Split (1)

train · 203k rows

node_id int64 0 76.9k	label int64 0 39	text stringlengths 13 124k	neighbors listlengths 0 3.32k	mask stringclasses 4 values
43,878	30	Title: A Dataset of Kurdish (Sorani) Named Entities - An Amendment to Kurdish-BLARK Named Entities Abstract: Named Entity Recognition (NER) is one of the essential applications of Natural Language Processing (NLP). It is also an instrument that plays a signiﬁcant role in many other NLP applications, such as Machine Tra...	[]	Train
43,879	5	Title: A Deep Reinforcement Learning based Algorithm for Time and Cost Optimized Scaling of Serverless Applications Abstract: Serverless computing has gained a strong traction in the cloud computing community in recent years. Among the many benefits of this novel computing model, the rapid auto-scaling capability of us...	[]	Validation
43,880	3	Title: A context model for collecting diversity-aware data Abstract: Diversity-aware data are essential for a robust modeling of human behavior in context. In addition, being the human behavior of interest for numerous applications, data must also be reusable across domain, to ensure diversity of interpretations. Curre...	[ 44798 ]	Train
43,881	24	Title: A Comprehensive Survey on Knowledge Distillation of Diffusion Models Abstract: Diffusion Models (DMs), also referred to as score-based diffusion models, utilize neural networks to specify score functions. Unlike most other probabilistic models, DMs directly model the score functions, which makes them more flexib...	[ 21152, 37697, 1603, 18022, 12841, 11982, 43697, 37299, 8308, 6133, 40858, 16095 ]	Train
43,882	26	Title: Community Detection Using Revised Medoid-Shift Based on KNN Abstract: nan	[]	Validation
43,883	6	Title: FeedbackLogs: Recording and Incorporating Stakeholder Feedback into Machine Learning Pipelines Abstract: Even though machine learning (ML) pipelines affect an increasing array of stakeholders, there is little work on how input from stakeholders is recorded and incorporated. We propose FeedbackLogs, addenda to ex...	[ 33933 ]	Train
43,884	7	Title: X-Mesh: A new approach for the simulation of two-phase flow with sharp interface Abstract: Accurate modeling of moving boundaries and interfaces is a difficulty present in many situations of computational mechanics. We use a new approach, X-Mesh, to simulate with the finite element method the interaction between...	[]	Train
43,885	16	Title: DIAMANT: Dual Image-Attention Map Encoders For Medical Image Segmentation Abstract: Although purely transformer-based architectures showed promising performance in many computer vision tasks, many hybrid models consisting of CNN and transformer blocks are introduced to fit more specialized tasks. Nevertheless, d...	[]	Train
43,886	16	Title: L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning Abstract: The ubiquity of camera-enabled devices has led to large amounts of unlabeled image data being produced at the edge. The integration of self-supervised learning (SSL) and federated learning...	[]	Validation
43,887	4	Title: Towards Automated Security Analysis of Smart Contracts based on Execution Property Graph Abstract: Identifying and mitigating vulnerabilities in smart contracts is crucial, especially considering the rapid growth and increasing complexity of Decentralized Finance (DeFi) platforms. To address the challenges assoc...	[ 25978 ]	Train
43,888	24	Title: Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models Abstract: Generalized Additive Models (GAMs) have recently experienced a resurgence in popularity due to their interpretability, which arises from expressing the target value as a sum of non-linear transformations of t...	[]	Train
43,889	24	Title: Data-Centric Learning from Unlabeled Graphs with Diffusion Model Abstract: Graph property prediction tasks are important and numerous. While each task offers a small size of labeled examples, unlabeled graphs have been collected from various sources and at a large scale. A conventional approach is training a mod...	[ 44040, 33533 ]	Train
43,890	27	Title: D-VAT: End-to-End Visual Active Tracking for Micro Aerial Vehicles Abstract: Visual active tracking is a growing research topic in robotics due to its key role in applications such as human assistance, disaster recovery, and surveillance. In contrast to passive tracking, active tracking approaches combine vision...	[]	Test
43,891	24	Title: Minibatching Offers Improved Generalization Performance for Second Order Optimizers Abstract: Training deep neural networks (DNNs) used in modern machine learning is computationally expensive. Machine learning scientists, therefore, rely on stochastic first-order methods for training, coupled with significant ha...	[]	Train
43,892	34	Title: Finding and Counting Patterns in Sparse Graphs Abstract: We consider algorithms for finding and counting small, fixed graphs in sparse host graphs. In the non-sparse setting, the parameters treedepth and treewidth play a crucial role in fast, constant-space and polynomial-space algorithms respectively. We discov...	[ 33714 ]	Validation
43,893	22	Title: A Calculus for Scoped Effects & Handlers Abstract: Algebraic effects&handlers have become a standard approach for side-effects in functional programming. Their modular composition with other effects and clean separation of syntax and semantics make them attractive to a wide audience. However, not all effects can...	[]	Validation
43,894	27	Title: Reducing Redundant Work in Jump Point Search Abstract: JPS (Jump Point Search) is a state-of-the-art optimal algorithm for online grid-based pathfinding. Widely used in games and other navigation scenarios, JPS nevertheless can exhibit pathological behaviours which are not well studied: (i) it may repeatedly sc...	[]	Test
43,895	24	Title: Causal Structural Learning from Time Series: A Convex Optimization Approach Abstract: Structural learning, which aims to learn directed acyclic graphs (DAGs) from observational data, is foundational to causal reasoning and scientific discovery. Recent advancements formulate structural learning into a continuous ...	[]	Train
43,896	16	Title: Deep Nonparametric Convexified Filtering for Computational Photography, Image Synthesis and Adversarial Defense Abstract: We aim to provide a general framework of for computational photography that recovers the real scene from imperfect images, via the Deep Nonparametric Convexified Filtering (DNCF). It is consi...	[]	Train
43,897	16	Title: A Review of Deep Learning for Video Captioning Abstract: Video captioning (VC) is a fast-moving, cross-disciplinary area of research that bridges work in the fields of computer vision, natural language processing (NLP), linguistics, and human-computer interaction. In essence, VC involves understanding a video an...	[]	Train
43,898	24	Title: Reinforcement Learning for Battery Management in Dairy Farming Abstract: Dairy farming is a particularly energy-intensive part of the agriculture sector. Effective battery management is essential for renewable integration within the agriculture sector. However, controlling battery charging/discharging is a diffi...	[]	Test
43,899	7	Title: Bridging scales with Machine Learning: From first principles statistical mechanics to continuum phase field computations to study order disorder transitions in LixCoO2 Abstract: LixTMO2 (TM=Ni, Co, Mn) forms an important family of cathode materials for Li-ion batteries, whose performance is strongly governed by ...	[]	Train
43,900	16	Title: Ladder: A software to label images, detect objects and deploy models recurrently for object detection Abstract: Object Detection (OD) is a computer vision technology that can locate and classify objects in images and videos, which has the potential to significantly improve efficiency in precision agriculture. To...	[]	Train
43,901	24	Title: Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning Abstract: Real-world graphs naturally exhibit hierarchical or cyclical structures that are unfit for the typical Euclidean space. While there exist graph neural networks that leverage hyperbolic or spherical spaces to learn repr...	[ 17719 ]	Train
43,902	27	Title: Enhancing AUV Autonomy With Model Predictive Path Integral Control Abstract: Autonomous underwater vehicles (AUVs) play a crucial role in surveying marine environments, carrying out underwater inspection tasks, and ocean exploration. However, in order to ensure that the AUV is able to carry out its mission succe...	[]	Train
43,903	28	Title: Complex CNN CSI Enhancer for Integrated Sensing and Communications Abstract: In this paper, we propose a novel complex convolutional neural network (CNN) CSI enhancer for integrated sensing and communications (ISAC), which exploits the correlation between the sensing parameters (such as angle-of-arrival and rang...	[ 39135 ]	Test
43,904	13	Title: The Deep Arbitrary Polynomial Chaos Neural Network or how Deep Artificial Neural Networks could benefit from Data-Driven Homogeneous Chaos Theory Abstract: nan	[]	Test
43,905	30	Title: DEplain: A German Parallel Corpus with Intralingual Translations into Plain Language for Sentence and Document Simplification Abstract: Text simplification is an intralingual translation task in which documents, or sentences of a complex source text are simplified for a target audience. The success of automatic ...	[]	Validation
43,906	30	Title: What In-Context Learning "Learns" In-Context: Disentangling Task Recognition and Task Learning Abstract: Large language models (LLMs) exploit in-context learning (ICL) to solve tasks with only a few demonstrations, but its mechanisms are not yet well-understood. Some works suggest that LLMs only recall already l...	[ 31264, 12485, 1321, 29612, 32206, 37179, 3795, 31923, 1333, 1654, 33363, 31355, 43327 ]	Train
43,907	34	Title: Improved Diversity Maximization Algorithms for Matching and Pseudoforest Abstract: In this work we consider the diversity maximization problem, where given a data set $X$ of $n$ elements, and a parameter $k$, the goal is to pick a subset of $X$ of size $k$ maximizing a certain diversity measure. [CH01] defined a...	[]	Train
43,908	24	Title: Towards Practical Federated Causal Structure Learning Abstract: Understanding causal relations is vital in scientific discovery. The process of causal structure learning involves identifying causal graphs from observational data to understand such relations. Usually, a central server performs this task, but shar...	[ 8059 ]	Test
43,909	23	Title: Approaching Unanticipated Consequences Abstract: In an ever-changing world, even software that fulfils its requirements may have un-envisioned aftereffects with significant impacts. We explored how such impacts can be better understood at the pre-design phase in support of organisational preparedness. We conside...	[]	Train
43,910	16	Title: NeRF-Loc: Visual Localization with Conditional Neural Radiance Field Abstract: We propose a novel visual re-localization method based on direct matching between the implicit 3D descriptors and the 2D image with transformer. A conditional neural radiance field(NeRF) is chosen as the 3D scene representation in our...	[ 7076 ]	Train
43,911	16	Title: ConceptLab: Creative Generation using Diffusion Prior Constraints Abstract: Recent text-to-image generative models have enabled us to transform our words into vibrant, captivating imagery. The surge of personalization techniques that has followed has also allowed us to imagine unique concepts in new scenes. Howe...	[ 10624, 42272, 10788, 42149, 16103, 33261, 305, 26809, 43867, 18205 ]	Validation
43,912	30	Title: OverPrompt: Enhancing ChatGPT Capabilities through an Efficient In-Context Learning Approach Abstract: The exceptional performance of pre-trained large language models has revolutionised various applications, but their adoption in production environments is hindered by prohibitive costs and inefficiencies, parti...	[ 39642, 16556, 33220, 13700 ]	Validation
43,913	24	Title: Understanding Reinforcement Learning Algorithms: The Progress from Basic Q-learning to Proximal Policy Optimization Abstract: This paper presents a review of the field of reinforcement learning (RL), with a focus on providing a comprehensive overview of the key concepts, techniques, and algorithms for beginners....	[]	Train
43,914	25	Title: TunesFormer: Forming Irish Tunes with Control Codes by Bar Patching Abstract: This paper introduces TunesFormer, an efficient Transformer-based dual-decoder model specifically designed for the generation of melodies that adhere to user-defined musical forms. Trained on 214,122 Irish tunes, TunesFormer utilizes t...	[ 8566, 45695 ]	Test
43,915	24	Title: Learning noisy-OR Bayesian Networks with Max-Product Belief Propagation Abstract: Noisy-OR Bayesian Networks (BNs) are a family of probabilistic graphical models which express rich statistical dependencies in binary data. Variational inference (VI) has been the main method proposed to learn noisy-OR BNs with com...	[]	Train
43,916	25	Title: Fake the Real: Backdoor Attack on Deep Speech Classification via Voice Conversion Abstract: Deep speech classification has achieved tremendous success and greatly promoted the emergence of many real-world applications. However, backdoor attacks present a new security threat to it, particularly with untrustworthy...	[ 39853 ]	Train
43,917	27	Title: PRIMP: PRobabilistically-Informed Motion Primitives for Efficient Affordance Learning from Demonstration Abstract: This paper proposes a learning-from-demonstration method using probability densities on the workspaces of robot manipulators. The method, named"PRobabilistically-Informed Motion Primitives (PRIMP)",...	[]	Train
43,918	16	Title: Self-Supervised Instance Segmentation by Grasping Abstract: Instance segmentation is a fundamental skill for many robotic applications. We propose a self-supervised method that uses grasp interactions to collect segmentation supervision for an instance segmentation model. When a robot grasps an item, the mask of...	[ 8214 ]	Train
43,919	10	Title: A Theory of Intelligences: Concepts, Models, Implications Abstract: Intelligence is a human construct to represent the ability to achieve goals. Given this wide berth, intelligence has been defined countless times, studied in a variety of ways and quantified using numerous measures. Understanding intelligence ul...	[ 13510 ]	Train
43,920	16	Title: 3D Video Loops from Asynchronous Input Abstract: Looping videos are short video clips that can be looped endlessly without visible seams or artifacts. They provide a very attractive way to capture the dynamism of natural scenes. Existing methods have been mostly limited to 2D representations. In this paper, we t...	[]	Train
43,921	5	Title: Speeding up charge exchange recombination spectroscopy analysis in support of NERSC/DIII-D realtime workflow Abstract: We report optimization work made in support of the development of a realtime Superfacility workflow between DIII-D and NERSC. At DIII-D, the ion properties measured by charge exchange recombinat...	[]	Test
43,922	24	Title: On the Role of Emergent Communication for Social Learning in Multi-Agent Reinforcement Learning Abstract: Explicit communication among humans is key to coordinating and learning. Social learning, which uses cues from experts, can greatly benefit from the usage of explicit communication to align heterogeneous pol...	[]	Test
43,923	14	Title: Exact computations with quasiseparable matrices Abstract: Quasiseparable matrices are a class of rank-structured matrices widely used in numerical linear algebra and of growing interest in computer algebra, with applications in e.g. the linearization of polynomial matrices. Various representation formats exist f...	[]	Test
43,924	24	Title: Transfer Causal Learning: Causal Effect Estimation with Knowledge Transfer Abstract: A novel problem of improving causal effect estimation accuracy with the help of knowledge transfer under the same covariate (or feature) space setting, i.e., homogeneous transfer learning (TL), is studied, referred to as the Tra...	[]	Train
43,925	30	Title: On the Tool Manipulation Capability of Open-source Large Language Models Abstract: Recent studies on software tool manipulation with large language models (LLMs) mostly rely on closed model APIs. The industrial adoption of these models is substantially constrained due to the security and robustness risks in expo...	[ 7936, 27138, 13700, 37252, 10510, 14869, 3609, 9499, 19747, 295, 6958, 17328, 25522, 21180, 29375, 32450, 33220, 32213, 43376, 41336, 1401, 634, 45182, 3967 ]	Train
43,926	6	Title: An XRI Mixed-Reality Internet-of-Things Architectural Framework Toward Immersive and Adaptive Smart Environments Abstract: The internet-of-things (IoT) refers to the growing number of embedded interconnected devices within everyday ubiquitous objects and environments, especially their networks, edge controllers,...	[ 29320, 24426, 5277, 10951 ]	Train
43,927	18	Title: MemSPICE: Automated Simulation and Energy Estimation Framework for MAGIC-Based Logic-in-Memory Abstract: Existing logic-in-memory (LiM) research is limited to generating mappings and micro-operations. In this paper, we present~\emph{MemSPICE}, a novel framework that addresses this gap by automatically generating...	[ 31516 ]	Train
43,928	30	Title: Discourse Centric Evaluation of Machine Translation with a Densely Annotated Parallel Corpus Abstract: Several recent papers claim human parity at sentence-level Machine Translation (MT), especially in high-resource languages. Thus, in response, the MT community has, in part, shifted its focus to document-level ...	[]	Train
43,929	24	Title: RDumb: A simple approach that questions our progress in continual test-time adaptation Abstract: Test-Time Adaptation (TTA) allows to update pretrained models to changing data distributions at deployment time. While early work tested these algorithms for individual fixed distribution shifts, recent work proposed...	[]	Test
43,930	30	Title: How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection Abstract: The introduction of ChatGPT has garnered widespread attention in both academic and industrial communities. ChatGPT is able to respond effectively to a wide range of human questions, providing fluent and comprehensive an...	[ 19968, 514, 27140, 37395, 41499, 8227, 9252, 37411, 43044, 37420, 38958, 30770, 31291, 7239, 14410, 5707, 35415, 12888, 33368, 7773, 27238, 2666, 45680, 31857, 22130, 7796, 32372, 24706, 17542, 44173, 38543, 10900, 16539, 3250, 6836, 5301, 3141...	Train
43,931	16	Title: Internal Structure Attention Network for Fingerprint Presentation Attack Detection from Optical Coherence Tomography Abstract: As a non-invasive optical imaging technique, optical coherence tomography (OCT) has proven promising for automatic fingerprint recognition system (AFRS) applications. Diverse approaches ...	[]	Train
43,932	30	Title: The First Parallel Corpora for Kurdish Sign Language Abstract: Kurdish Sign Language (KuSL) is the natural language of the Kurdish Deaf people. We work on automatic translation between spoken Kurdish and KuSL. Sign languages evolve rapidly and follow grammatical rules that differ from spoken languages. Consequen...	[]	Train
43,933	31	Title: Streaming CTR Prediction: Rethinking Recommendation Task for Real-World Streaming Data Abstract: The Click-Through Rate (CTR) prediction task is critical in industrial recommender systems, where models are usually deployed on dynamic streaming data in practical applications. Such streaming data in real-world rec...	[ 43608, 45354, 7175, 5591 ]	Train
43,934	27	Title: Stochastic Approach for Modeling a Soft Robotic Finger with Creep Behavior Abstract: Soft robots have high adaptability and safeness which are derived from their softness, and therefore it is paid attention to use them in human society. However, the controllability of soft robots is not enough to perform dextero...	[]	Train
43,935	27	Title: A novel model for layer jamming-based continuum robots Abstract: Continuum robots with variable stiffness have gained wide popularity in the last decade. Layer jamming (LJ) has emerged as a simple and efficient technique to achieve tunable stiffness for continuum robots. Despite its merits, the development of a ...	[ 19721 ]	Train
43,936	4	Title: Effective Feature Extraction for Intrusion Detection System using Non-negative Matrix Factorization and Univariate analysis Abstract: An Intrusion detection system (IDS) is essential for avoiding malicious activity. Mostly, IDS will be improved by machine learning approaches, but the model efficiency is degradin...	[]	Train
43,937	30	Title: Detecting Misinformation with LLM-Predicted Credibility Signals and Weak Supervision Abstract: Credibility signals represent a wide range of heuristics that are typically used by journalists and fact-checkers to assess the veracity of online content. Automating the task of credibility signal extraction, however,...	[ 36179, 13700 ]	Train
43,938	16	Title: Generative Adversarial Networks for Spatio-Spectral Compression of Hyperspectral Images Abstract: Deep learning-based image compression methods have led to high rate-distortion performances compared to traditional codecs. Recently, Generative Adversarial Networks (GANs)-based compression models, e.g., High Fidel...	[]	Validation
43,939	24	Title: Deep neural networks from the perspective of ergodic theory Abstract: The design of deep neural networks remains somewhat of an art rather than precise science. By tentatively adopting ergodic theory considerations on top of viewing the network as the time evolution of a dynamical system, with each layer corresp...	[]	Validation
43,940	24	Title: A Comprehensive Review and a Taxonomy of Edge Machine Learning: Requirements, Paradigms, and Techniques Abstract: The union of Edge Computing (EC) and Artificial Intelligence (AI) has brought forward the Edge AI concept to provide intelligent solutions close to the end-user environment, for privacy preservation,...	[ 12851 ]	Train
43,941	3	Title: Tapping into Privacy: A Study of User Preferences and Concerns on Trigger-Action Platforms Abstract: The Internet of Things (IoT) devices are rapidly increasing in popularity, with more individuals using Internet-connected devices that continuously monitor their activities. This work explores privacy concerns an...	[]	Validation
43,942	16	Title: CLVOS23: A Long Video Object Segmentation Dataset for Continual Learning Abstract: Continual learning in real-world scenarios is a major challenge. A general continual learning model should have a constant memory size and no predefined task boundaries, as is the case in semi-supervised Video Object Segmentation ...	[]	Validation
43,943	37	Title: A Framework for Combining Entity Resolution and Query Answering in Knowledge Bases Abstract: We propose a new framework for combining entity resolution and query answering in knowledge bases (KBs) with tuple-generating dependencies (tgds) and equality-generating dependencies (egds) as rules. We define the semant...	[ 9355 ]	Validation
43,944	2	Title: Short Boolean Formulas as Explanations in Practice Abstract: We investigate explainability via short Boolean formulas in the data model based on unary relations. As an explanation of length k, we take a Boolean formula of length k that minimizes the error with respect to the target attribute to be explained. We ...	[]	Validation
43,945	16	Title: Content-based Unrestricted Adversarial Attack Abstract: Unrestricted adversarial attacks typically manipulate the semantic content of an image (e.g., color or texture) to create adversarial examples that are both effective and photorealistic, demonstrating their ability to deceive human perception and deep neura...	[ 10624, 22886, 5619, 42771, 2453, 17878, 13272 ]	Test
43,946	31	Title: Attacking Pre-trained Recommendation Abstract: Recently, a series of pioneer studies have shown the potency of pre-trained models in sequential recommendation, illuminating the path of building an omniscient unified pre-trained recommendation model for different downstream recommendation tasks. Despite these adv...	[ 18949 ]	Test
43,947	16	Title: Masked Images Are Counterfactual Samples for Robust Fine-Tuning Abstract: Deep learning models are challenged by the distribution shift between the training data and test data. Recently, the large models pre-trained on diverse data have demonstrated unprecedented robustness to various distribution shifts. Howeve...	[ 32441, 25941 ]	Train
43,948	16	Title: A Data-Centric Solution to NonHomogeneous Dehazing via Vision Transformer Abstract: Recent years have witnessed an increased interest in image dehazing. Many deep learning methods have been proposed to tackle this challenge, and have made significant accomplishments dealing with homogeneous haze. However, these ...	[ 12563 ]	Train
43,949	6	Title: Relatedly: Scaffolding Literature Reviews with Existing Related Work Sections Abstract: Scholars who want to research a scientific topic must take time to read, extract meaning, and identify connections across many papers. As scientific literature grows, this becomes increasingly challenging. Meanwhile, authors ...	[ 14635, 43410, 8491, 45804 ]	Validation
43,950	34	Title: Structural Equivalence in Subgraph Matching Abstract: Symmetry plays a major role in subgraph matching both in the description of the graphs in question and in how it confounds the search process. This work addresses how to quantify these effects and how to use symmetries to increase the efficiency of subgraph i...	[]	Validation
43,951	24	Title: A Systematic Literature Review on Client Selection in Federated Learning Abstract: With the arising concerns of privacy within machine learning, federated learning (FL) was invented in 2017, in which the clients, such as mobile devices, train a model and send the update to the centralized server. Choosing client...	[]	Train
43,952	36	Title: Learning to Bid in Repeated First-Price Auctions with Budgets Abstract: Budget management strategies in repeated auctions have received growing attention in online advertising markets. However, previous work on budget management in online bidding mainly focused on second-price auctions. The rapid shift from seco...	[ 15281 ]	Train
43,953	16	Title: READ Avatars: Realistic Emotion-controllable Audio Driven Avatars Abstract: We present READ Avatars, a 3D-based approach for generating 2D avatars that are driven by audio input with direct and granular control over the emotion. Previous methods are unable to achieve realistic animation due to the many-to-many n...	[]	Train
43,954	7	Title: Error Approximation and Bias Correction in Dynamic Problems using a Recurrent Neural Network/Finite Element Hybrid Model Abstract: This work proposes a hybrid modeling framework based on recurrent neural networks (RNNs) and the finite element (FE) method to approximate model discrepancies in time dependent, mult...	[]	Train
43,955	24	Title: Where to Diffuse, How to Diffuse, and How to Get Back: Automated Learning for Multivariate Diffusions Abstract: Diffusion-based generative models (DBGMs) perturb data to a target noise distribution and reverse this process to generate samples. The choice of noising process, or inference diffusion process, affect...	[ 43496, 29082 ]	Train
43,956	30	Title: SLCNN: Sentence-Level Convolutional Neural Network for Text Classification Abstract: Text classification is a fundamental task in natural language processing (NLP). Several recent studies show the success of deep learning on text processing. Convolutional neural network (CNN), as a popular deep learning model, h...	[]	Test
43,957	20	Title: Improved Approximations for Translational Packing of Convex Polygons Abstract: Optimal packing of objects in containers is a critical problem in various real-life and industrial applications. This paper investigates the two-dimensional packing of convex polygons without rotations, where only translations are all...	[]	Validation
43,958	4	Title: Secure and Trustworthy Computing 2.0 Vision Statement Abstract: The Secure and Trustworthy Computing (SaTC) program within the National Science Foundation (NSF) program serves as the primary instrument for creating novel fundamental science in security and privacy in the United States with broad impacts that inf...	[]	Train
43,959	4	Title: Blockchain Censorship Abstract: Permissionless blockchains promise to be resilient against censorship by a single entity. This suggests that deterministic rules, and not third-party actors, are responsible for deciding if a transaction is appended to the blockchain or not. In 2022, the U.S. Office of Foreign Ass...	[ 44541, 22655 ]	Validation
43,960	24	Title: The Impossibility of Parallelizing Boosting Abstract: The aim of boosting is to convert a sequence of weak learners into a strong learner. At their heart, these methods are fully sequential. In this paper, we investigate the possibility of parallelizing boosting. Our main contribution is a strong negative result...	[]	Train
43,961	24	Title: Deep Learning and Computational Physics (Lecture Notes) Abstract: These notes were compiled as lecture notes for a course developed and taught at the University of the Southern California. They should be accessible to a typical engineering graduate student with a strong background in Applied Mathematics. The mai...	[ 13424, 1306 ]	Train
43,962	8	Title: Enabling Technologies for Programmable and Software-Defined Networks: Bolstering the Path Towards 6G Abstract: Although the complete scope of the sixth generation of mobile technologies (6G) is still unclear, the prominence of the Internet of Things (IoT) and Artificial Intelligence (AI) / Machine Learning (ML) ...	[]	Validation
43,963	26	Title: Weighted flow diffusion for local graph clustering with node attributes: an algorithm and statistical guarantees Abstract: Local graph clustering methods aim to detect small clusters in very large graphs without the need to process the whole graph. They are fundamental and scalable tools for a wide range of task...	[ 22612 ]	Train
43,964	28	Title: Modular CSI Quantization for FDD Massive MIMO Communication Abstract: We consider high-dimensional MIMO transmissions in frequency division duplexing (FDD) systems. For precoding, the frequency selective channel has to be measured, quantized and fed back to the base station by the users. When the number of anten...	[]	Train
43,965	24	Title: Goal-Conditioned Imitation Learning using Score-based Diffusion Policies Abstract: We propose a new policy representation based on score-based diffusion models (SDMs). We apply our new policy representation in the domain of Goal-Conditioned Imitation Learning (GCIL) to learn general-purpose goal-specified polici...	[ 8994, 1603, 43139, 34215, 16298, 24651, 13261, 16273, 14036, 17529 ]	Train
43,966	15	Title: An Optical XNOR-Bitcount Based Accelerator for Efficient Inference of Binary Neural Networks Abstract: Binary Neural Networks (BNNs) are increasingly preferred over full-precision Convolutional Neural Networks (CNNs) to reduce the memory and computational requirements of inference processing with minimal accurac...	[ 12027, 9655 ]	Train
43,967	4	Title: Deep Attention Recognition for Attack Identification in 5G UAV scenarios: Novel Architecture and End-to-End Evaluation Abstract: Despite the robust security features inherent in the 5G framework, attackers will still discover ways to disrupt 5G unmanned aerial vehicle (UAV) operations and decrease UAV control co...	[]	Train
43,968	30	Title: Archive TimeLine Summarization (ATLS): Conceptual Framework for Timeline Generation over Historical Document Collections Abstract: Archive collections are nowadays mostly available through search engines interfaces, which allow a user to retrieve documents by issuing queries. The study of these collections may b...	[]	Train
43,969	24	Title: An Interpretable Loan Credit Evaluation Method Based on Rule Representation Learner Abstract: The interpretability of model has become one of the obstacles to its wide application in the high-stake fields. The usual way to obtain interpretability is to build a black-box first and then explain it using the post-h...	[]	Train
43,970	30	Title: TheoremQA: A Theorem-driven Question Answering dataset Abstract: The recent LLMs like GPT-4 and PaLM-2 have made tremendous progress in solving fundamental math problems like GSM8K by achieving over 90% accuracy. However, their capabilities to solve more challenging math problems which require domain-specific kn...	[ 32450, 37987, 15812, 33220, 13510, 13700, 30538, 43980, 19727, 33490, 6963, 29396, 45494, 32859, 29375 ]	Train
43,971	27	Title: CUREE: A Curious Underwater Robot for Ecosystem Exploration Abstract: The current approach to exploring and monitoring complex underwater ecosystems, such as coral reefs, is to conduct surveys using diver-held or static cameras, or deploying sensor buoys. These approaches often fail to capture the full variation...	[ 33073, 35410 ]	Train
43,972	25	Title: Multi-Loss Convolutional Network with Time-Frequency Attention for Speech Enhancement Abstract: The Dual-Path Convolution Recurrent Network (DPCRN) was proposed to effectively exploit time-frequency domain information. By combining the DPRNN module with Convolution Recurrent Network (CRN), the DPCRN obtained a p...	[]	Validation
43,973	24	Title: Link Prediction without Graph Neural Networks Abstract: Link prediction, which consists of predicting edges based on graph features, is a fundamental task in many graph applications. As for several related problems, Graph Neural Networks (GNNs), which are based on an attribute-centric message-passing paradigm, h...	[ 28880 ]	Train
43,974	30	Title: Intrinsic Dimension Estimation for Robust Detection of AI-Generated Texts Abstract: Rapidly increasing quality of AI-generated content makes it difficult to distinguish between human and AI-generated texts, which may lead to undesirable consequences for society. Therefore, it becomes increasingly important to st...	[ 22476, 497, 38235, 25367, 33368, 43930, 315, 33598 ]	Train
43,975	27	Title: Social Impressions of the NAO Robot and its Impact on Physiology Abstract: The social applications of robots possess intrinsic challenges with respect to social paradigms and heterogeneity of different groups. These challenges can be in the form of social acceptability, anthropomorphism, likeability, past experi...	[]	Test
43,976	24	Title: Diffusion Policies for Out-of-Distribution Generalization in Offline Reinforcement Learning Abstract: Offline Reinforcement Learning (RL) methods leverage previous experiences to learn better policies than the behavior policy used for data collection. In contrast to behavior cloning, which assumes the data is co...	[ 32314 ]	Test
43,977	16	Title: Discovering Spatio-Temporal Rationales for Video Question Answering Abstract: This paper strives to solve complex video question answering (VideoQA) which features long video containing multiple objects and events at different time. To tackle the challenge, we highlight the importance of identifying question-cri...	[ 30965 ]	Train

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