.
Unlearning as multi-task optimization: A normalized gradient difference approach with an adaptive learning rate
Machine unlearning has been used to remove unwanted knowledge acquired by large language models (LLMs).
ARMADA: Attribute-Based Multimodal Data Augmentation
To address these issues, we propose Attribute-based Multimodal Data Augmentation (ARMADA), a novel multimodal data augmentation method via knowledge-guided manipulation of visual attributes of the mentioned entities.
Chemical-Reaction-Aware Molecule Representation Learning
Molecule representation learning (MRL) methods aim to embed molecules into a real vector space.
On the Sensitivity of Adversarial Robustness to Input Data Distributions
Even a semantics-preserving transformations on the input data distribution can cause a significantly different robustness for the adversarial trained model that is both trained and evaluated on the new distribution.
advertorch v0.1: An Adversarial Robustness Toolbox based on PyTorch
advertorch is a toolbox for adversarial robustness research.
