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272689881 | 2409.09513 | 2024-09-14 | Planning Transformer: Long-Horizon Offline Reinforcement Learning with Planning Tokens | Supervised learning approaches to offline reinforcement learning, particularly those utilizing the Decision Transformer, have shown effectiveness in continuous environments and for sparse rewards. However, they often struggle with long-horizon tasks due to the high compounding error of auto-regressive models. To overco... | [
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272689457 | 2409.09356 | 2024-09-14 | Towards Robust Detection of Open Source Software Supply Chain Poisoning Attacks in Industry Environments | The exponential growth of open-source package ecosystems, particularly NPM and PyPI, has led to an alarming increase in software supply chain poisoning attacks. Existing static analysis methods struggle with high false positive rates and are easily thwarted by obfuscation and dynamic code execution techniques. While dy... | [
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272689641 | 2409.09369 | 2024-09-14 | Interpretable Vision-Language Survival Analysis with Ordinal Inductive Bias for Computational Pathology | Histopathology Whole-Slide Images (WSIs) provide an important tool to assess cancer prognosis in computational pathology (CPATH). While existing survival analysis (SA) approaches have made exciting progress, they are generally limited to adopting highly-expressive network architectures and only coarse-grained patient-l... | [
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272689503 | 2409.09322 | 2024-09-14 | A Compressive Memory-based Retrieval Approach for Event Argument Extraction | Recent works have demonstrated the effectiveness of retrieval augmentation in the Event Argument Extraction (EAE) task. However, existing retrieval-based EAE methods have two main limitations: (1) input length constraints and (2) the gap between the retriever and the inference model. These issues limit the diversity an... | [
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272986778 | 2409.18980 | 2024-09-14 | IW-Bench: Evaluating Large Multimodal Models for Converting Image-to-Web | Recently advancements in large multimodal models have led to significant strides in image comprehension capabilities. Despite these advancements, there is a lack of the robust benchmark specifically for assessing the Image-to-Web conversion proficiency of these large models. Primarily, it is essential to ensure the int... | [
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272705367 | 2409.11430 | 2024-09-14 | Federated Learning with Quantum Computing and Fully Homomorphic Encryption: A Novel Computing Paradigm Shift in Privacy-Preserving ML | The widespread deployment of products powered by machine learning models is raising concerns around data privacy and information security worldwide. To address this issue, Federated Learning was first proposed as a privacy-preserving alternative to conventional methods that allow multiple learning clients to share mode... | [
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272689502 | 2409.09304 | 2024-09-14 | Consistent Spectral Clustering in Hyperbolic Spaces | Clustering, as an unsupervised technique, plays a pivotal role in various data analysis applications. Among clustering algorithms, Spectral Clustering on Euclidean Spaces has been extensively studied. However, with the rapid evolution of data complexity, Euclidean Space is proving to be inefficient for representing and... | [
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277787189 | 2409.10570 | 2024-09-14 | Protecting Copyright of Medical Pre-trained Language Models: Training-Free Backdoor Model Watermarking | With the advancement of intelligent healthcare, medical pre-trained language models (Med-PLMs) have emerged and demonstrated significant effectiveness in downstream medical tasks. While these models are valuable assets, they are vulnerable to misuse and theft, requiring copyright protection. However, existing watermark... | [
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272689844 | 2409.09418 | 2024-09-14 | Distributed Clustering based on Distributional Kernel | This paper introduces a new framework for clustering in a distributed network called Distributed Clustering based on Distributional Kernel (K) or KDC that produces the final clusters based on the similarity with respect to the distributions of initial clusters, as measured by K. It is the only framework that satisfies ... | [
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272689974 | 2409.09441 | 2024-09-14 | PIP-Loco: A Proprioceptive Infinite Horizon Planning Framework for Quadrupedal Robot Locomotion | A core strength of Model Predictive Control (MPC) for quadrupedal locomotion has been its ability to enforce constraints and provide interpretability of the sequence of commands over the horizon. However, despite being able to plan, MPC struggles to scale with task complexity, often failing to achieve robust behavior o... | [
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272690036 | 2409.09790 | 2024-09-15 | Multiple Rotation Averaging with Constrained Reweighting Deep Matrix Factorization | Multiple rotation averaging plays a crucial role in computer vision and robotics domains. The conventional optimization-based methods optimize a nonlinear cost function based on certain noise assumptions, while most previous learning-based methods require ground truth labels in the supervised training process. Recogniz... | [
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272689669 | 2409.09721 | 2024-09-15 | Finetuning CLIP to Reason about Pairwise Differences | Vision-language models (VLMs) such as CLIP are trained via contrastive learning between text and image pairs, resulting in aligned image and text embeddings that are useful for many downstream tasks. A notable drawback of CLIP, however, is that the resulting embedding space seems to lack some of the structure of its pu... | [
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272689168 | 2409.09748 | 2024-09-15 | Explore the Hallucination on Low-level Perception for MLLMs | The rapid development of Multi-modality Large Language Models (MLLMs) has significantly influenced various aspects of industry and daily life, showcasing impressive capabilities in visual perception and understanding. However, these models also exhibit hallucinations, which limit their reliability as AI systems, especi... | [
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272689379 | 2409.09722 | 2024-09-15 | Measuring Recency Bias In Sequential Recommendation Systems | Recency bias in a sequential recommendation system refers to the overly high emphasis placed on recent items within a user session. This bias can diminish the serendipity of recommendations and hinder the system's ability to capture users' long-term interests, leading to user disengagement. We propose a simple yet effe... | [
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272689839 | 2409.09707 | 2024-09-15 | Synergistic Spotting and Recognition of Micro-Expression via Temporal State Transition | Micro-expressions are involuntary facial movements that cannot be consciously controlled, conveying subtle cues with substantial real-world applications. The analysis of micro-expressions generally involves two main tasks: spotting micro-expression intervals in long videos and recognizing the emotions associated with t... | [
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272689854 | 2409.09564 | 2024-09-15 | TG-LLaVA: Text Guided LLaVA via Learnable Latent Embeddings | Currently, inspired by the success of vision-language models (VLMs), an increasing number of researchers are focusing on improving VLMs and have achieved promising results. However, most existing methods concentrate on optimizing the connector and enhancing the language model component, while neglecting improvements to... | [
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272690349 | 2409.09692 | 2024-09-15 | Predicting building types and functions at transnational scale | Building-specific knowledge such as building type and function information is important for numerous energy applications. However, comprehensive datasets containing this information for individual households are missing in many regions of Europe. For the first time, we investigate whether it is feasible to predict buil... | [
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273654146 | 2410.20313 | 2024-09-15 | Efficient Circuit Wire Cutting Based on Commuting Groups | Current quantum devices face challenges when dealing with large circuits due to error rates as circuit size and the number of qubits increase. The circuit wire-cutting technique addresses this issue by breaking down a large circuit into smaller, more manageable subcircuits. However, the exponential increase in the numb... | [
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272690371 | 2409.09783 | 2024-09-15 | Learning Rate Optimization for Deep Neural Networks Using Lipschitz Bandits | Learning rate is a crucial parameter in training of neural networks. A properly tuned learning rate leads to faster training and higher test accuracy. In this paper, we propose a Lipschitz bandit-driven approach for tuning the learning rate of neural networks. The proposed approach is compared with the popular HyperOpt... | [
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272689575 | 2409.09696 | 2024-09-15 | AutoJournaling: A Context-Aware Journaling System Leveraging MLLMs on Smartphone Screenshots | Journaling offers significant benefits, including fostering self-reflection, enhancing writing skills, and aiding in mood monitoring. However, many people abandon the practice because traditional journaling is time-consuming, and detailed life events may be overlooked if not recorded promptly. Given that smartphones ar... | [
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273162937 | 2410.02998 | 2024-09-15 | Q-SCALE: Quantum computing-based Sensor Calibration for Advanced Learning and Efficiency | In a world burdened by air pollution, the integration of state-of-the-art sensor calibration techniques utilizing Quantum Computing (QC) and Machine Learning (ML) holds promise for enhancing the accuracy and efficiency of air quality monitoring systems in smart cities. This article investigates the process of calibrati... | [
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272689905 | 2409.09569 | 2024-09-15 | Bias Begets Bias: The Impact of Biased Embeddings on Diffusion Models | With the growing adoption of Text-to-Image (TTI) systems, the social biases of these models have come under increased scrutiny. Herein we conduct a systematic investigation of one such source of bias for diffusion models: embedding spaces. First, because traditional classifier-based fairness definitions require true la... | [
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277857528 | 2409.09586 | 2024-09-15 | ValueCompass: A Framework for Measuring Contextual Value Alignment Between Human and LLMs | As AI systems become more advanced, ensuring their alignment with a diverse range of individuals and societal values becomes increasingly critical. But how can we capture fundamental human values and assess the degree to which AI systems align with them? We introduce ValueCompass, a framework of fundamental values, gro... | [
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272689173 | 2409.09668 | 2024-09-15 | EditBoard: Towards a Comprehensive Evaluation Benchmark for Text-Based Video Editing Models | The rapid development of diffusion models has significantly advanced AI-generated content (AIGC), particularly in Text-to-Image (T2I) and Text-to-Video (T2V) generation. Text-based video editing, leveraging these generative capabilities, has emerged as a promising field, enabling precise modifications to videos based o... | [
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272689557 | 2409.09740 | 2024-09-15 | VGG-Tex: A Vivid Geometry-Guided Facial Texture Estimation Model for High Fidelity Monocular 3D Face Reconstruction | 3D face reconstruction from monocular images has promoted the development of various applications such as augmented reality. Though existing methods have made remarkable progress, most of them emphasize geometric reconstruction, while overlooking the importance of texture prediction. To address this issue, we propose V... | [
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272709376 | 2409.11432 | 2024-09-15 | A hybrid solution for 2-UAV RAN slicing | It's possible to distribute the Internet to users via drones. However it is then necessary to place the drones according to the positions of the users. Moreover, the 5th Generation (5G) New Radio (NR) technology is designed to accommodate a wide range of applications and industries. The NGNM 5G White Paper \cite{5gwhit... | [
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272689973 | 2409.09785 | 2024-09-15 | Large Language Model Based Generative Error Correction: A Challenge and Baselines for Speech Recognition, Speaker Tagging, and Emotion Recognition | Given recent advances in generative AI technology, a key question is how large language models (LLMs) can enhance acoustic modeling tasks using text decoding results from a frozen, pretrained automatic speech recognition (ASR) model. To explore new capabilities in language modeling for speech processing, we introduce t... | [
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272689771 | 2409.09788 | 2024-09-15 | Reasoning Paths with Reference Objects Elicit Quantitative Spatial Reasoning in Large Vision-Language Models | Despite recent advances demonstrating vision-language models' (VLMs) abilities to describe complex relationships in images using natural language, their capability to quantitatively reason about object sizes and distances remains underexplored. In this work, we introduce a manually annotated benchmark, Q-Spatial Bench,... | [
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272689192 | 2409.09652 | 2024-09-15 | Unveiling Gender Bias in Large Language Models: Using Teacher's Evaluation in Higher Education As an Example | This paper investigates gender bias in Large Language Model (LLM)-generated teacher evaluations in higher education setting, focusing on evaluations produced by GPT-4 across six academic subjects. By applying a comprehensive analytical framework that includes Odds Ratio (OR) analysis, Word Embedding Association Test (W... | [
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272969340 | 2409.18636 | 2024-09-15 | Unsupervised Fingerphoto Presentation Attack Detection With Diffusion Models | Smartphone-based contactless fingerphoto authentication has become a reliable alternative to traditional contact-based fingerprint biometric systems owing to rapid advances in smartphone camera technology. Despite its convenience, fingerprint authentication through fingerphotos is more vulnerable to presentation attack... | [
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272690045 | 2409.09831 | 2024-09-15 | Generating Synthetic Free-text Medical Records with Low Re-identification Risk using Masked Language Modeling | The vast amount of available medical records has the potential to improve healthcare and biomedical research. However, privacy restrictions make these data accessible for internal use only. Recent works have addressed this problem by generating synthetic data using Causal Language Modeling. Unfortunately, by taking thi... | [
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272689627 | 2409.09770 | 2024-09-15 | Cluster Aware Graph Anomaly Detection | Graph anomaly detection has gained significant attention across various domains, particularly in critical applications like fraud detection in e-commerce platforms and insider threat detection in cybersecurity. Usually, these data are composed of multiple types (e.g., user information and transaction records for financ... | [
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272690004 | 2409.09779 | 2024-09-15 | Underwater Image Enhancement via Dehazing and Color Restoration | Underwater visual imaging is crucial for marine engineering, but it suffers from low contrast, blurriness, and color degradation, which hinders downstream analysis. Existing underwater image enhancement methods often treat the haze and color cast as a unified degradation process, neglecting their inherent independence ... | [
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272690022 | 2409.09681 | 2024-09-15 | E-Commerce Inpainting with Mask Guidance in Controlnet for Reducing Overcompletion | E-commerce image generation has always been one of the core demands in the e-commerce field. The goal is to restore the missing background that matches the main product given. In the post-AIGC era, diffusion models are primarily used to generate product images, achieving impressive results. This paper systematically an... | [
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272689513 | 2409.09860 | 2024-09-15 | Revisiting Physical-World Adversarial Attack on Traffic Sign Recognition: A Commercial Systems Perspective | Traffic Sign Recognition (TSR) is crucial for safe and correct driving automation. Recent works revealed a general vulnerability of TSR models to physical-world adversarial attacks, which can be low-cost, highly deployable, and capable of causing severe attack effects such as hiding a critical traffic sign or spoofing ... | [
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272689623 | 2409.09642 | 2024-09-15 | Extract and Diffuse: Latent Integration for Improved Diffusion-based Speech and Vocal Enhancement | Diffusion-based generative models have recently achieved remarkable results in speech and vocal enhancement due to their ability to model complex speech data distributions. While these models generalize well to unseen acoustic environments, they may not achieve the same level of fidelity as the discriminative models sp... | [
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272689616 | 2409.09676 | 2024-09-15 | Nebula: Efficient, Private and Accurate Histogram Estimation | We present \textit{Nebula}, a system for differentially private histogram estimation on data distributed among clients. \textit{Nebula} allows clients to independently decide whether to participate in the system, and locally encode their data so that an untrusted server only learns data values whose multiplicity exceed... | [
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272693872 | 2409.10574 | 2024-09-15 | Detection Made Easy: Potentials of Large Language Models for Solidity Vulnerabilities | The large-scale deployment of Solidity smart contracts on the Ethereum mainnet has increasingly attracted financially-motivated attackers in recent years. A few now-infamous attacks in Ethereum's history includes DAO attack in 2016 (50 million dollars lost), Parity Wallet hack in 2017 (146 million dollars locked), Beau... | [
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272689272 | 2409.09614 | 2024-09-15 | HJ-sampler: A Bayesian sampler for inverse problems of a stochastic process by leveraging Hamilton-Jacobi PDEs and score-based generative models | The interplay between stochastic processes and optimal control has been extensively explored in the literature. With the recent surge in the use of diffusion models, stochastic processes have increasingly been applied to sample generation. This paper builds on the log transform, known as the Cole-Hopf transform in Brow... | [
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