An Inexact Halpern Iteration with Application to Distributionally Robust...
The Halpern iteration for solving monotone inclusion problems has gained increasing interests in recent years due to its simple form and appealing convergence properties. In this paper, we investigate...
View ArticleEmojiCrypt: Prompt Encryption for Secure Communication with Large Language...
Cloud-based large language models (LLMs) such as ChatGPT have increasingly become integral to daily operations, serving as vital tools across various applications. While these models offer substantial...
View ArticleUsing YOLO v7 to Detect Kidney in Magnetic Resonance Imaging
Introduction This study explores the use of the latest You Only Look Once (YOLO V7) object detection method to enhance kidney detection in medical imaging by training and testing a modified YOLO V7 on...
View ArticleBIKED++: A Multimodal Dataset of 1.4 Million Bicycle Image and Parametric CAD...
This paper introduces a public dataset of 1.4 million procedurally-generated bicycle designs represented parametrically, as JSON files, and as rasterized images. The dataset is created through the use...
View ArticleAnatomically-Controllable Medical Image Generation with Segmentation-Guided...
Diffusion models have enabled remarkably high-quality medical image generation, which can help mitigate the expenses of acquiring and annotating new images by supplementing small or imbalanced...
View ArticleRL-VLM-F: Reinforcement Learning from Vision Language Foundation Model Feedback
Reward engineering has long been a challenge in Reinforcement Learning (RL) research, as it often requires extensive human effort and iterative processes of trial-and-error to design effective reward...
View ArticleTest-Time Adaptation for Depth Completion
It is common to observe performance degradation when transferring models trained on some (source) datasets to target testing data due to a domain gap between them. Existing methods for bridging this...
View ArticleBGE M3-Embedding: Multi-Lingual, Multi-Functionality, Multi-Granularity Text...
In this paper, we present a new embedding model, called M3-Embedding, which is distinguished for its versatility in Multi-Linguality, Multi-Functionality, and Multi-Granularity. It can support more...
View ArticleSolving Hierarchical Information-Sharing Dec-POMDPs: An Extensive-Form Game...
A recent theory shows that a multi-player decentralized partially observable Markov decision process can be transformed into an equivalent single-player game, enabling the application of...
View ArticleOn the Exploitation of DCT-Traces in the Generative-AI Domain
Deepfakes represent one of the toughest challenges in the world of Cybersecurity and Digital Forensics, especially considering the high-quality results obtained with recent generative AI-based...
View ArticleQuality and Trust in LLM-generated Code
Machine learning models are widely used but can also often be wrong. Users would benefit from a reliable indication of whether a given output from a given model should be trusted, so a rational...
View ArticlePrompting Large Language Models for Zero-Shot Clinical Prediction with...
The inherent complexity of structured longitudinal Electronic Health Records (EHR) data poses a significant challenge when integrated with Large Language Models (LLMs), which are traditionally tailored...
View ArticleSkip \n: A Simple Method to Reduce Hallucination in Large Vision-Language Models
Recent advancements in large vision-language models (LVLMs) have demonstrated impressive capability in visual information understanding with human language. Despite these advances, LVLMs still face...
View ArticleReproducibility, energy efficiency and performance of pseudorandom number...
Pseudo-Random Number Generators (PRNGs) have become ubiquitous in machine learning technologies because they are interesting for numerous methods. The field of machine learning holds the potential for...
View ArticleOn the Semantics of LM Latent Space: A Vocabulary-defined Approach
Understanding the latent space of language models (LM) is crucial to refining their performance and interpretability. Existing analyses often fall short in providing disentangled (model-centric)...
View ArticleInverse analysis of granular flows using differentiable graph neural network...
Inverse problems in granular flows, such as landslides and debris flows, involve estimating material parameters or boundary conditions based on target runout profile. Traditional high-fidelity...
View ArticleVision Mamba: Efficient Visual Representation Learning with Bidirectional...
Recently the state space models (SSMs) with efficient hardware-aware designs, i.e., the Mamba deep learning model, have shown great potential for long sequence modeling. Meanwhile building efficient...
View ArticleAugmenting Math Word Problems via Iterative Question Composing
Despite the advancements in large language models (LLMs) for mathematical reasoning, solving competition-level math problems remains a significant challenge, especially for open-source LLMs without...
View ArticleKeep or toss? A nonparametric score to evaluate solutions for noisy ICA
Independent Component Analysis (ICA) was introduced in the 1980's as a model for Blind Source Separation (BSS), which refers to the process of recovering the sources underlying a mixture of signals,...
View ArticleScalable network reconstruction in subquadratic time
Network reconstruction consists in determining the unobserved pairwise couplings between $N$ nodes given only observational data on the resulting behavior that is conditioned on those couplings --...
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