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272832283 | 2409.15600 | 2024-09-23 | Polyatomic Complexes: A topologically-informed learning representation for atomistic systems | Developing robust representations of chemical structures that enable models to learn topological inductive biases is challenging. In this manuscript, we present a representation of atomistic systems. We begin by proving that our representation satisfies all structural, geometric, efficiency, and generalizability constr... | [
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272832488 | 2409.15565 | 2024-09-23 | Critic Loss for Image Classification | Modern neural network classifiers achieve remarkable performance across a variety of tasks; however, they frequently exhibit overconfidence in their predictions due to the cross-entropy loss. Inspired by this problem, we propose the \textbf{Cr}i\textbf{t}ic Loss for Image \textbf{Cl}assification (CrtCl, pronounced Crit... | [
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272831922 | 2409.15615 | 2024-09-23 | KISS-Matcher: Fast and Robust Point Cloud Registration Revisited | While global point cloud registration systems have advanced significantly in all aspects, many studies have focused on specific components, such as feature extraction, graph-theoretic pruning, or pose solvers. In this paper, we take a holistic view on the registration problem and develop an open-source and versatile C+... | [
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272827116 | 2409.15267 | 2024-09-23 | Peer-to-Peer Learning Dynamics of Wide Neural Networks | Peer-to-peer learning is an increasingly popular framework that enables beyond-5G distributed edge devices to collaboratively train deep neural networks in a privacy-preserving manner without the aid of a central server. Neural network training algorithms for emerging environments, e.g., smart cities, have many design ... | [
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272827545 | 2409.15199 | 2024-09-23 | Learning from Contrastive Prompts: Automated Optimization and Adaptation | As LLMs evolve, significant effort is spent on manually crafting prompts. While existing prompt optimization methods automate this process, they rely solely on learning from incorrect samples, leading to a sub-optimal performance. Additionally, an unexplored challenge in the literature is prompts effective for prior mo... | [
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272832190 | 2409.15520 | 2024-09-23 | MobiZO: Enabling Efficient LLM Fine-Tuning at the Edge via Inference Engines | Large Language Models (LLMs) are currently pre-trained and fine-tuned on large cloud servers. The next frontier is LLM personalization, where a foundation model can be fine-tuned with user/task-specific data. Given the sensitive nature of such private data, it is desirable to fine-tune these models on edge devices to i... | [
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272831947 | 2409.15593 | 2024-09-23 | Lie symmetries, closed-form solutions, and conservation laws of a constitutive equation modeling stress in elastic materials | The Lie-point symmetry method is used to find some closed-form solutions for a constitutive equation modeling stress in elastic materials. The partial differential equation (PDE), which involves a power law with arbitrary exponent n, was investigated by Mason and his collaborators (Magan et al., Wave Motion, 77, 156-18... | [
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272831893 | 2409.15486 | 2024-09-23 | VLMine: Long-Tail Data Mining with Vision Language Models | Ensuring robust performance on long-tail examples is an important problem for many real-world applications of machine learning, such as autonomous driving. This work focuses on the problem of identifying rare examples within a corpus of unlabeled data. We propose a simple and scalable data mining approach that leverage... | [
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272827858 | 2409.14794 | 2024-09-23 | Advancing Depression Detection on Social Media Platforms Through Fine-Tuned Large Language Models | This study investigates the use of Large Language Models (LLMs) for improved depression detection from users social media data. Through the use of fine-tuned GPT 3.5 Turbo 1106 and LLaMA2-7B models and a sizable dataset from earlier studies, we were able to identify depressed content in social media posts with a high a... | [
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272826918 | 2409.14737 | 2024-09-23 | Generalizable Autonomous Driving System across Diverse Adverse Weather Conditions | Various adverse weather conditions pose a significant challenge to autonomous driving (AD) street scene semantic understanding (segmentation). A common strategy is to minimize the disparity between images captured in clear and adverse weather conditions. However, this technique typically relies on utilizing clear image... | [
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272826811 | 2409.15097 | 2024-09-23 | Efficiently Dispatching Flash Attention For Partially Filled Attention Masks | Transformers are widely used across various applications, many of which yield sparse or partially filled attention matrices. Examples include attention masks designed to reduce the quadratic complexity of attention, sequence packing techniques, and recent innovations like tree masking for fast validation in MEDUSA. Des... | [
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272827889 | 2409.14702 | 2024-09-23 | Rate-Splitting for Cell-Free Massive MIMO: Performance Analysis and Generative AI Approach | Cell-free (CF) massive multiple-input multipleoutput (MIMO) provides a ubiquitous coverage to user equipments (UEs) but it is also susceptible to interference. Ratesplitting (RS) effectively extracts data by decoding interference, yet its effectiveness is limited by the weakest UE. In this paper, we investigate an RS-b... | [
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272827943 | 2409.14666 | 2024-09-23 | Semi-supervised Learning For Robust Speech Evaluation | Speech evaluation measures a learners oral proficiency using automatic models. Corpora for training such models often pose sparsity challenges given that there often is limited scored data from teachers, in addition to the score distribution across proficiency levels being often imbalanced among student cohorts. Automa... | [
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272827326 | 2409.14704 | 2024-09-23 | VLEU: a Method for Automatic Evaluation for Generalizability of Text-to-Image Models | Progress in Text-to-Image (T2I) models has significantly improved the generation of images from textual descriptions. However, existing evaluation metrics do not adequately assess the models' ability to handle a diverse range of textual prompts, which is crucial for their generalizability. To address this, we introduce... | [
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272832438 | 2409.15517 | 2024-09-23 | MATCH POLICY: A Simple Pipeline from Point Cloud Registration to Manipulation Policies | Many manipulation tasks require the robot to rearrange objects relative to one another. Such tasks can be described as a sequence of relative poses between parts of a set of rigid bodies. In this work, we propose MATCH POLICY, a simple but novel pipeline for solving high-precision pick and place tasks. Instead of predi... | [
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272826840 | 2409.15012 | 2024-09-23 | Inference-Friendly Models With MixAttention | The size of the key-value (KV) cache plays a critical role in determining both the maximum context length and the number of concurrent requests supported during inference in modern language models. The KV cache size grows proportionally with the number of attention heads and the tokens processed, leading to increased m... | [
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272826872 | 2409.15179 | 2024-09-23 | MIMAFace: Face Animation via Motion-Identity Modulated Appearance Feature Learning | Current diffusion-based face animation methods generally adopt a ReferenceNet (a copy of U-Net) and a large amount of curated self-acquired data to learn appearance features, as robust appearance features are vital for ensuring temporal stability. However, when trained on public datasets, the results often exhibit a no... | [
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272827490 | 2409.14689 | 2024-09-23 | EDGE-Rec: Efficient and Data-Guided Edge Diffusion For Recommender Systems Graphs | Most recommender systems research focuses on binary historical user-item interaction encodings to predict future interactions. User features, item features, and interaction strengths remain largely under-utilized in this space or only indirectly utilized, despite proving largely effective in large-scale production reco... | [
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272827000 | 2409.15130 | 2024-09-23 | CAMAL: Optimizing LSM-trees via Active Learning | We use machine learning to optimize LSM-tree structure, aiming to reduce the cost of processing various read/write operations. We introduce a new approach Camal, which boasts the following features: (1) ML-Aided: Camal is the first attempt to apply active learning to tune LSM-tree based key-value stores. The learning p... | [
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273233720 | 2410.07191 | 2024-09-23 | Curb Your Attention: Causal Attention Gating for Robust Trajectory Prediction in Autonomous Driving | Trajectory prediction models in autonomous driving are vulnerable to perturbations from non-causal agents whose actions should not affect the ego-agent's behavior. Such perturbations can lead to incorrect predictions of other agents' trajectories, potentially compromising the safety and efficiency of the ego-vehicle's ... | [
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272832272 | 2409.15395 | 2024-09-23 | Parse Trees Guided LLM Prompt Compression | Offering rich contexts to Large Language Models (LLMs) has shown to boost the performance in various tasks, but the resulting longer prompt would increase the computational cost and might exceed the input limit of LLMs. Recently, some prompt compression methods have been suggested to shorten the length of prompts by us... | [
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272827145 | 2409.14747 | 2024-09-23 | Distribution-Level Feature Distancing for Machine Unlearning: Towards a Better Trade-off Between Model Utility and Forgetting | With the explosive growth of deep learning applications and increasing privacy concerns, the right to be forgotten has become a critical requirement in various AI industries. For example, given a facial recognition system, some individuals may wish to remove their personal data that might have been used in the training... | [
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272832389 | 2409.15590 | 2024-09-23 | MapEx: Indoor Structure Exploration with Probabilistic Information Gain from Global Map Predictions | Exploration is a critical challenge in robotics, centered on understanding unknown environments. In this work, we focus on robots exploring structured indoor environments which are often predictable and composed of repeating patterns. Most existing approaches, such as conventional frontier approaches, have difficulty l... | [
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272827851 | 2409.14968 | 2024-09-23 | Mutation-Based Deep Learning Framework Testing Method in JavaScript Environment | In recent years, Deep Learning (DL) applications in JavaScript environment have become increasingly popular. As the infrastructure for DL applications, JavaScript DL frameworks play a crucial role in the development and deployment. It is essential to ensure the quality of JavaScript DL frameworks. However, the bottlene... | [
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272831783 | 2409.15584 | 2024-09-23 | FACET: Fast and Accurate Event-Based Eye Tracking Using Ellipse Modeling for Extended Reality | Eye tracking is a key technology for gaze-based interactions in Extended Reality (XR), but traditional frame-based systems struggle to meet XR's demands for high accuracy, low latency, and power efficiency. Event cameras offer a promising alternative due to their high temporal resolution and low power consumption. In t... | [
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272827061 | 2409.14805 | 2024-09-23 | SDBA: A Stealthy and Long-Lasting Durable Backdoor Attack in Federated Learning | Federated learning is a promising approach for training machine learning models while preserving data privacy. However, its distributed nature makes it vulnerable to backdoor attacks, particularly in NLP tasks, where related research remains limited. This paper introduces SDBA, a novel backdoor attack mechanism designe... | [
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272827086 | 2409.14826 | 2024-09-23 | ToolPlanner: A Tool Augmented LLM for Multi Granularity Instructions with Path Planning and Feedback | Recently, tool-augmented LLMs have gained increasing attention. Given an instruction, tool-augmented LLMs can interact with various external tools in multiple rounds and provide a final answer. However, previous LLMs were trained on overly detailed instructions, which included API names or parameters, while real users ... | [
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272831753 | 2409.15616 | 2024-09-23 | Reinforcement Feature Transformation for Polymer Property Performance Prediction | Polymer property performance prediction aims to forecast specific features or attributes of polymers, which has become an efficient approach to measuring their performance. However, existing machine learning models face challenges in effectively learning polymer representations due to low-quality polymer datasets, whic... | [
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272826754 | 2409.14672 | 2024-09-23 | Speechworthy Instruction-tuned Language Models | Current instruction-tuned language models are exclusively trained with textual preference data and thus are often not aligned with the unique requirements of other modalities, such as speech. To better align language models with the speech domain, we explore (i) prompting strategies grounded in radio-industry best prac... | [
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273098442 | 2410.01836 | 2024-09-23 | Temporal Graph Memory Networks For Knowledge Tracing | Tracing a student's knowledge growth given the past exercise answering is a vital objective in automatic tutoring systems to customize the learning experience. Yet, achieving this objective is a non-trivial task as it involves modeling the knowledge state across multiple knowledge components (KCs) while considering the... | [
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272826973 | 2409.15006 | 2024-09-23 | Generalizing monocular colonoscopy image depth estimation by uncertainty-based global and local fusion network | Objective: Depth estimation is crucial for endoscopic navigation and manipulation, but obtaining ground-truth depth maps in real clinical scenarios, such as the colon, is challenging. This study aims to develop a robust framework that generalizes well to real colonoscopy images, overcoming challenges like non-Lambertia... | [
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272987204 | 2409.19013 | 2024-09-23 | Improving Academic Skills Assessment with NLP and Ensemble Learning | This study addresses the critical challenges of assessing foundational academic skills by leveraging advancements in natural language processing (NLP). Traditional assessment methods often struggle to provide timely and comprehensive feedback on key cognitive and linguistic aspects, such as coherence, syntax, and analy... | [
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272826660 | 2409.14778 | 2024-09-23 | Human Hair Reconstruction with Strand-Aligned 3D Gaussians | We introduce a new hair modeling method that uses a dual representation of classical hair strands and 3D Gaussians to produce accurate and realistic strand-based reconstructions from multi-view data. In contrast to recent approaches that leverage unstructured Gaussians to model human avatars, our method reconstructs th... | [
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272832461 | 2409.15481 | 2024-09-23 | Adapting Segment Anything Model for Unseen Object Instance Segmentation | Unseen Object Instance Segmentation (UOIS) is crucial for autonomous robots operating in unstructured environments. Previous approaches require full supervision on large-scale tabletop datasets for effective pretraining. In this paper, we propose UOIS-SAM, a data-efficient solution for the UOIS task that leverages SAM'... | [
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272832436 | 2409.15402 | 2024-09-23 | Uncovering Coordinated Cross-Platform Information Operations Threatening the Integrity of the 2024 U.S. Presidential Election Online Discussion | Information Operations (IOs) pose a significant threat to the integrity of democratic processes, with the potential to influence election-related online discourse. In anticipation of the 2024 U.S. presidential election, we present a study aimed at uncovering the digital traces of coordinated IOs on $\mathbb{X}$ (former... | [
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272826867 | 2409.14810 | 2024-09-23 | Pre-trained Language Model and Knowledge Distillation for Lightweight Sequential Recommendation | Sequential recommendation models user interests based on historical behaviors to provide personalized recommendation. Previous sequential recommendation algorithms primarily employ neural networks to extract features of user interests, achieving good performance. However, due to the recommendation system datasets spars... | [
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272832546 | 2409.15553 | 2024-09-23 | SOFI: Multi-Scale Deformable Transformer for Camera Calibration with Enhanced Line Queries | Camera calibration consists of estimating camera parameters such as the zenith vanishing point and horizon line. Estimating the camera parameters allows other tasks like 3D rendering, artificial reality effects, and object insertion in an image. Transformer-based models have provided promising results; however, they la... | [
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272827514 | 2409.14978 | 2024-09-23 | TS-HTFA: Advancing Time Series Forecasting via Hierarchical Text-Free Alignment with Large Language Models | Given the significant potential of large language models (LLMs) in sequence modeling, emerging studies have begun applying them to time-series forecasting. Despite notable progress, existing methods still face two critical challenges: 1) their reliance on large amounts of paired text data, limiting the model applicabil... | [
"cs.AI"
] | null | [
"target.author.publication_history"
] | [] | [
{
"author_id": "p wang_51",
"name": "Pengfei Wang",
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},
{
"author_id": "h zheng_4",
"name": "Huanran Zheng",
"publication_history": null,
"h_index": null,
"num_papers": null,
"n... | null |
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