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
28,178	15	Title: SafeBet: Secure, Simple, and Fast Speculative Execution Abstract: Spectre attacks exploit microprocessor speculative execution to read and transmit forbidden data outside the attacker's trust domain and sandbox. Recent hardware schemes allow potentially-unsafe speculative accesses but prevent the secret's transm...	[ 18584 ]	Train
28,179	30	Title: Learn to Compose Syntactic and Semantic Representations Appropriately for Compositional Generalization Abstract: Recent studies have shown that sequence-to-sequence (Seq2Seq) models are limited in solving the compositional generalization (CG) tasks, failing to systematically generalize to unseen compositions of ...	[]	Test
28,180	24	Title: Unmatched uncertainty mitigation through neural network supported model predictive control Abstract: This paper presents a deep learning based model predictive control (MPC) algorithm for systems with unmatched and bounded state-action dependent uncertainties of unknown structure. We utilize a deep neural networ...	[]	Validation
28,181	24	Title: NCART: Neural Classification and Regression Tree for Tabular Data Abstract: Deep learning models have become popular in the analysis of tabular data, as they address the limitations of decision trees and enable valuable applications like semi-supervised learning, online learning, and transfer learning. However, ...	[]	Train
28,182	10	Title: A New Perspective on Evaluation Methods for Explainable Artificial Intelligence (XAI) Abstract: Within the field of Requirements Engineering (RE), the increasing significance of Explainable Artificial Intelligence (XAI) in aligning AI-supported systems with user needs, societal expectations, and regulatory stand...	[]	Train
28,183	36	Title: Best-Response Dynamics in Lottery Contests Abstract: We study the convergence of best-response dynamics in lottery contests. We show that best-response dynamics rapidly converges to the (unique) equilibrium for homogeneous agents but may not converge for non-homogeneous agents, even for just two non-homogeneous ...	[]	Train
28,184	24	Title: Subsampling Suffices for Adaptive Data Analysis Abstract: Ensuring that analyses performed on a dataset are representative of the entire population is one of the central problems in statistics. Most classical techniques assume that the dataset is independent of the analyst’s query and break down in the common se...	[ 16495 ]	Test
28,185	22	Title: Attention, Compilation, and Solver-based Symbolic Analysis are All You Need Abstract: In this paper we present a Java-to-Python (J2P) and Python-to-Java (P2J) back-to-back code translation method, and associated tool called CoTran, based on large language models (LLMs). Our method leverages the attention mechani...	[ 42523 ]	Train
28,186	16	Title: SaliencyCut: Augmenting Plausible Anomalies for Open-set Fine-Grained Anomaly Detection Abstract: Open-set fine-grained anomaly detection is a challenging task that requires learning discriminative fine-grained features to detect anomalies that were even unseen during training. As a cheap yet effective approach,...	[]	Test
28,187	24	Title: Feature selection simultaneously preserving both class and cluster structures Abstract: When a data set has significant differences in its class and cluster structure, selecting features aiming only at the discrimination of classes would lead to poor clustering performance, and similarly, feature selection aimin...	[]	Test
28,188	20	Title: Faster Algorithm for Minimum Ply Covering of Points with Unit Squares Abstract: Biedl et al. introduced the minimum ply cover problem in CG 2021 following the seminal work of Erlebach and van Leeuwen in SODA 2008. They showed that determining the minimum ply cover number for a given set of points by a given set ...	[]	Validation
28,189	16	Title: GP-UNIT: Generative Prior for Versatile Unsupervised Image-to-Image Translation Abstract: Recent advances in deep learning have witnessed many successful unsupervised image-to-image translation models that learn correspondences between two visual domains without paired data. However, it is still a great challeng...	[ 23014 ]	Train
28,190	16	Title: PseudoBound: Limiting the anomaly reconstruction capability of one-class classifiers using pseudo anomalies Abstract: nan	[]	Train
28,191	16	Title: A Critical Analysis of the Limitation of Deep Learning based 3D Dental Mesh Segmentation Methods in Segmenting Partial Scans Abstract: Tooth segmentation from intraoral scans is a crucial part of digital dentistry. Many Deep Learning based tooth segmentation algorithms have been developed for this task. In most ...	[]	Validation
28,192	24	Title: Bayesian Models of Functional Connectomics and Behavior Abstract: The problem of jointly analysing functional connectomics and behavioral data is extremely challenging owing to the complex interactions between the two domains. In addition, clinical rs-fMRI studies often have to contend with limited samples, espe...	[]	Validation
28,193	10	Title: Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming Abstract: Pre-trained large language models (LMs) struggle to perform logical reasoning reliably despite advances in scale and compositionality. In this work, we tackle this challenge through the lens of symbolic programming. W...	[ 10864, 27621, 37647 ]	Validation
28,194	27	Title: Multi-Stage Monte Carlo Tree Search for Non-Monotone Object Rearrangement Planning in Narrow Confined Environments Abstract: Non-monotone object rearrangement planning in confined spaces such as cabinets and shelves is a widely occurring but challenging problem in robotics. Both the robot motion and the availabl...	[]	Train
28,195	24	Title: Unsupervised Meta-Learning via Few-shot Pseudo-supervised Contrastive Learning Abstract: Unsupervised meta-learning aims to learn generalizable knowledge across a distribution of tasks constructed from unlabeled data. Here, the main challenge is how to construct diverse tasks for meta-learning without label info...	[ 5128, 39057, 39703 ]	Test
28,196	6	Title: "Get ready for a party": Exploring smarter smart spaces with help from large language models Abstract: The right response to someone who says"get ready for a party"is deeply influenced by meaning and context. For a smart home assistant (e.g., Google Home), the ideal response might be to survey the available devi...	[ 20193 ]	Validation
28,197	24	Title: XFL: A High Performace, Lightweighted Federated Learning Framework Abstract: This paper introduces XFL, an industrial-grade federated learning project. XFL supports training AI models collaboratively on multiple devices, while utilizes homomorphic encryption, differential privacy, secure multi-party computation ...	[]	Train
28,198	36	Title: Combinatorial Pen Testing (or Consumer Surplus of Deferred-Acceptance Auctions) Abstract: Pen testing is the problem of selecting high-capacity resources when the only way to measure the capacity of a resource expends its capacity. We have a set of $n$ pens with unknown amounts of ink and our goal is to select a...	[]	Test
28,199	16	Title: Time-Conditioned Generative Modeling of Object-Centric Representations for Video Decomposition and Prediction Abstract: When perceiving the world from multiple viewpoints, humans have the ability to reason about the complete objects in a compositional manner even when an object is completely occluded from certai...	[]	Test
28,200	4	Title: Mercury: An Automated Remote Side-channel Attack to Nvidia Deep Learning Accelerator Abstract: DNN accelerators have been widely deployed in many scenarios to speed up the inference process and reduce the energy consumption. One big concern about the usage of the accelerators is the confidentiality of the deploy...	[]	Test
28,201	16	Title: Spatial-Temporal Enhanced Transformer Towards Multi-Frame 3D Object Detection Abstract: The Detection Transformer (DETR) has revolutionized the design of CNN-based object detection systems, showcasing impressive performance. However, its potential in the domain of multi-frame 3D object detection remains largely ...	[]	Train
28,202	8	Title: Mixed-Variable PSO with Fairness on Multi-Objective Field Data Replication in Wireless Networks Abstract: Digital twins have shown a great potential in supporting the development of wireless networks. They are virtual representations of 5G/6G systems enabling the design of machine learning and optimization-based...	[]	Train
28,203	4	Title: Balanced Datasets for IoT IDS Abstract: As the Internet of Things (IoT) continues to grow, cyberattacks are becoming increasingly common. The security of IoT networks relies heavily on intrusion detection systems (IDSs). The development of an IDS that is accurate and efficient is a challenging task. As a result,...	[]	Test
28,204	30	Title: Gotta: Generative Few-shot Question Answering by Prompt-based Cloze Data Augmentation Abstract: Few-shot question answering (QA) aims at precisely discovering answers to a set of questions from context passages while only a few training samples are available. Although existing studies have made some progress and...	[]	Train
28,205	24	Title: An Analytical Study of Covid-19 Dataset using Graph-Based Clustering Algorithms Abstract: nan	[]	Train
28,206	24	Title: Keep It Simple: Fault Tolerance Evaluation of Federated Learning with Unreliable Clients Abstract: Federated learning (FL), as an emerging artificial intelligence (AI) approach, enables decentralized model training across multiple devices without exposing their local training data. FL has been increasingly gaini...	[]	Test
28,207	6	Title: Exploring the Effects of Japanese Font Designs on Impression Formation and Decision-Making in Text-Based Communication Abstract: Text-based communication, such as text chat, is commonly employed in various contexts, both professional and personal. However, it lacks the rich emotional cues present in verbal and v...	[]	Validation
28,208	16	Title: Spatial Self-Distillation for Object Detection with Inaccurate Bounding Boxes Abstract: Object detection via inaccurate bounding boxes supervision has boosted a broad interest due to the expensive high-quality annotation data or the occasional inevitability of low annotation quality (\eg tiny objects). The previ...	[]	Validation
28,209	2	Title: Conditional logic as a short-circuit logic Abstract: Both two-valued and three-valued conditional logic (CL), defined by Guzm\'an and Squier (1990) and based on McCarthy's non-commutative connectives, axiomatise a short-circuit logic (SCL) that defines more identities than MSCL (Memorising SCL), which also has a...	[]	Validation
28,210	16	Title: Scoring Cycling Environments Perceived Safety using Pairwise Image Comparisons Abstract: Today, many cities seek to transition to more sustainable transportation systems. Cycling is critical in this transition for shorter trips, including first-and-last-mile links to transit. Yet, if individuals perceive cycling...	[]	Train
28,211	16	Title: Zero-Knowledge Zero-Shot Learning for Novel Visual Category Discovery Abstract: Generalized Zero-Shot Learning (GZSL) and Open-Set Recognition (OSR) are two mainstream settings that greatly extend conventional visual object recognition. However, the limitations of their problem settings are not negligible. The n...	[]	Train
28,212	24	Title: Concept-based explainability for an EEG transformer model Abstract: Deep learning models are complex due to their size, structure, and inherent randomness in training procedures. Additional complexity arises from the selection of datasets and inductive biases. Addressing these challenges for explainability, Kim ...	[]	Validation
28,213	30	Title: Detect Depression from Social Networks with Sentiment Knowledge Sharing Abstract: Social network plays an important role in propagating people's viewpoints, emotions, thoughts, and fears. Notably, following lockdown periods during the COVID-19 pandemic, the issue of depression has garnered increasing attention, ...	[ 28304, 15611, 16375 ]	Validation
28,214	30	Title: CodeKGC: Code Language Model for Generative Knowledge Graph Construction Abstract: Current generative knowledge graph construction approaches usually fail to capture structural knowledge by simply flattening natural language into serialized texts or a specification language. However, large generative language mo...	[ 3745, 1639, 4051, 11190, 27801 ]	Validation
28,215	13	Title: The Intel neuromorphic DNS challenge Abstract: A critical enabler for progress in neuromorphic computing research is the ability to transparently evaluate different neuromorphic solutions on important tasks and to compare them to state-of-the-art conventional solutions. The Intel Neuromorphic Deep Noise Suppress...	[ 17211, 27221 ]	Train
28,216	16	Title: EFaR 2023: Efficient Face Recognition Competition Abstract: This paper presents the summary of the Efficient Face Recognition Competition (EFaR) held at the 2023 International Joint Conference on Biometrics (IJCB 2023). The competition received 17 submissions from 6 different teams. To drive further development ...	[ 29128, 5916, 41429 ]	Train
28,217	30	Title: Decision-Oriented Dialogue for Human-AI Collaboration Abstract: We describe a class of tasks called decision-oriented dialogues, in which AI assistants must collaborate with one or more humans via natural language to help them make complex decisions. We formalize three domains in which users face everyday decisi...	[ 4546, 634, 13700, 33477 ]	Validation
28,218	28	Title: Interleaved Training for Massive MIMO Downlink via Exploring Spatial Correlation Abstract: Interleaved training has been studied for single-user and multi-user massive MIMO downlink with either fully-digital or hybrid beamforming. However, the impact of channel correlation on its average training overhead is rar...	[]	Train
28,219	24	Title: STG-MTL: Scalable Task Grouping for Multi-Task Learning Using Data Map Abstract: Multi-Task Learning (MTL) is a powerful technique that has gained popularity due to its performance improvement over traditional Single-Task Learning (STL). However, MTL is often challenging because there is an exponential number of...	[]	Train
28,220	16	Title: Cheating off your neighbors: Improving activity recognition through corroboration Abstract: Understanding the complexity of human activities solely through an individual's data can be challenging. However, in many situations, surrounding individuals are likely performing similar activities, while existing human ...	[]	Train
28,221	37	Title: From Words to Code: Harnessing Data for Program Synthesis from Natural Language Abstract: Creating programs to correctly manipulate data is a difficult task, as the underlying programming languages and APIs can be challenging to learn for many users who are not skilled programmers. Large language models (LLMs) d...	[ 37957, 332, 37740, 1326, 19250, 22578, 40020, 5461, 26393, 36636, 39773 ]	Train
28,222	24	Title: Self-Compressing Neural Networks Abstract: This work focuses on reducing neural network size, which is a major driver of neural network execution time, power consumption, bandwidth, and memory footprint. A key challenge is to reduce size in a manner that can be exploited readily for efficient training and infere...	[]	Train
28,223	10	Title: Optimization’s Neglected Normative Commitments Abstract: Optimization is offered as an objective approach to resolving complex, real-world decisions involving uncertainty and conflicting interests. It drives business strategies as well as public policies and, increasingly, lies at the heart of sophisticated mach...	[]	Validation
28,224	24	Title: GANExplainer: GAN-based Graph Neural Networks Explainer Abstract: . With the rapid deployment of graph neural networks (GNNs) based techniques into a wide range of applications such as link prediction, node classiﬁcation, and graph classiﬁcation the explainability of GNNs has become an indispensable component fo...	[]	Train
28,225	16	Title: Collaborative Blind Image Deblurring Abstract: Blurry images usually exhibit similar blur at various locations across the image domain, a property barely captured in nowadays blind deblurring neural networks. We show that when extracting patches of similar underlying blur is possible, jointly processing the stac...	[ 12461 ]	Train
28,226	4	Title: Label Inference Attack against Split Learning under Regression Setting Abstract: As a crucial building block in vertical Federated Learning (vFL), Split Learning (SL) has demonstrated its practice in the two-party model training collaboration, where one party holds the features of data samples and another party ...	[ 30337, 43007 ]	Train
28,227	4	Title: Universal Neural-Cracking-Machines: Self-Configurable Password Models from Auxiliary Data Abstract: We introduce the concept of"universal password model"-- a password model that, once pre-trained, can automatically adapt its guessing strategy based on the target system. To achieve this, the model does not need t...	[]	Train
28,228	15	Title: FlooNoC: A Multi-Tbps Wide NoC for Heterogeneous AXI4 Traffic Abstract: Meeting the staggering bandwidth requirements of today's applications challenges the traditional narrow and serialized NoCs, which hit hard bounds on the maximum operating frequency. This paper proposes FlooNoC, an open-source, low-latency, ...	[]	Train
28,229	16	Title: ESceme: Vision-and-Language Navigation with Episodic Scene Memory Abstract: Vision-and-language navigation (VLN) simulates a visual agent that follows natural-language navigation instructions in real-world scenes. Existing approaches have made enormous progress in navigation in new environments, such as beam sea...	[]	Train
28,230	23	Title: Identifying and Consolidating Knowledge Engineering Requirements Abstract: Knowledge engineering is the process of creating and maintaining knowledge-producing systems. Throughout the history of computer science and AI, knowledge engineering workflows have been widely used because high-quality knowledge is assum...	[]	Train
28,231	24	Title: Classification of Anomalies in Telecommunication Network KPI Time Series Abstract: The increasing complexity and scale of telecommunication networks have led to a growing interest in automated anomaly detection systems. However, the classification of anomalies detected on network Key Performance Indicators (KPI)...	[]	Validation
28,232	24	Title: Analysis of Arrhythmia Classification on ECG Dataset Abstract: The heart is one of the most vital organs in the human body. It supplies blood and nutrients in other parts of the body. Therefore, maintaining a healthy heart is essential. As a heart disorder, arrhythmia is a condition in which the heart's pumping ...	[]	Train
28,233	24	Title: SortedNet, a Place for Every Network and Every Network in its Place: Towards a Generalized Solution for Training Many-in-One Neural Networks Abstract: As the size of deep learning models continues to grow, finding optimal models under memory and computation constraints becomes increasingly more important. Althou...	[ 45470 ]	Train
28,234	25	Title: Lip-to-Speech Synthesis in the Wild with Multi-task Learning Abstract: Recent studies have shown impressive performance in Lip-to-speech synthesis that aims to reconstruct speech from visual information alone. However, they have been suffering from synthesizing accurate speech in the wild, due to insufficient su...	[ 36618, 33326, 19637, 118, 8186, 25052 ]	Train
28,235	24	Title: Towards a Better Understanding of Representation Dynamics under TD-learning Abstract: TD-learning is a foundation reinforcement learning (RL) algorithm for value prediction. Critical to the accuracy of value predictions is the quality of state representations. In this work, we consider the question: how does end...	[]	Test
28,236	25	Title: Speech-to-Speech Translation with Discrete-Unit-Based Style Transfer Abstract: Direct speech-to-speech translation (S2ST) with discrete self-supervised representations has achieved remarkable accuracy, but is unable to preserve the speaker timbre of the source speech during translation. Meanwhile, the scarcity o...	[ 36104, 21778 ]	Test
28,237	27	Title: Runtime optimization of acquisition trajectories for X-ray computed tomography with a robotic sample holder Abstract: Tomographic imaging systems are expected to work with a wide range of samples that house complex structures and challenging material compositions, which can influence image quality in a bad way. ...	[ 1353 ]	Validation
28,238	27	Title: End-to-End Reinforcement Learning for Torque Based Variable Height Hopping Abstract: Legged locomotion is arguably the most suited and versatile mode to deal with natural or unstructured terrains. Intensive research into dynamic walking and running controllers has recently yielded great advances, both in the opt...	[ 21025 ]	Train
28,239	25	Title: From Audio to Symbolic Encoding Abstract: Automatic music transcription (AMT) aims to convert raw audio to symbolic music representation. As a fundamental problem of music information retrieval (MIR), AMT is considered a difficult task even for trained human experts due to overlap of multiple harmonics in the ac...	[]	Train
28,240	24	Title: Addressing Selection Bias in Computerized Adaptive Testing: A User-Wise Aggregate Influence Function Approach Abstract: Computerized Adaptive Testing (CAT) is a widely used, efficient test mode that adapts to the examinee's proficiency level in the test domain. CAT requires pre-trained item profiles, for CAT ite...	[]	Train
28,241	16	Title: STDepthFormer: Predicting Spatio-temporal Depth from Video with a Self-supervised Transformer Model Abstract: In this paper, a self-supervised model that simultaneously predicts a sequence of future frames from video-input with a novel spatial-temporal attention (ST) network is proposed. The ST transformer netwo...	[]	Test
28,242	6	Title: Diminished Diversity-of-Thought in a Standard Large Language Model Abstract: We test whether Large Language Models (LLMs) can be used to simulate human participants in social-science studies. To do this, we run replications of 14 studies from the Many Labs 2 replication project with OpenAI's text-davinci-003 mod...	[ 1664, 17920, 33220, 30668, 4762, 21724 ]	Test
28,243	30	Title: CFSum Coarse-to-Fine Contribution Network for Multimodal Summarization Abstract: Multimodal summarization usually suffers from the problem that the contribution of the visual modality is unclear. Existing multimodal summarization approaches focus on designing the fusion methods of different modalities, while ign...	[]	Train
28,244	27	Title: Ditto in the House: Building Articulation Models of Indoor Scenes through Interactive Perception Abstract: Virtualizing the physical world into virtual models has been a critical technique for robot navigation and planning in the real world. To foster manipulation with articulated objects in everyday life, this ...	[ 13382, 34000, 11570, 42909, 15743 ]	Train
28,245	16	Title: Learning to Transfer In‐Hand Manipulations Using a Greedy Shape Curriculum Abstract: In‐hand object manipulation is challenging to simulate due to complex contact dynamics, non‐repetitive finger gaits, and the need to indirectly control unactuated objects. Further adapting a successful manipulation skill to new ...	[ 15221 ]	Validation
28,246	16	Title: Meta-Learners for Few-Shot Weakly-Supervised Medical Image Segmentation Abstract: Most uses of Meta-Learning in visual recognition are very often applied to image classification, with a relative lack of works in other tasks {such} as segmentation and detection. We propose a generic Meta-Learning framework for fe...	[]	Train
28,247	10	Title: Modeling Human Cognition with a Hybrid Deep Reinforcement Learning Agent Abstract: Human cognition model could help us gain insights in how human cognition behaviors work under external stimuli, pave the way for synthetic data generation, and assist in adaptive intervention design for cognition regulation. When ...	[]	Train
28,248	16	Title: Self-Supervised Graph Transformer for Deepfake Detection Abstract: Deepfake detection methods have shown promising results in recognizing forgeries within a given dataset, where training and testing take place on the in-distribution dataset. However, their performance deteriorates significantly when presented wi...	[]	Train
28,249	24	Title: LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation Abstract: Due to the sweeping digitalization of processes, increasingly vast amounts of time series data are being produced. Accurate classification of such time series facilitates decision making in multiple domains. State-of-th...	[ 34307 ]	Validation
28,250	24	Title: Towards Quantum Federated Learning Abstract: Quantum Federated Learning (QFL) is an emerging interdisciplinary field that merges the principles of Quantum Computing (QC) and Federated Learning (FL), with the goal of leveraging quantum technologies to enhance privacy, security, and efficiency in the learning proc...	[ 22553 ]	Test
28,251	5	Title: Convex Hulls and Triangulations of Planar Point Sets on the Congested Clique Abstract: We consider geometric problems on planar $n^2$-point sets in the congested clique model. Initially, each node in the $n$-clique network holds a batch of $n$ distinct points in the Euclidean plane given by $O(\log n)$-bit coord...	[]	Train
28,252	16	Title: CVFC: Attention-Based Cross-View Feature Consistency for Weakly Supervised Semantic Segmentation of Pathology Images Abstract: Histopathology image segmentation is the gold standard for diagnosing cancer, and can indicate cancer prognosis. However, histopathology image segmentation requires high-quality masks, s...	[ 23320, 754 ]	Train
28,253	39	Title: Optimal local identifying and local locating-dominating codes Abstract: We introduce two new classes of covering codes in graphs for every positive integer $r$. These new codes are called local $r$-identifying and local $r$-locating-dominating codes and they are derived from $r$-identifying and $r$-locating-domi...	[]	Validation
28,254	16	Title: VTPNet for 3D deep learning on point cloud Abstract: Recently, Transformer-based methods for point cloud learning have achieved good results on various point cloud learning benchmarks. However, since the attention mechanism needs to generate three feature vectors of query, key, and value to calculate attention f...	[]	Test
28,255	11	Title: Multi-Cluster Aggregative Games: A Linearly Convergent Nash Equilibrium Seeking Algorithm and its Applications in Energy Management Abstract: We propose a type of non-cooperative game, termed multi-cluster aggregative game, which is composed of clusters as players, where each cluster consists of collaborative ag...	[]	Train
28,256	10	Title: Describing and Organizing Semantic Web and Machine Learning Systems in the SWeMLS-KG Abstract: In line with the general trend in artificial intelligence research to create intelligent systems that combine learning and symbolic components, a new sub-area has emerged that focuses on combining machine learning (ML)...	[ 20398 ]	Train
28,257	28	Title: Attention to Entropic Communication Abstract: The concept of attention, numerical weights that emphasize the importance of particular data, has proven to be very relevant in artificial intelligence. Relative entropy (RE, aka Kullback-Leibler divergence) plays a central role in communication theory. Here we combi...	[]	Train
28,258	36	Title: Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games Abstract: In the first-order query model for zero-sum $K\times K$ matrix games, playersobserve the expected pay-offs for all their possible actions under therandomized action played by their...	[]	Test
28,259	24	Title: Strategy Synthesis in Markov Decision Processes Under Limited Sampling Access Abstract: A central task in control theory, artificial intelligence, and formal methods is to synthesize reward-maximizing strategies for agents that operate in partially unknown environments. In environments modeled by gray-box Markov...	[]	Train
28,260	36	Title: Entropy-Based Strategies for Multi-Bracket Pools Abstract: Much work in the March Madness literature has discussed how to estimate the probability that any one team beats any other team. There has been strikingly little work, however, on what to do with these win probabilities. Hence we pose the multi-brackets p...	[]	Test
28,261	16	Title: Comparing PSDNet, pretrained networks, and traditional feature extraction for predicting the particle size distribution of granular materials from photographs Abstract: This study aims to evaluate PSDNet, a series of convolutional neural networks (ConvNets) trained with photographs to predict the particle size d...	[ 33682 ]	Test
28,262	10	Title: Online Goal Recognition in Discrete and Continuous Domains Using a Vectorial Representation Abstract: While recent work on online goal recognition efficiently infers goals under low observability, comparatively less work focuses on online goal recognition that works in both discrete and continuous domains. Onlin...	[]	Test
28,263	24	Title: On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology Abstract: Message Passing Neural Networks (MPNNs) are instances of Graph Neural Networks that leverage the graph to send messages over the edges. This inductive bias leads to a phenomenon known as over-squashing, where...	[ 2656, 42306, 39650, 2982, 14184, 12267, 22063, 28948, 43193, 40890, 10555, 42942 ]	Train
28,264	16	Title: Score-based Conditional Generation with Fewer Labeled Data by Self-calibrating Classifier Guidance Abstract: Score-based Generative Models (SGMs) are a popular family of deep generative models that achieves leading image generation quality. Earlier studies have extended SGMs to tackle class-conditional generatio...	[]	Train
28,265	24	Title: Feature Collapse Abstract: We formalize and study a phenomenon called feature collapse that makes precise the intuitive idea that entities playing a similar role in a learning task receive similar representations. As feature collapse requires a notion of task, we leverage a simple but prototypical NLP task to st...	[]	Train
28,266	16	Title: NeTO: Neural Reconstruction of Transparent Objects with Self-Occlusion Aware Refraction-Tracing Abstract: We present a novel method, called NeTO, for capturing 3D geometry of solid transparent objects from 2D images via volume rendering. Reconstructing transparent objects is a very challenging task, which is ill...	[]	Train
28,267	34	Title: Tolerant Testing of High-Dimensional Samplers with Subcube Conditioning Abstract: We study the tolerant testing problem for high-dimensional samplers. Given as input two samplers $\mathcal{P}$ and $\mathcal{Q}$ over the $n$-dimensional space $\{0,1\}^n$, and two parameters $\varepsilon_2>\varepsilon_1$, the goal...	[]	Train
28,268	5	Title: Safe, Seamless, And Scalable Integration Of Asynchronous GPU Streams In PETSc Abstract: Leveraging Graphics Processing Units (GPUs) to accelerate scientific software has proven to be highly successful, but in order to extract more performance, GPU programmers must overcome the high latency costs associated with ...	[]	Test
28,269	10	Title: The Equitable AI Research Roundtable (EARR): Towards Community-Based Decision Making in Responsible AI Development Abstract: This paper reports on our initial evaluation of The Equitable AI Research Roundtable -- a coalition of experts in law, education, community engagement, social justice, and technology. EARR...	[]	Train
28,270	30	Title: An Empirical Study of Metrics to Measure Representational Harms in Pre-Trained Language Models Abstract: Large-scale Pre-Trained Language Models (PTLMs) capture knowledge from massive human-written data which contains latent societal biases and toxic contents. In this paper, we leverage the primary task of PTLMs...	[ 43641, 24284 ]	Train
28,271	6	Title: BiHeartS: Bilateral Heart Rate from multiple devices and body positions for Sleep measurement Dataset Abstract: Sleep is the primary mean of recovery from accumulated fatigue and thus plays a crucial role in fostering people's mental and physical well-being. Sleep quality monitoring systems are often implemented...	[]	Test
28,272	16	Title: Pedestrian Crossing Action Recognition and Trajectory Prediction with 3D Human Keypoints Abstract: Accurate understanding and prediction of human behaviors are critical prerequisites for autonomous vehicles, especially in highly dynamic and interactive scenarios such as intersections in dense urban areas. In thi...	[]	Train
28,273	2	Title: Quantitative Verification With Neural Networks For Probabilistic Programs and Stochastic Systems Abstract: We present a data-driven approach to the quantitative verification of probabilistic programs and stochastic dynamical models. Our approach leverages neural networks to compute tight and sound bounds for the...	[]	Train
28,274	23	Title: An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry Abstract: Deep Neural Networks (DNNs) are being adopted as components in software systems. Creating and specializing DNNs from scratch has grown increasingly difficult as state-of-the-art architectures grow more comple...	[ 34243, 25000, 34473, 25738, 40074, 39133, 9213 ]	Train
28,275	16	Title: Learning from Label Proportion with Online Pseudo-Label Decision by Regret Minimization Abstract: This paper proposes a novel and efficient method for Learning from Label Proportions (LLP), whose goal is to train a classifier only by using the class label proportions of instance sets, called bags. We propose a n...	[ 37212 ]	Validation
28,276	27	Title: Optimal Vehicle Trajectory Planning for Static Obstacle Avoidance using Nonlinear Optimization Abstract: Vehicle trajectory planning is a key component for an autonomous driving system. A practical system not only requires the component to compute a feasible trajectory, but also a comfortable one given certain c...	[]	Train
28,277	24	Title: Distributed TD(0) With Almost No Communication Abstract: We provide a new non-asymptotic analysis of distributed temporal difference learning with linear function approximation. Our approach relies on “one-shot averaging,” where N agents run identical local copies of the TD(0) method and average the outcomes onl...	[ 153, 21228, 4335 ]	Train

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