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Found 17 papers, 4 papers with code
Prove Symbolic Regression is NP-hard by Symbol Graph
Symbolic regression (SR) is the task of discovering a symbolic expression that fits a given data set from the space of mathematical expressions.
How Johnny Can Persuade LLMs to Jailbreak Them: Rethinking Persuasion to Challenge AI Safety by Humanizing LLMs
This paper introduces a new perspective to jailbreak LLMs as human-like communicators, to explore this overlooked intersection between everyday language interaction and AI safety.
Robust 3D Tracking with Quality-Aware Shape Completion
Considering that, we propose to construct a synthetic target representation composed of dense and complete point clouds depicting the target shape precisely by shape completion for robust 3D tracking.
Causal Bandits: Online Decision-Making in Endogenous Settings
To this end, in this paper, we consider the problem of online learning in linear stochastic contextual bandit problems with endogenous covariates.
Pathology Steered Stratification Network for Subtype Identification in Alzheimer's Disease
Alzheimer's disease (AD) is a heterogeneous, multifactorial neurodegenerative disorder characterized by beta-amyloid, pathologic tau, and neurodegeneration.
Social Influence Dialogue Systems: A Survey of Datasets and Models For Social Influence Tasks
Dialogue systems capable of social influence such as persuasion, negotiation, and therapy, are essential for extending the use of technology to numerous realistic scenarios.
Seamlessly Integrating Factual Information and Social Content with Persuasive Dialogue
Complex conversation settings such as persuasion involve communicating changes in attitude or behavior, so users' perspectives need to be addressed, even when not directly related to the topic.
Uncovering the System Vulnerability and Criticality of Human Brain under Dynamical Neuropathological Events in Alzheimer's Disease
Background: Despite the striking efforts in investigating neurobiological factors behind the acquisition of amyloid-\b{eta} (A), protein tau (T), and neurodegeneration ([N]) biomarkers, the mechanistic pathways of how AT[N] biomarkers spreading throughout the brain remain elusive.
Online Auction-Based Incentive Mechanism Design for Horizontal Federated Learning with Budget Constraint
To obtain a high-quality model, an incentive mechanism is necessary to motivate more high-quality workers with data and computing power.
Auction-Based Ex-Post-Payment Incentive Mechanism Design for Horizontal Federated Learning with Reputation and Contribution Measurement
Federated learning trains models across devices with distributed data, while protecting the privacy and obtaining a model similar to that of centralized ML.
Insta-VAX: A Multimodal Benchmark for Anti-Vaccine and Misinformation Posts Detection on Social Media
The dataset and classifiers contribute to monitoring and tracking of vaccine discussions for social scientific and public health efforts in combating the problem of vaccine misinformation.
Evaluation of In-Person Counseling Strategies To Develop Physical Activity Chatbot for Women
To develop intervention chatbots, the first step is to understand natural language conversation strategies in human conversation.
Dialoging Resonance: How Users Perceive, Reciprocate and React to Chatbot's Self-Disclosure in Conversational Recommendations
Using chatbots to deliver recommendations is increasingly popular.
Analyzing the Spatiotemporal Interaction and Propagation of ATN Biomarkers in Alzheimer's Disease using Longitudinal Neuroimaging Data
Three major biomarkers: beta-amyloid (A), pathologic tau (T), and neurodegeneration (N), are recognized as valid proxies for neuropathologic changes of Alzheimer's disease.
A Network-Guided Reaction-Diffusion Model of AT[N] Biomarkers in Alzheimer's Disease
Currently, many studies of Alzheimer's disease (AD) are investigating the neurobiological factors behind the acquisition of beta-amyloid (A), pathologic tau (T), and neurodegeneration ([N]) biomarkers from neuroimages.
Predictive and Generative Neural Networks for Object Functionality
Given a 3D object in isolation, our functional similarity network (fSIM-NET), a variation of the triplet network, is trained to predict the functionality of the object by inferring functionality-revealing interaction contexts.
Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Good
Developing intelligent persuasive conversational agents to change people's opinions and actions for social good is the frontier in advancing the ethical development of automated dialogue systems.
