node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
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|---|---|---|---|---|
36,178 | 30 | Title: Few-shot Event Detection: An Empirical Study and a Unified View
Abstract: Few-shot event detection (ED) has been widely studied, while this brings noticeable discrepancies, e.g., various motivations, tasks, and experimental settings, that hinder the understanding of models for future progress.This paper presents... | [
12128,
37921,
6537,
45018,
44189
] | Train |
36,179 | 30 | Title: OpenAssistant Conversations - Democratizing Large Language Model Alignment
Abstract: Aligning large language models (LLMs) with human preferences has proven to drastically improve usability and has driven rapid adoption as demonstrated by ChatGPT. Alignment techniques such as supervised fine-tuning (SFT) and rei... | [
14592,
34178,
13700,
42756,
38533,
34953,
40330,
12940,
38414,
20879,
14609,
22547,
34963,
2197,
10518,
24087,
28440,
43672,
30366,
8608,
12321,
13345,
34208,
43937,
44323,
29999,
2608,
5041,
19378,
43641,
41395,
5815,
6328,
26423,
12474,
9403,
... | Train |
36,180 | 24 | Title: Tight Risk Bounds for Gradient Descent on Separable Data
Abstract: We study the generalization properties of unregularized gradient methods applied to separable linear classification -- a setting that has received considerable attention since the pioneering work of Soudry et al. (2018). We establish tight upper ... | [] | Validation |
36,181 | 24 | Title: Error Feedback Can Accurately Compress Preconditioners
Abstract: Leveraging second-order information at the scale of deep networks is one of the main lines of approach for improving the performance of current optimizers for deep learning. Yet, existing approaches for accurate full-matrix preconditioning, such as... | [
857,
13879
] | Train |
36,182 | 31 | Title: A Diffusion model for POI recommendation
Abstract: Next Point-of-Interest (POI) recommendation is a critical task in location-based services that aim to provide personalized suggestions for the user’s next destination. Previous works on POI recommendation have laid focus on modeling the user’s spatial preference... | [
23377,
41693,
1078,
42511
] | Train |
36,183 | 10 | Title: A optimization framework for herbal prescription planning based on deep reinforcement learning
Abstract: Treatment planning for chronic diseases is a critical task in medical artificial intelligence, particularly in traditional Chinese medicine (TCM). However, generating optimized sequential treatment strategies... | [] | Validation |
36,184 | 5 | Title: MPI Advance : Open-Source Message Passing Optimizations
Abstract: The large variety of production implementations of the message passing interface (MPI) each provide unique and varying underlying algorithms. Each emerging supercomputer supports one or a small number of system MPI installations, tuned for the giv... | [
19148,
14239
] | Train |
36,185 | 30 | Title: CAISA at SemEval-2023 Task 8: Counterfactual Data Augmentation for Mitigating Class Imbalance in Causal Claim Identification
Abstract: Class imbalance problem can cause machine learning models to produce an undesirable performance on the minority class as well as the whole dataset. Using data augmentation techni... | [
30086
] | Test |
36,186 | 24 | Title: Beyond spectral gap (extended): The role of the topology in decentralized learning
Abstract: In data-parallel optimization of machine learning models, workers collaborate to improve their estimates of the model: more accurate gradients allow them to use larger learning rates and optimize faster. In the decentral... | [] | Train |
36,187 | 24 | Title: Detection of DDoS Attacks in Software Defined Networking Using Machine Learning Models
Abstract: The concept of Software Defined Networking (SDN) represents a modern approach to networking that separates the control plane from the data plane through network abstraction, resulting in a flexible, programmable and ... | [] | Test |
36,188 | 4 | Title: Citadel: Enclaves with Strong Microarchitectural Isolation and Secure Shared Memory on a Speculative Out-of-Order Processor
Abstract: We present Citadel, to our knowledge, the first enclave platform with strong microarchitectural isolation to run realistic secure programs on a speculative out-of-order multicore ... | [] | Train |
36,189 | 31 | Title: DataChat: Prototyping a Conversational Agent for Dataset Search and Visualization
Abstract: Data users need relevant context and research expertise to effectively search for and identify relevant datasets. Leading data providers, such as the Inter-university Consortium for Political and Social Research (ICPSR), ... | [
40192
] | Validation |
36,190 | 24 | Title: Layer-wise Adaptive Step-Sizes for Stochastic First-Order Methods for Deep Learning
Abstract: We propose a new per-layer adaptive step-size procedure for stochastic first-order optimization methods for minimizing empirical loss functions in deep learning, eliminating the need for the user to tune the learning ra... | [] | Train |
36,191 | 37 | Title: Comparative Evaluation of Data Decoupling Techniques for Federated Machine Learning with Database as a Service
Abstract: Federated Learning (FL) is a machine learning approach that allows multiple clients to collaboratively learn a shared model without sharing raw data. However, current FL systems provide an all... | [] | Test |
36,192 | 16 | Title: Diffusion Model for Generative Image Denoising
Abstract: In supervised learning for image denoising, usually the paired clean images and noisy images are collected or synthesised to train a denoising model. L2 norm loss or other distance functions are used as the objective function for training. It often leads t... | [
500
] | Train |
36,193 | 27 | Title: From Rolling Over to Walking: Enabling Humanoid Robots to Develop Complex Motor Skills
Abstract: We present a novel method for enabling humanoid robots to learn a wide range of motor skills through reinforcement learning. Our approach introduces an achievement-triggered multi-path reward function that draws on p... | [] | Validation |
36,194 | 16 | Title: Radar Enlighten the Dark: Enhancing Low-Visibility Perception for Automated Vehicles with Camera-Radar Fusion
Abstract: Sensor fusion is a crucial augmentation technique for improving the accuracy and reliability of perception systems for automated vehicles under diverse driving conditions. However, adverse weat... | [] | Train |
36,195 | 25 | Title: Algorithms of Sampling-Frequency-Independent Layers for Non-integer Strides
Abstract: In this paper, we propose algorithms for handling non-integer strides in sampling-frequency-independent (SFI) convolutional and transposed convolutional layers. The SFI layers have been developed for handling various sampling f... | [] | Train |
36,196 | 4 | Title: From Text to MITRE Techniques: Exploring the Malicious Use of Large Language Models for Generating Cyber Attack Payloads
Abstract: This research article critically examines the potential risks and implications arising from the malicious utilization of large language models(LLM), focusing specifically on ChatGPT ... | [
26792,
15601,
45190,
14742
] | Train |
36,197 | 30 | Title: Holistic Exploration on Universal Decompositional Semantic Parsing: Architecture, Data Augmentation, and LLM Paradigm
Abstract: In this paper, we conduct a holistic exploration of the Universal Decompositional Semantic (UDS) Parsing. We first introduce a cascade model for UDS parsing that decomposes the complex ... | [
5643,
23252
] | Validation |
36,198 | 25 | Title: On Data Sampling Strategies for Training Neural Network Speech Separation Models
Abstract: Speech separation remains an important area of multi-speaker signal processing. Deep neural network (DNN) models have attained the best performance on many speech separation benchmarks. Some of these models can take signif... | [] | Train |
36,199 | 8 | Title: How Does Forecasting Affect the Convergence of DRL Techniques in O-RAN Slicing?
Abstract: The success of immersive applications such as virtual reality (VR) gaming and metaverse services depends on low latency and reliable connectivity. To provide seamless user experiences, the open radio access network (O-RAN) ... | [
38155
] | Validation |
36,200 | 24 | Title: Instance-based Explanations for Gradient Boosting Machine Predictions with AXIL Weights
Abstract: We show that regression predictions from linear and tree-based models can be represented as linear combinations of target instances in the training data. This also holds for models constructed as ensembles of trees,... | [] | Train |
36,201 | 10 | Title: LATTE: Label-efficient Incident Phenotyping from Longitudinal Electronic Health Records
Abstract: Electronic health record (EHR) data are increasingly used to support real-world evidence (RWE) studies. Yet its ability to generate reliable RWE is limited by the lack of readily available precise information on the... | [] | Test |
36,202 | 16 | Title: Learning a Room with the Occ-SDF Hybrid: Signed Distance Function Mingled with Occupancy Aids Scene Representation
Abstract: Implicit neural rendering, which uses signed distance function (SDF) representation with geometric priors (such as depth or surface normal), has led to impressive progress in the surface r... | [] | Test |
36,203 | 2 | Title: Symmetries of structures that fail to interpret something finite
Abstract: We investigate structural implications arising from the condition that a given directed graph does not interpret, in the sense of primitive positive interpretation with parameters or orbits, every finite structure. Our results generalize ... | [] | Train |
36,204 | 16 | Title: TrainFors: A Large Benchmark Training Dataset for Image Manipulation Detection and Localization
Abstract: The evaluation datasets and metrics for image manipulation detection and localization (IMDL) research have been standardized. But the training dataset for such a task is still nonstandard. Previous researche... | [] | Train |
36,205 | 30 | Title: UzbekTagger: The rule-based POS tagger for Uzbek language
Abstract: This research paper presents a part-of-speech (POS) annotated dataset and tagger tool for the low-resource Uzbek language. The dataset includes 12 tags, which were used to develop a rule-based POS-tagger tool. The corpus text used in the annotat... | [
28741
] | Validation |
36,206 | 8 | Title: A Comparative Analysis of Deep Reinforcement Learning-based xApps in O-RAN
Abstract: The highly heterogeneous ecosystem of Next Generation (NextG) wireless communication systems calls for novel networking paradigms where functionalities and operations can be dynamically and optimally reconfigured in real time to... | [] | Test |
36,207 | 16 | Title: Active Label Refinement for Semantic Segmentation of Satellite Images
Abstract: Remote sensing through semantic segmentation of satellite images contributes to the understanding and utilisation of the earth's surface. For this purpose, semantic segmentation networks are typically trained on large sets of labelle... | [] | Train |
36,208 | 16 | Title: Salient Object Detection for Images Taken by People With Vision Impairments
Abstract: Salient object detection is the task of producing a binary mask for an image that deciphers which pixels belong to the foreground object versus background. We introduce a new salient object detection dataset using images taken ... | [
10561
] | Train |
36,209 | 24 | Title: Deep Gaussian Markov Random Fields for Graph-Structured Dynamical Systems
Abstract: Probabilistic inference in high-dimensional state-space models is computationally challenging. For many spatiotemporal systems, however, prior knowledge about the dependency structure of state variables is available. We leverage ... | [] | Test |
36,210 | 16 | Title: HODINet: High-Order Discrepant Interaction Network for RGB-D Salient Object Detection
Abstract: RGB-D salient object detection (SOD) aims to detect the prominent regions by jointly modeling RGB and depth information. Most RGB-D SOD methods apply the same type of backbones and fusion modules to identically learn ... | [] | Validation |
36,211 | 24 | Title: Optimal Sample Complexity of Reinforcement Learning for Uniformly Ergodic Discounted Markov Decision Processes
Abstract: We consider the optimal sample complexity theory of tabular reinforcement learning (RL) for controlling the infinite horizon discounted reward in a Markov decision process (MDP). Optimal min-m... | [] | Train |
36,212 | 16 | Title: Classification robustness to common optical aberrations
Abstract: Computer vision using deep neural networks (DNNs) has brought about seminal changes in people's lives. Applications range from automotive, face recognition in the security industry, to industrial process monitoring. In some cases, DNNs infer even ... | [] | Validation |
36,213 | 15 | Title: ViTA: A Vision Transformer Inference Accelerator for Edge Applications
Abstract: Vision Transformer models, such as ViT, Swin Transformer, and Transformer-in-Transformer, have recently gained significant traction in computer vision tasks due to their ability to capture the global relation between features which ... | [
42233
] | Train |
36,214 | 6 | Title: UnifiedGesture: A Unified Gesture Synthesis Model for Multiple Skeletons
Abstract: The automatic co-speech gesture generation draws much attention in computer animation. Previous works designed network structures on individual datasets, which resulted in a lack of data volume and generalizability across differen... | [
42786,
41699,
33512,
19667,
15092,
39606,
28055,
17241,
42397
] | Train |
36,215 | 10 | Title: Delivering Inflated Explanations
Abstract: In the quest for Explainable Artificial Intelligence (XAI) one of the questions that frequently arises given a decision made by an AI system is, ``why was the decision made in this way?'' Formal approaches to explainability build a formal model of the AI system and use ... | [] | Train |
36,216 | 16 | Title: A temporally quantized distribution of pupil diameters as a new feature for cognitive load classification
Abstract: In this paper, we present a new feature that can be used to classify cognitive load based on pupil information. The feature consists of a temporal segmentation of the eye tracking recordings. For e... | [] | Validation |
36,217 | 11 | Title: A Method for Emerging Empirical Age Structures in Agent-Based Models with Exogenous Survival Probabilities
Abstract: For many applications of agent-based models (ABMs), an agent's age influences important decisions (e.g. their contribution to/withdrawal from pension funds, their level of risk aversion in decisio... | [] | Validation |
36,218 | 16 | Title: Temporal Interpolation is all You Need for Dynamic Neural Radiance Fields
Abstract: Temporal interpolation often plays a crucial role to learn meaningful representations in dynamic scenes. In this paper, we propose a novel method to train spatiotemporal neural radiance fields of dynamic scenes based on temporal ... | [
15944,
37769,
15458
] | Train |
36,219 | 27 | Title: Bio-inspired spike-based Hippocampus and Posterior Parietal Cortex models for robot navigation and environment pseudo-mapping
Abstract: The brain has a great capacity for computation and efficient resolution of complex problems, far surpassing modern computers. Neuromorphic engineering seeks to mimic the basic p... | [] | Validation |
36,220 | 30 | Title: Explaining Hate Speech Classification with Model Agnostic Methods
Abstract: There have been remarkable breakthroughs in Machine Learning and Artificial Intelligence, notably in the areas of Natural Language Processing and Deep Learning. Additionally, hate speech detection in dialogues has been gaining popularity... | [
22641
] | Train |
36,221 | 27 | Title: Zero-Shot Transfer of Haptics-Based Object Insertion Policies
Abstract: Humans naturally exploit haptic feedback during contact-rich tasks like loading a dishwasher or stocking a bookshelf. Current robotic systems focus on avoiding unexpected contact, often relying on strategically placed environment sensors. Re... | [] | Train |
36,222 | 30 | Title: The eBible Corpus: Data and Model Benchmarks for Bible Translation for Low-Resource Languages
Abstract: Efficiently and accurately translating a corpus into a low-resource language remains a challenge, regardless of the strategies employed, whether manual, automated, or a combination of the two. Many Christian o... | [] | Train |
36,223 | 17 | Title: Automatic Joint Parameter Estimation from Magnetic Motion Capture Data
Abstract: This paper describes a technique for using magnetic motion capture data to determine the joint parameters of an articulated hierarchy. This technique makes it possible to determine limb lengths, joint locations, and sensor placement... | [
45122,
32791
] | Test |
36,224 | 16 | Title: ELIXR: Towards a general purpose X-ray artificial intelligence system through alignment of large language models and radiology vision encoders
Abstract: In this work, we present an approach, which we call Embeddings for Language/Image-aligned X-Rays, or ELIXR, that leverages a language-aligned image encoder comb... | [
10624,
7833,
18404
] | Validation |
36,225 | 37 | Title: Pylon: Semantic Table Union Search in Data Lakes
Abstract: The large size and fast growth of data repositories, such as data lakes, has spurred the need for data discovery to help analysts find related data. The problem has become challenging as (i) a user typically does not know what datasets exist in an enormo... | [] | Validation |
36,226 | 24 | Title: Slice-and-Forge: Making Better Use of Caches for Graph Convolutional Network Accelerators
Abstract: Graph convolutional networks (GCNs) are becoming increasingly popular as they can process a wide variety of data formats that prior deep neural networks cannot easily support. One key challenge in designing hardwa... | [
18243,
9755,
31532
] | Train |
36,227 | 24 | Title: LAVA: Data Valuation without Pre-Specified Learning Algorithms
Abstract: Traditionally, data valuation is posed as a problem of equitably splitting the validation performance of a learning algorithm among the training data. As a result, the calculated data values depend on many design choices of the underlying l... | [
8669,
31949,
2397
] | Validation |
36,228 | 24 | Title: Modeling Dynamic Environments with Scene Graph Memory
Abstract: Embodied AI agents that search for objects in large environments such as households often need to make efficient decisions by predicting object locations based on partial information. We pose this as a new type of link prediction problem: link predi... | [
37609
] | Train |
36,229 | 24 | Title: Spatial Graph Coarsening: Weather and Weekday Prediction with London's Bike-Sharing Service using GNN
Abstract: This study introduced the use of Graph Neural Network (GNN) for predicting the weather and weekday of a day in London, from the dataset of Santander Cycles bike-sharing system as a graph classification... | [] | Train |
36,230 | 24 | Title: Neural Network Entropy (NNetEn): Entropy-Based EEG Signal and Chaotic Time Series Classification, Python Package for NNetEn Calculation
Abstract: Entropy measures are effective features for time series classification problems. Traditional entropy measures, such as Shannon entropy, use probability distribution fu... | [
21678
] | Test |
36,231 | 27 | Title: On Semidefinite Relaxations for Matrix-Weighted State-Estimation Problems in Robotics
Abstract: In recent years, there has been remarkable progress in the development of so-called certifiable perception methods, which leverage semidefinite, convex relaxations to find global optima of perception problems in robot... | [
17009,
21595
] | Train |
36,232 | 36 | Title: Maximizing Social Welfare in Score-Based Social Distance Games
Abstract: Social distance games have been extensively studied as a coalition formation model where the utilities of agents in each coalition were captured using a utility function u that took into account distances in a given social network. In this ... | [
28497
] | Train |
36,233 | 30 | Title: Teamwork Is Not Always Good: An Empirical Study of Classifier Drift in Class-incremental Information Extraction
Abstract: Class-incremental learning (CIL) aims to develop a learning system that can continually learn new classes from a data stream without forgetting previously learned classes. When learning class... | [
12128,
44189
] | Train |
36,234 | 27 | Title: Human Following Based on Visual Perception in the Context of Warehouse Logistics
Abstract: Warehousing and logistics robots, which have benefited from the development of 5G, the internet, artificial intelligence, and robot technology, are commonly used to assist warehouse personnel in picking up or delivering he... | [] | Train |
36,235 | 4 | Title: EESMR: Energy Efficient BFT-SMR for the masses
Abstract: Modern Byzantine Fault-Tolerant State Machine Replication (BFT-SMR) solutions focus on reducing communication complexity, improving throughput, or lowering latency. This work explores the energy efficiency of BFT-SMR protocols. First, we propose a novel SM... | [] | Train |
36,236 | 24 | Title: On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation
Abstract: Although powerful graph neural networks (GNNs) have boosted numerous real-world applications, the potential privacy risk is still underexplored. To close this gap, we perform the first comprehensive study of grap... | [] | Train |
36,237 | 27 | Title: Reactive Landing Controller for Quadruped Robots
Abstract: Quadruped robots are machines intended for challenging and harsh environments. Despite the progress in locomotion strategy, safely recovering from unexpected falls or planned drops is still an open problem. It is further made more difficult when high hor... | [
21323,
8845
] | Train |
36,238 | 28 | Title: A New Information Theory of Certainty for Machine Learning
Abstract: Claude Shannon coined entropy to quantify the uncertainty of a random distribution for communication coding theory. We observe that the uncertainty nature of entropy also limits its direct usage in mathematical modeling. Therefore we propose a ... | [
41014
] | Train |
36,239 | 27 | Title: Active Velocity Estimation using Light Curtains via Self-Supervised Multi-Armed Bandits
Abstract: To navigate in an environment safely and autonomously, robots must accurately estimate where obstacles are and how they move. Instead of using expensive traditional 3D sensors, we explore the use of a much cheaper, ... | [] | Train |
36,240 | 24 | Title: Towards a responsible machine learning approach to identify forced labor in fisheries
Abstract: Many fishing vessels use forced labor, but identifying vessels that engage in this practice is challenging because few are regularly inspected. We developed a positive-unlabeled learning algorithm using vessel charact... | [] | Train |
36,241 | 24 | Title: Gradient is All You Need?
Abstract: In this paper we provide a novel analytical perspective on the theoretical understanding of gradient-based learning algorithms by interpreting consensus-based optimization (CBO), a recently proposed multi-particle derivative-free optimization method, as a stochastic relaxation... | [
40035
] | Train |
36,242 | 24 | Title: Fair yet Asymptotically Equal Collaborative Learning
Abstract: In collaborative learning with streaming data, nodes (e.g., organizations) jointly and continuously learn a machine learning (ML) model by sharing the latest model updates computed from their latest streaming data. For the more resourceful nodes to b... | [] | Train |
36,243 | 27 | Title: ReProHRL: Towards Multi-Goal Navigation in the Real World using Hierarchical Agents
Abstract: Robots have been successfully used to perform tasks with high precision. In real-world environments with sparse rewards and multiple goals, learning is still a major challenge and Reinforcement Learning (RL) algorithms ... | [] | Validation |
36,244 | 24 | Title: Towards Optimal Randomized Strategies in Adversarial Example Game
Abstract: The vulnerability of deep neural network models to adversarial example attacks is a practical challenge in many artificial intelligence applications. A recent line of work shows that the use of randomization in adversarial training is th... | [] | Train |
36,245 | 16 | Title: Navigating Uncertainty: The Role of Short-Term Trajectory Prediction in Autonomous Vehicle Safety
Abstract: Autonomous vehicles require accurate and reliable short-term trajectory predictions for safe and efficient driving. While most commercial automated vehicles currently use state machine-based algorithms for... | [] | Train |
36,246 | 24 | Title: LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning
Abstract: Recent methods for imitation learning directly learn a $Q$-function using an implicit reward formulation rather than an explicit reward function. However, these methods generally require implicit reward regularization to improve s... | [
10498,
42934,
11902
] | Validation |
36,247 | 24 | Title: A Survey on Class Imbalance in Federated Learning
Abstract: Federated learning, which allows multiple client devices in a network to jointly train a machine learning model without direct exposure of clients' data, is an emerging distributed learning technique due to its nature of privacy preservation. However, i... | [] | Validation |
36,248 | 16 | Title: Anatomy-Driven Pathology Detection on Chest X-rays
Abstract: Pathology detection and delineation enables the automatic interpretation of medical scans such as chest X-rays while providing a high level of explainability to support radiologists in making informed decisions. However, annotating pathology bounding b... | [] | Train |
36,249 | 31 | Title: PiTL: Cross-modal Retrieval with Weakly-supervised Vision-language Pre-training via Prompting
Abstract: Vision-language (VL) Pre-training (VLP) has shown to well generalize VL models over a wide range of VL downstream tasks, especially for cross-modal retrieval. However, it hinges on a huge amount of image-text ... | [
10624
] | Validation |
36,250 | 37 | Title: Bridging graph data models: RDF, RDF-star, and property graphs as directed acyclic graphs
Abstract: Graph database users today face a choice between two technology stacks: the Resource Description Framework (RDF), on one side, is a data model with built-in semantics that was originally developed by the W3C to ex... | [] | Test |
36,251 | 4 | Title: The Doctrine of Cyber Effect: An Ethics Framework for Defensive Cyber Deception
Abstract: The lack of established rules and regulations in cyberspace is attributed to the absence of agreed-upon ethical principles, making it difficult to establish accountability, regulations, and laws. Addressing this challenge r... | [
10282,
18853
] | Train |
36,252 | 30 | Title: Instruct-FinGPT: Financial Sentiment Analysis by Instruction Tuning of General-Purpose Large Language Models
Abstract: Sentiment analysis is a vital tool for uncovering insights from financial articles, news, and social media, shaping our understanding of market movements. Despite the impressive capabilities of ... | [
40192,
13700,
25936,
27537,
24308
] | Test |
36,253 | 6 | Title: Community College Articulation Agreement Websites: Students' Suggestions for New Academic Advising Software Features
Abstract: Purpose: Community college counselors and students use articulation agreement websites to (a) learn how community college courses will transfer and fulfill university requirements and (b... | [] | Train |
36,254 | 24 | Title: Data-Driven Projection for Reducing Dimensionality of Linear Programs: Generalization Bound and Learning Methods
Abstract: This paper studies a simple data-driven approach to high-dimensional linear programs (LPs). Given data of past $n$-dimensional LPs, we learn an $n\times k$ \textit{projection matrix} ($n>k$)... | [
22088
] | Test |
36,255 | 31 | Title: Continuous Input Embedding Size Search For Recommender Systems
Abstract: Latent factor models are the most popular backbones for today's recommender systems owing to their prominent performance. Latent factor models represent users and items as real-valued embedding vectors for pairwise similarity computation, a... | [
36861,
23389,
10286
] | Train |
36,256 | 24 | Title: Duality in Multi-View Restricted Kernel Machines
Abstract: We propose a unifying setting that combines existing restricted kernel machine methods into a single primal-dual multi-view framework for kernel principal component analysis in both supervised and unsupervised settings. We derive the primal and dual repr... | [
31958,
7887
] | Train |
36,257 | 16 | Title: EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation
Abstract: Locating 3D objects from a single RGB image via Perspective-n-Points (PnP) is a long-standing problem in computer vision. Driven by end-to-end deep learning, recent studies suggest interpreting PnP ... | [
28803,
45970,
39960,
16538,
20768,
9121,
21802,
4526,
1087,
34497,
19269,
9932,
22861,
40140,
9428,
25300,
23513,
218,
17372,
4451,
8809,
30955,
13949
] | Validation |
36,258 | 14 | Title: Jordan algebra in R
Abstract: In this short article I introduce the"jordan"package which provides functionality for working with different types of Jordan algebra. I give some numerical verification of the Jordan identity for the five types of Jordan algebras. The package is available on CRAN at https://CRAN.R-p... | [] | Train |
36,259 | 27 | Title: Learning to Explore Informative Trajectories and Samples for Embodied Perception
Abstract: We are witnessing significant progress on perception models, specifically those trained on large-scale internet images. However, efficiently generalizing these perception models to unseen embodied tasks is insufficiently s... | [] | Train |
36,260 | 30 | Title: Bypass Temporal Classification: Weakly Supervised Automatic Speech Recognition with Imperfect Transcripts
Abstract: This paper presents a novel algorithm for building an automatic speech recognition (ASR) model with imperfect training data. Imperfectly transcribed speech is a prevalent issue in human-annotated s... | [] | Validation |
36,261 | 28 | Title: Fundamental CRB-Rate Tradeoff in Multi-Antenna ISAC Systems with Information Multicasting and Multi-Target Sensing
Abstract: This paper investigates the performance tradeoff for a multi-antenna integrated sensing and communication (ISAC) system with simultaneous information multicasting and multi-target sensing,... | [] | Validation |
36,262 | 16 | Title: Convolutional Neural Networks Rarely Learn Shape for Semantic Segmentation
Abstract: Shape learning, or the ability to leverage shape information, could be a desirable property of convolutional neural networks (CNNs) when target objects have specific shapes. While some research on the topic is emerging, there is... | [] | Train |
36,263 | 30 | Title: Exploring New Frontiers in Agricultural NLP: Investigating the Potential of Large Language Models for Food Applications
Abstract: This paper explores new frontiers in agricultural natural language processing by investigating the effectiveness of using food-related text corpora for pretraining transformer-based l... | [
20355,
13700,
45189,
11273,
34327,
24,
37531,
31147,
24756,
7996,
575,
45505,
33220,
15301,
16581,
29396,
16471,
35041,
6124,
44272,
1151
] | Validation |
36,264 | 24 | Title: Model-agnostic machine learning of conservation laws from data
Abstract: We present a machine learning based method for learning first integrals of systems of ordinary differential equations from given trajectory data. The method is model-agnostic in that it does not require explicit knowledge of the underlying ... | [] | Validation |
36,265 | 16 | Title: Learning Profitable NFT Image Diffusions via Multiple Visual-Policy Guided Reinforcement Learning
Abstract: We study the task of generating profitable Non-Fungible Token (NFT) images from user-input texts. Recent advances in diffusion models have shown great potential for image generation. However, existing work... | [
18272,
4194,
11820,
7597,
27184,
33621
] | Train |
36,266 | 4 | Title: ItyFuzz: Snapshot-Based Fuzzer for Smart Contract
Abstract: Smart contracts are critical financial instruments, and their security is of utmost importance. However, smart contract programs are difficult to fuzz due to the persistent blockchain state behind all transactions. Mutating sequences of transactions are... | [
45566
] | Train |
36,267 | 16 | Title: Scaling may be all you need for achieving human-level object recognition capacity with human-like visual experience
Abstract: This paper asks whether current self-supervised learning methods, if sufficiently scaled up, would be able to reach human-level visual object recognition capabilities with the same type a... | [
20696
] | Train |
36,268 | 27 | Title: DexRepNet: Learning Dexterous Robotic Grasping Network with Geometric and Spatial Hand-Object Representations
Abstract: Robotic dexterous grasping is a challenging problem due to the high degree of freedom (DoF) and complex contacts of multi-fingered robotic hands. Existing deep reinforcement learning (DRL) base... | [
15221
] | Train |
36,269 | 24 | Title: Continual Causal Effect Estimation: Challenges and Opportunities
Abstract: A further understanding of cause and effect within observational data is critical across many domains, such as economics, health care, public policy, web mining, online advertising, and marketing campaigns. Although significant advances h... | [
3892,
13583
] | Train |
36,270 | 16 | Title: RadarGNN: Transformation Invariant Graph Neural Network for Radar-based Perception
Abstract: A reliable perception has to be robust against challenging environmental conditions. Therefore, recent efforts focused on the use of radar sensors in addition to camera and lidar sensors for perception applications. Howe... | [] | Train |
36,271 | 16 | Title: PhysBench: A Benchmark Framework for Remote Physiological Sensing with New Dataset and Baseline
Abstract: In recent years, due to the widespread use of internet videos, physiological remote sensing has gained more and more attention in the fields of affective computing and telemedicine. Recovering physiological ... | [] | Train |
36,272 | 16 | Title: Dynamic Token Pruning in Plain Vision Transformers for Semantic Segmentation
Abstract: Vision transformers have achieved leading performance on various visual tasks yet still suffer from high computational complexity. The situation deteriorates in dense prediction tasks like semantic segmentation, as high-resolu... | [] | Train |
36,273 | 34 | Title: Edge-Coloring Algorithms for Bounded Degree Multigraphs
Abstract: In this paper, we consider algorithms for edge-coloring multigraphs $G$ of bounded maximum degree, i.e., $\Delta(G) = O(1)$. Shannon's theorem states that any multigraph of maximum degree $\Delta$ can be properly edge-colored with $\lfloor 3\Delta... | [
23716
] | Train |
36,274 | 28 | Title: Trade-offs Between Weak-Noise Performance and Probability of Anomaly in Parameter Estimation from Noisy Chaotic Signals
Abstract: We consider the problem of parameter estimation, based on noisy chaotic signals, from the viewpoint of twisted modulation for waveform communication. In particular, we study communica... | [] | Test |
36,275 | 24 | Title: Mastering the exploration-exploitation trade-off in Bayesian Optimization
Abstract: Gaussian Process based Bayesian Optimization is a well-known sample efficient sequential strategy for globally optimizing black-box, expensive, and multi-extremal functions. The role of the Gaussian Process is to provide a probab... | [] | Train |
36,276 | 16 | Title: Identification of Novel Classes for Improving Few-Shot Object Detection
Abstract: Conventional training of deep neural networks requires a large number of the annotated image which is a laborious and time-consuming task, particularly for rare objects. Few-shot object detection (FSOD) methods offer a remedy by re... | [
23909
] | Train |
36,277 | 4 | Title: DRAINCLoG: Detecting Rogue Accounts with Illegally-obtained NFTs using Classifiers Learned on Graphs
Abstract: As Non-Fungible Tokens (NFTs) continue to grow in popularity, NFT users have become targets of phishing attacks by cybercriminals, called NFT drainers. Over the last year, \$100 million worth of NFTs we... | [
6696
] | Train |
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