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272694646 | 2409.10868 | 2024-09-17 | LVBA: LiDAR-Visual Bundle Adjustment for RGB Point Cloud Mapping | Point cloud maps with accurate color are crucial in robotics and mapping applications. Existing approaches for producing RGB-colorized maps are primarily based on real-time localization using filter-based estimation or sliding window optimization, which may lack accuracy and global consistency. In this work, we introdu... | [
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272693963 | 2409.11091 | 2024-09-17 | Online Combinatorial Allocations and Auctions with Few Samples | In online combinatorial allocations/auctions, n bidders sequentially arrive, each with a combinatorial valuation (such as submodular/XOS) over subsets of m indivisible items. The aim is to immediately allocate a subset of the remaining items to maximize the total welfare, defined as the sum of bidder valuations. A long... | [
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273162464 | 2410.02774 | 2024-09-17 | Estimating the Unobservable Components of Electricity Demand Response with Inverse Optimization | Understanding and predicting the electricity demand responses to prices are critical activities for system operators, retailers, and regulators. While conventional machine learning and time series analyses have been adequate for the routine demand patterns that have adapted only slowly over many years, the emergence of... | [
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272694624 | 2409.11071 | 2024-09-17 | Improve Machine Learning carbon footprint using Parquet dataset format and Mixed Precision training for regression models -- Part II | This is the 2nd part of the dissertation for my master degree and compared the power consumption using the Comma-Separated-Values (CSV) and parquet dataset format with the default floating point (32bit) and Nvidia mixed precision (16bit and 32bit) while training a regression ML model. The same custom PC as per the 1st ... | [
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272693913 | 2409.11212 | 2024-09-17 | Self-Evolutionary Large Language Models through Uncertainty-Enhanced Preference Optimization | Iterative preference optimization has recently become one of the de-facto training paradigms for large language models (LLMs), but the performance is still underwhelming due to too much noisy preference data yielded in the loop. To combat this issue, we present an \textbf{U}ncertainty-enhanced \textbf{P}reference \text... | [
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272703814 | 2409.11516 | 2024-09-17 | Learning-Augmented Frequency Estimation in Sliding Windows | We show how to utilize machine learning approaches to improve sliding window algorithms for approximate frequency estimation problems, under the ``algorithms with predictions'' framework. In this dynamic environment, previous learning-augmented algorithms are less effective, since properties in sliding window resolutio... | [
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272708652 | 2409.11546 | 2024-09-17 | NCT-CRC-HE: Not All Histopathological Datasets Are Equally Useful | Numerous deep learning-based solutions have been proposed for histopathological image analysis over the past years. While they usually demonstrate exceptionally high accuracy, one key question is whether their precision might be affected by low-level image properties not related to histopathology but caused by microsco... | [
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272694181 | 2409.11307 | 2024-09-17 | GS-Net: Generalizable Plug-and-Play 3D Gaussian Splatting Module | 3D Gaussian Splatting (3DGS) integrates the strengths of primitive-based representations and volumetric rendering techniques, enabling real-time, high-quality rendering. However, 3DGS models typically overfit to single-scene training and are highly sensitive to the initialization of Gaussian ellipsoids, heuristically d... | [
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272694389 | 2409.10944 | 2024-09-17 | Contrasformer: A Brain Network Contrastive Transformer for Neurodegenerative Condition Identification | Understanding neurological disorder is a fundamental problem in neuroscience, which often requires the analysis of brain networks derived from functional magnetic resonance imaging (fMRI) data. Despite the prevalence of Graph Neural Networks (GNNs) and Graph Transformers in various domains, applying them to brain netwo... | [
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272694656 | 2409.11200 | 2024-09-17 | LoRa Communication for Agriculture 4.0: Opportunities, Challenges, and Future Directions | The emerging field of smart agriculture leverages the Internet of Things (IoT) to revolutionize farming practices. This paper investigates the transformative potential of Long Range (LoRa) technology as a key enabler of long-range wireless communication for agricultural IoT systems. By reviewing existing literature, we... | [
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272694096 | 2409.11313 | 2024-09-17 | Protecting Privacy in Software Logs: What Should Be Anonymized? | Software logs, generated during the runtime of software systems, are essential for various development and analysis activities, such as anomaly detection and failure diagnosis. However, the presence of sensitive information in these logs poses significant privacy concerns, particularly regarding Personally Identifiable... | [
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272694272 | 2409.11233 | 2024-09-17 | Evaluating the Impact of Compression Techniques on Task-Specific Performance of Large Language Models | Large language models (LLMs) offer powerful capabilities but incur substantial computational costs, driving the need for efficient compression techniques. This study evaluates the impact of popular compression methods - Magnitude Pruning, SparseGPT, and Wanda - on the LLaMA-2-7B model, focusing on the trade-offs betwee... | [
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272704031 | 2409.11561 | 2024-09-17 | Hypergraph-based Coordinated Task Allocation and Socially-aware Navigation for Multi-Robot Systems | A team of multiple robots seamlessly and safely working in human-filled public environments requires adaptive task allocation and socially-aware navigation that account for dynamic human behavior. Current approaches struggle with highly dynamic pedestrian movement and the need for flexible task allocation. We propose H... | [
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272693943 | 2409.11174 | 2024-09-17 | Identifying Influential nodes in Brain Networks via Self-Supervised Graph-Transformer | Studying influential nodes (I-nodes) in brain networks is of great significance in the field of brain imaging. Most existing studies consider brain connectivity hubs as I-nodes. However, this approach relies heavily on prior knowledge from graph theory, which may overlook the intrinsic characteristics of the brain netw... | [
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273162725 | 2410.02773 | 2024-09-17 | Mind the Uncertainty in Human Disagreement: Evaluating Discrepancies between Model Predictions and Human Responses in VQA | Large vision-language models frequently struggle to accurately predict responses provided by multiple human annotators, particularly when those responses exhibit human uncertainty. In this study, we focus on the Visual Question Answering (VQA) task, and we comprehensively evaluate how well the state-of-the-art vision-l... | [
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272694172 | 2409.11329 | 2024-09-17 | Reducing Catastrophic Forgetting in Online Class Incremental Learning Using Self-Distillation | In continual learning, there is a serious problem of catastrophic forgetting, in which previous knowledge is forgotten when a model learns new tasks. Various methods have been proposed to solve this problem. Replay methods which replay data from previous tasks in later training, have shown good accuracy. However, repla... | [
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272710312 | 2409.11583 | 2024-09-17 | Uncertainty Decomposition and Error Margin Detection of Homodyned-K Distribution in Quantitative Ultrasound | Homodyned K-distribution (HK-distribution) parameter estimation in quantitative ultrasound (QUS) has been recently addressed using Bayesian Neural Networks (BNNs). BNNs have been shown to significantly reduce computational time in speckle statistics-based QUS without compromising accuracy and precision. Additionally, t... | [
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272987039 | 2409.18991 | 2024-09-17 | Surveying the MLLM Landscape: A Meta-Review of Current Surveys | The rise of Multimodal Large Language Models (MLLMs) has become a transformative force in the field of artificial intelligence, enabling machines to process and generate content across multiple modalities, such as text, images, audio, and video. These models represent a significant advancement over traditional unimodal... | [
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272693830 | 2409.10908 | 2024-09-17 | Clustering with Non-adaptive Subset Queries | Recovering the underlying clustering of a set $U$ of $n$ points by asking pair-wise same-cluster queries has garnered significant interest in the last decade. Given a query $S \subset U$, $|S|=2$, the oracle returns yes if the points are in the same cluster and no otherwise. For adaptive algorithms with pair-wise queri... | [
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272694667 | 2409.11325 | 2024-09-17 | TopoMaskV2: Enhanced Instance-Mask-Based Formulation for the Road Topology Problem | Recently, the centerline has become a popular representation of lanes due to its advantages in solving the road topology problem. To enhance centerline prediction, we have developed a new approach called TopoMask. Unlike previous methods that rely on keypoints or parametric methods, TopoMask utilizes an instance-mask-b... | [
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272694176 | 2409.11111 | 2024-09-17 | Few-Shot Domain Adaptation for Learned Image Compression | Learned image compression (LIC) has achieved state-of-the-art rate-distortion performance, deemed promising for next-generation image compression techniques. However, pre-trained LIC models usually suffer from significant performance degradation when applied to out-of-training-domain images, implying their poor general... | [
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272694637 | 2409.11219 | 2024-09-17 | Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models | The machine learning community is increasingly recognizing the importance of fostering trust and safety in modern generative AI (GenAI) models. We posit machine unlearning (MU) as a crucial foundation for developing safe, secure, and trustworthy GenAI models. Traditional MU methods often rely on stringent assumptions a... | [
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272708767 | 2409.11536 | 2024-09-17 | Obfuscation Based Privacy Preserving Representations are Recoverable Using Neighborhood Information | Rapid growth in the popularity of AR/VR/MR applications and cloud-based visual localization systems has given rise to an increased focus on the privacy of user content in the localization process. This privacy concern has been further escalated by the ability of deep neural networks to recover detailed images of a scen... | [
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272694313 | 2409.11281 | 2024-09-17 | Beyond Relevance: Improving User Engagement by Personalization for Short-Video Search | Personalized search has been extensively studied in various applications, including web search, e-commerce, social networks, etc. With the soaring popularity of short-video platforms, exemplified by TikTok and Kuaishou, the question arises: can personalization elevate the realm of short-video search, and if so, which t... | [
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273162251 | 2410.02777 | 2024-09-17 | Secure and Confidential Certificates of Online Fairness | The black-box service model enables ML service providers to serve clients while keeping their intellectual property and client data confidential. Confidentiality is critical for delivering ML services legally and responsibly, but makes it difficult for outside parties to verify important model properties such as fairne... | [
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272694147 | 2409.10794 | 2024-09-17 | Multi-frequency Electrical Impedance Tomography Reconstruction with Multi-Branch Attention Image Prior | Multi-frequency Electrical Impedance Tomography (mfEIT) is a promising biomedical imaging technique that estimates tissue conductivities across different frequencies. Current state-of-the-art (SOTA) algorithms, which rely on supervised learning and Multiple Measurement Vectors (MMV), require extensive training data, ma... | [
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272694014 | 2409.11056 | 2024-09-17 | Large Language Models are Good Multi-lingual Learners : When LLMs Meet Cross-lingual Prompts | With the advent of Large Language Models (LLMs), generating rule-based data for real-world applications has become more accessible. Due to the inherent ambiguity of natural language and the complexity of rule sets, especially in long contexts, LLMs often struggle to follow all specified rules, frequently omitting at le... | [
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272694681 | 2409.11305 | 2024-09-17 | Measurement of top-quark pair production in association with charm quarks in proton-proton collisions at $\sqrt{s}=13$ TeV with the ATLAS detector | Inclusive cross-sections for top-quark pair production in association with charm quarks are measured with proton-proton collision data at a center-of-mass energy of 13 TeV corresponding to an integrated luminosity of 140 fb$^{-1}$, collected with the ATLAS experiment at the LHC between 2015 and 2018. The measurements a... | [
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272694127 | 2409.10883 | 2024-09-17 | CREAM: Comparison-Based Reference-Free ELO-Ranked Automatic Evaluation for Meeting Summarization | Large Language Models (LLMs) have spurred interest in automatic evaluation methods for summarization, offering a faster, more cost-effective alternative to human evaluation. However, existing methods often fall short when applied to complex tasks like long-context summarizations and dialogue-based meeting summarization... | [
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272694146 | 2409.11143 | 2024-09-17 | Semformer: Transformer Language Models with Semantic Planning | Next-token prediction serves as the dominant component in current neural language models. During the training phase, the model employs teacher forcing, which predicts tokens based on all preceding ground truth tokens. However, this approach has been found to create shortcuts, utilizing the revealed prefix to spuriously... | [
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272694226 | 2409.10942 | 2024-09-17 | Optimizing TinyML: The Impact of Reduced Data Acquisition Rates for Time Series Classification on Microcontrollers | Tiny Machine Learning (TinyML) enables efficient, lowcost, and privacy preserving machine learning inference directly on microcontroller units (MCUs) connected to sensors. Optimizing models for these constrained environments is crucial. This paper investigates how reducing data acquisition rates affects TinyML models f... | [
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272708263 | 2409.11500 | 2024-09-17 | Multi-Document Grounded Multi-Turn Synthetic Dialog Generation | We introduce a technique for multi-document grounded multi-turn synthetic dialog generation that incorporates three main ideas. First, we control the overall dialog flow using taxonomy-driven user queries that are generated with Chain-of-Thought (CoT) prompting. Second, we support the generation of multi-document groun... | [
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272705257 | 2409.11527 | 2024-09-17 | Improving LLM Reasoning with Multi-Agent Tree-of-Thought Validator Agent | Multi-agent strategies have emerged as a promising approach to enhance the reasoning abilities of Large Language Models (LLMs) by assigning specialized roles in the problem-solving process. Concurrently, Tree of Thoughts (ToT) methods have shown potential in improving reasoning for complex question-answering tasks by e... | [
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272693958 | 2409.11254 | 2024-09-17 | Towards Novel Malicious Packet Recognition: A Few-Shot Learning Approach | As the complexity and connectivity of networks increase, the need for novel malware detection approaches becomes imperative. Traditional security defenses are becoming less effective against the advanced tactics of today's cyberattacks. Deep Packet Inspection (DPI) has emerged as a key technology in strengthening netwo... | [
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272693916 | 2409.11270 | 2024-09-17 | Geometry Aware Meta-Learning Neural Network for Joint Phase and Precoder Optimization in RIS | In reconfigurable intelligent surface (RIS) aided systems, the joint optimization of the precoder matrix at the base station and the phase shifts of the RIS elements involves significant complexity. In this paper, we propose a complex-valued, geometry aware meta-learning neural network that maximizes the weighted sum r... | [
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272694046 | 2409.11055 | 2024-09-17 | Exploring the Trade-Offs: Quantization Methods, Task Difficulty, and Model Size in Large Language Models From Edge to Giant | Quantization has gained attention as a promising solution for the cost-effective deployment of large and small language models. However, most prior work has been limited to perplexity or basic knowledge tasks and lacks a comprehensive evaluation of recent models like Llama-3.3. In this paper, we conduct a comprehensive... | [
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272694349 | 2409.11250 | 2024-09-17 | Linear Recency Bias During Training Improves Transformers' Fit to Reading Times | Recent psycholinguistic research has compared human reading times to surprisal estimates from language models to study the factors shaping human sentence processing difficulty. Previous studies have shown a strong fit between surprisal values from Transformers and reading times. However, standard Transformers work with... | [
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279250709 | 2409.11554 | 2024-09-17 | PropEnc: A Property Encoder for Graph Neural Networks | Graph machine learning, particularly using graph neural networks, heavily relies on node features. However, many real-world systems, such as social and biological networks, lack node features due to privacy concerns, incomplete data, or collection limitations. Structural and positional encoding are commonly used to add... | [
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272707887 | 2409.11449 | 2024-09-17 | Evaluation of pretrained language models on music understanding | Music-text multimodal systems have enabled new approaches to Music Information Research (MIR) applications such as audio-to-text and text-to-audio retrieval, text-based song generation, and music captioning. Despite the reported success, little effort has been put into evaluating the musical knowledge of Large Language... | [
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272694555 | 2409.10897 | 2024-09-17 | AutoSpec: Automated Generation of Neural Network Specifications | The increasing adoption of neural networks in learning-augmented systems highlights the importance of model safety and robustness, particularly in safety-critical domains. Despite progress in the formal verification of neural networks, current practices require users to manually define model specifications -- propertie... | [
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272693773 | 2409.11028 | 2024-09-17 | Estimating the distribution of numerosity and non-numerical visual magnitudes in natural scenes using computer vision | Humans share with many animal species the ability to perceive and approximately represent the number of objects in visual scenes. This ability improves throughout childhood, suggesting that learning and development play a key role in shaping our number sense. This hypothesis is further supported by computational invest... | [
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272693925 | 2409.10825 | 2024-09-17 | Unveiling and Mitigating Bias in Large Language Model Recommendations: A Path to Fairness | excel in delivering comprehensive suggestions by deeply analyzing content and user behavior. However, they often inherit biases from skewed training data, favoring mainstream content while underrepresenting diverse or non-traditional options. This study explores the interplay between bias and LLM-based recommendation s... | [
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272694063 | 2409.11041 | 2024-09-17 | Towards No-Code Programming of Cobots: Experiments with Code Synthesis by Large Code Models for Conversational Programming | While there has been a lot of research recently on robots in household environments, at the present time, most robots in existence can be found on shop floors, and most interactions between humans and robots happen there. ``Collaborative robots'' (cobots) designed to work alongside humans on assembly lines traditionall... | [
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272694444 | 2409.10953 | 2024-09-17 | Robust High-Speed State Estimation for Off-road Navigation using Radar Velocity Factors | Enabling robot autonomy in complex environments for mission critical application requires robust state estimation. Particularly under conditions where the exteroceptive sensors, which the navigation depends on, can be degraded by environmental challenges thus, leading to mission failure. It is precisely in such challen... | [
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272694581 | 2409.11119 | 2024-09-17 | Multi-Cohort Framework with Cohort-Aware Attention and Adversarial Mutual-Information Minimization for Whole Slide Image Classification | Whole Slide Images (WSIs) are critical for various clinical applications, including histopathological analysis. However, current deep learning approaches in this field predominantly focus on individual tumor types, limiting model generalization and scalability. This relatively narrow focus ultimately stems from the inh... | [
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272694658 | 2409.11063 | 2024-09-17 | A Unifying Action Principle for Classical Mechanical Systems | The modern theory of classical mechanics, developed by Lagrange, Hamilton and Noether, attempts to cast all of classical motion in the form of an optimization problem, based on an energy functional called the classical action. The most important advantage of this formalism is the ability to manifestly incorporate and e... | [
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272694277 | 2409.10831 | 2024-09-17 | PDMX: A Large-Scale Public Domain MusicXML Dataset for Symbolic Music Processing | The recent explosion of generative AI-Music systems has raised numerous concerns over data copyright, licensing music from musicians, and the conflict between open-source AI and large prestige companies. Such issues highlight the need for publicly available, copyright-free musical data, in which there is a large shorta... | [
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272694645 | 2409.11274 | 2024-09-17 | Task Arithmetic for Language Expansion in Speech Translation | Recent progress in large language models (LLMs) has gained interest in speech-text multimodal foundation models, achieving strong performance on instruction-tuned speech translation (ST). However, expanding language pairs is costly due to re-training on combined new and previous datasets. To address this, we aim to bui... | [
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272694067 | 2409.11394 | 2024-09-17 | Distributed Perception Aware Safe Leader Follower System via Control Barrier Methods | This paper addresses a distributed leader-follower formation control problem for a group of agents, each using a body-fixed camera with a limited field of view (FOV) for state estimation. The main challenge arises from the need to coordinate the agents' movements with their cameras' FOV to maintain visibility of the le... | [
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272832498 | 2409.15359 | 2024-09-17 | Watch Your Steps: Observable and Modular Chains of Thought | We propose a variant of chain of thought (CoT) prompting called Program Trace Prompting that makes explanations more observable while preserving the power, generality and flexibility of CoT. In our approach, few-shot CoT demonstrations are wrapped in a formal syntax based on Python, and each prompt: identifies and name... | [
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272693934 | 2409.10992 | 2024-09-17 | A Best-of-Both Approach to Improve Match Predictions and Reciprocal Recommendations for Job Search | Matching users with mutual preferences is a critical aspect of services driven by reciprocal recommendations, such as job search. To produce recommendations in such scenarios, one can predict match probabilities and construct rankings based on these predictions. However, this direct match prediction approach often unde... | [
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272986625 | 2409.18987 | 2024-09-17 | Efficient and Personalized Mobile Health Event Prediction via Small Language Models | Healthcare monitoring is crucial for early detection, timely intervention, and the ongoing management of health conditions, ultimately improving individuals' quality of life. Recent research shows that Large Language Models (LLMs) have demonstrated impressive performance in supporting healthcare tasks. However, existin... | [
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272693936 | 2409.11011 | 2024-09-17 | Enhanced segmentation of femoral bone metastasis in CT scans of patients using synthetic data generation with 3D diffusion models | Purpose: Bone metastasis have a major impact on the quality of life of patients and they are diverse in terms of size and location, making their segmentation complex. Manual segmentation is time-consuming, and expert segmentations are subject to operator variability, which makes obtaining accurate and reproducible segm... | [
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272694311 | 2409.11068 | 2024-09-17 | A Reinforcement Learning Environment for Automatic Code Optimization in the MLIR Compiler | Code optimization is a crucial task aimed at enhancing code performance. However, this process is often tedious and complex, highlighting the necessity for automatic code optimization techniques. Reinforcement Learning (RL), a machine learning technique, has emerged as a promising approach for tackling such complex opt... | [
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272708995 | 2409.11513 | 2024-09-17 | Mamba Fusion: Learning Actions Through Questioning | Video Language Models (VLMs) are crucial for generalizing across diverse tasks and using language cues to enhance learning. While transformer-based architectures have been the de facto in vision-language training, they face challenges like quadratic computational complexity, high GPU memory usage, and difficulty with l... | [
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272694246 | 2409.11227 | 2024-09-17 | Generalized Few-Shot Semantic Segmentation in Remote Sensing: Challenge and Benchmark | Learning with limited labelled data is a challenging problem in various applications, including remote sensing. Few-shot semantic segmentation is one approach that can encourage deep learning models to learn from few labelled examples for novel classes not seen during the training. The generalized few-shot segmentation... | [
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273162745 | 2410.02783 | 2024-09-17 | Enhancing Mental Health Support through Human-AI Collaboration: Toward Secure and Empathetic AI-enabled chatbots | Access to mental health support remains limited, particularly in marginalized communities where structural and cultural barriers hinder timely care. This paper explores the potential of AI-enabled chatbots as a scalable solution, focusing on advanced large language models (LLMs)-GPT v4, Mistral Large, and LLama V3.1-an... | [
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272986903 | 2409.19962 | 2024-09-17 | Two-Stage Optimization for Efficient V2G Coordination in Distribution Power System | With the growing popularity of electric vehicles (EVs), maintaining power grid stability has become a significant challenge. To address this issue, EV scheduling control strategies have been developed to manage vehicle-to-grid (V2G) in coordination with the optimal power flow. In existing studies, such coordination opt... | [
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272708769 | 2409.11761 | 2024-09-18 | Consistent Estimation of a Class of Distances Between Covariance Matrices | This work considers the problem of estimating the distance between two covariance matrices directly from the data. Particularly, we are interested in the family of distances that can be expressed as sums of traces of functions that are separately applied to each covariance matrix. This family of distances is particular... | [
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272753249 | 2409.12263 | 2024-09-18 | Detecting LGBTQ+ Instances of Cyberbullying | Social media continues to have an impact on the trajectory of humanity. However, its introduction has also weaponized keyboards, allowing the abusive language normally reserved for in-person bullying to jump onto the screen, i.e., cyberbullying. Cyberbullying poses a significant threat to adolescents globally, affectin... | [
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272831775 | 2409.15361 | 2024-09-18 | Multitask Mayhem: Unveiling and Mitigating Safety Gaps in LLMs Fine-tuning | Recent breakthroughs in Large Language Models (LLMs) have led to their adoption across a wide range of tasks, ranging from code generation to machine translation and sentiment analysis, etc. Red teaming/Safety alignment efforts show that fine-tuning models on benign (non-harmful) data could compromise safety. However, ... | [
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