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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|---|---|---|---|---|
19,678 | 4 | Title: Hybrid load balancing method with failover capability in server cluster using SDN
Abstract: Traditional load balancers used in server clusters have problems such as lack of flexibility, high cost, etc. To overcome these problems, research has been conducted to apply a load balancer using software-defined network... | [] | Train |
19,679 | 10 | Title: Bayesian artificial brain with ChatGPT
Abstract: This paper aims to investigate the mathematical problem-solving capabilities of Chat Generative Pre-Trained Transformer (ChatGPT) in case of Bayesian reasoning. The study draws inspiration from Zhu&Gigerenzer's research in 2006, which posed the question: Can child... | [] | Test |
19,680 | 24 | Title: Shared Adversarial Unlearning: Backdoor Mitigation by Unlearning Shared Adversarial Examples
Abstract: Backdoor attacks are serious security threats to machine learning models where an adversary can inject poisoned samples into the training set, causing a backdoored model which predicts poisoned samples with par... | [
30307,
43782,
6222,
7312,
8669
] | Train |
19,681 | 10 | Title: CGMI: Configurable General Multi-Agent Interaction Framework
Abstract: Benefiting from the powerful capabilities of large language models (LLMs), agents based on LLMs have shown the potential to address domain-specific tasks and emulate human behaviors. However, the content generated by these agents remains some... | [
33477,
2549
] | Train |
19,682 | 31 | Title: Is Meta-Learning the Right Approach for the Cold-Start Problem in Recommender Systems?
Abstract: Recommender systems have become fundamental building blocks of modern online products and services, and have a substantial impact on user experience. In the past few years, deep learning methods have attracted a lot ... | [] | Test |
19,683 | 5 | Title: Robust Fully-Asynchronous Methods for Distributed Training over General Architecture
Abstract: Perfect synchronization in distributed machine learning problems is inefficient and even impossible due to the existence of latency, package losses and stragglers. We propose a Robust Fully-Asynchronous Stochastic Grad... | [] | Validation |
19,684 | 24 | Title: Convergence and Privacy of Decentralized Nonconvex Optimization with Gradient Clipping and Communication Compression
Abstract: Achieving communication efficiency in decentralized machine learning has been attracting significant attention, with communication compression recognized as an effective technique in alg... | [
4064,
29579,
4244
] | Train |
19,685 | 30 | Title: Large-Scale Text Analysis Using Generative Language Models: A Case Study in Discovering Public Value Expressions in AI Patents
Abstract: Labeling data is essential for training text classifiers but is often difficult to accomplish accurately, especially for complex and abstract concepts. Seeking an improved meth... | [
13700,
15301,
13510
] | Validation |
19,686 | 24 | Title: Inductive Graph Unlearning
Abstract: As a way to implement the"right to be forgotten"in machine learning, \textit{machine unlearning} aims to completely remove the contributions and information of the samples to be deleted from a trained model without affecting the contributions of other samples. Recently, many ... | [
36725
] | Train |
19,687 | 8 | Title: NeutRAN: An Open RAN Neutral Host Architecture for Zero-Touch RAN and Spectrum Sharing
Abstract: Obtaining access to exclusive spectrum, cell sites, Radio Access Network (RAN) equipment, and edge infrastructure imposes major capital expenses to mobile network operators. A neutral host infrastructure, by which a ... | [] | Test |
19,688 | 27 | Title: Temporal Video-Language Alignment Network for Reward Shaping in Reinforcement Learning
Abstract: Designing appropriate reward functions for Reinforcement Learning (RL) approaches has been a significant problem, especially for complex environments such as Atari games. Utilizing natural language instructions to pr... | [] | Train |
19,689 | 16 | Title: Open-World Pose Transfer via Sequential Test-Time Adaption
Abstract: Pose transfer aims to transfer a given person into a specified posture, has recently attracted considerable attention. A typical pose transfer framework usually employs representative datasets to train a discriminative model, which is often vio... | [
43608
] | Validation |
19,690 | 28 | Title: A Wideband MIMO Channel Model for Aerial Intelligent Reflecting Surface-Assisted Wireless Communications
Abstract: Compared to traditional intelligent reflecting surfaces(IRS), aerial IRS (AIRS) has unique advantages, such as more flexible deployment and wider service coverage. However, modeling AIRS in the chan... | [] | Validation |
19,691 | 30 | Title: Large Language Models in Analyzing Crash Narratives - A Comparative Study of ChatGPT, BARD and GPT-4
Abstract: In traffic safety research, extracting information from crash narratives using text analysis is a common practice. With recent advancements of large language models (LLM), it would be useful to know how... | [
613
] | Validation |
19,692 | 24 | Title: Context-Aware Differential Privacy for Language Modeling
Abstract: The remarkable ability of language models (LMs) has also brought challenges at the interface of AI and security. A critical challenge pertains to how much information these models retain and leak about the training data. This is particularly urge... | [] | Train |
19,693 | 16 | Title: PolyDiffuse: Polygonal Shape Reconstruction via Guided Set Diffusion Models
Abstract: This paper presents PolyDiffuse, a novel structured reconstruction algorithm that transforms visual sensor data into polygonal shapes with Diffusion Models (DM), an emerging machinery amid exploding generative AI, while formula... | [
2633,
33251,
13596
] | Train |
19,694 | 25 | Title: Collaborative Song Dataset (CoSoD): An annotated dataset of multi-artist collaborations in popular music
Abstract: The Collaborative Song Dataset (CoSoD) is a corpus of 331 multi-artist collaborations from the 2010-2019 Billboard"Hot 100"year-end charts. The corpus is annotated with formal sections, aspects of v... | [] | Train |
19,695 | 36 | Title: Steering No-Regret Learners to Optimal Equilibria
Abstract: We consider the problem of steering no-regret-learning agents to play desirable equilibria in extensive-form games via nonnegative payments. We show that steering is impossible if the total budget (across iterations) is finite. However, with average, re... | [
33202,
19770,
28390
] | Train |
19,696 | 24 | Title: Flag Aggregator: Scalable Distributed Training under Failures and Augmented Losses using Convex Optimization
Abstract: Modern ML applications increasingly rely on complex deep learning models and large datasets. There has been an exponential growth in the amount of computation needed to train the largest models.... | [] | Test |
19,697 | 24 | Title: A Dual Formulation for Probabilistic Principal Component Analysis
Abstract: In this paper, we characterize Probabilistic Principal Component Analysis in Hilbert spaces and demonstrate how the optimal solution admits a representation in dual space. This allows us to develop a generative framework for kernel metho... | [] | Validation |
19,698 | 16 | Title: ReBotNet: Fast Real-time Video Enhancement
Abstract: Most video restoration networks are slow, have high computational load, and can't be used for real-time video enhancement. In this work, we design an efficient and fast framework to perform real-time video enhancement for practical use-cases like live video ca... | [] | Train |
19,699 | 4 | Title: 5G-SRNG: 5G Spectrogram-based Random Number Generation for Devices with Low Entropy Sources
Abstract: Random number generation (RNG) is a crucial element in security protocols, and its performance and reliability are critical for the safety and integrity of digital systems. This is especially true in 5G networks... | [
32326
] | Train |
19,700 | 16 | Title: Makeup Extraction of 3D Representation via Illumination‐Aware Image Decomposition
Abstract: Facial makeup enriches the beauty of not only real humans but also virtual characters; therefore, makeup for 3D facial models is highly in demand in productions. However, painting directly on 3D faces and capturing real‐w... | [] | Train |
19,701 | 24 | Title: Incremental Outlier Detection Modelling Using Streaming Analytics in Finance & Health Care
Abstract: In this paper, we had built the online model which are built incrementally by using online outlier detection algorithms under the streaming environment. We identified that there is highly necessity to have the st... | [] | Test |
19,702 | 31 | Title: Injecting the BM25 Score as Text Improves BERT-Based Re-rankers
Abstract: In this paper we propose a novel approach for combining first-stage lexical retrieval models and Transformer-based re-rankers: we inject the relevance score of the lexical model as a token in the middle of the input of the cross-encoder re... | [
13865,
34981,
23558,
25089
] | Train |
19,703 | 10 | Title: Revisiting Inferential Benchmarks for Knowledge Graph Completion
Abstract: Knowledge Graph (KG) completion is the problem of extending an incomplete KG with missing facts. A key feature of Machine Learning approaches for KG completion is their ability to learn inference patterns, so that the predicted facts are ... | [
5451
] | Train |
19,704 | 24 | Title: Effectively Modeling Time Series with Simple Discrete State Spaces
Abstract: Time series modeling is a well-established problem, which often requires that methods (1) expressively represent complicated dependencies, (2) forecast long horizons, and (3) efficiently train over long sequences. State-space models (SS... | [
43873,
15270,
40652,
42064,
6457,
15838
] | Test |
19,705 | 24 | Title: SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models
Abstract: Diffusion Probabilistic Models (DPMs) have achieved considerable success in generation tasks. As sampling from DPMs is equivalent to solving diffusion SDE or ODE which is time-consuming, numerous fast sampling methods built upon i... | [
12515,
23563,
20624,
37299,
6133
] | Train |
19,706 | 1 | Title: Generative Steganography Diffusion
Abstract: Generative steganography (GS) is an emerging technique that generates stego images directly from secret data. Various GS methods based on GANs or Flow have been developed recently. However, existing GAN-based GS methods cannot completely recover the hidden secret data... | [
26003,
6589,
3614
] | Test |
19,707 | 24 | Title: Carbon Emission Prediction and Clean Industry Transformation Based on Machine Learning: A Case Study of Sichuan Province
Abstract: This study preprocessed 2000-2019 energy consumption data for 46 key Sichuan industries using matrix normalization. DBSCAN clustering identified 16 feature classes to objectively gro... | [] | Validation |
19,708 | 24 | Title: Disentanglement via Latent Quantization
Abstract: In disentangled representation learning, a model is asked to tease apart a dataset's underlying sources of variation and represent them independently of one another. Since the model is provided with no ground truth information about these sources, inductive biase... | [] | Train |
19,709 | 24 | Title: Evaluating Language Models for Mathematics through Interactions
Abstract: The standard methodology of evaluating large language models (LLMs) based on static pairs of inputs and outputs is insufficient for developing assistants: this kind of assessments fails to take into account the essential interactive elemen... | [
12602
] | Validation |
19,710 | 16 | Title: Opening the Vocabulary of Egocentric Actions
Abstract: Human actions in egocentric videos are often hand-object interactions composed from a verb (performed by the hand) applied to an object. Despite their extensive scaling up, egocentric datasets still face two limitations - sparsity of action compositions and ... | [
32960,
27273,
1063
] | Train |
19,711 | 17 | Title: Sampling Visible GGX Normals with Spherical Caps
Abstract: Importance sampling the distribution of visible GGX normals requires sampling those of a hemisphere. In this work, we introduce a novel method for sampling such visible normals. Our method builds upon the insight that a hemispherical mirror reflects para... | [] | Train |
19,712 | 28 | Title: A General Approach to Fully Linearize the Power Amplifiers in mMIMO with Less Complexity
Abstract: A radio frequency (RF) power amplifier (PA) plays an important role to amplify the message signal at higher power to transmit it to a distant receiver. Due to a typical nonlinear behavior of the PA at high power tr... | [] | Test |
19,713 | 16 | Title: An Open Hyperspectral Dataset with Sea-Land-Cloud Ground-Truth from the HYPSO-1 Satellite
Abstract: Hyperspectral Imaging, employed in satellites for space remote sensing, like HYPSO-1, faces constraints due to few labeled data sets, affecting the training of AI models demanding these ground-truth annotations. I... | [] | Train |
19,714 | 30 | Title: DN at SemEval-2023 Task 12: Low-Resource Language Text Classification via Multilingual Pretrained Language Model Fine-tuning
Abstract: In our work, a model is implemented that solves the task, based on multilingual pre-trained models. We also consider various methods of data preprocessing | [
34249,
24954,
20226
] | Test |
19,715 | 24 | Title: Improving Adversarial Transferability with Scheduled Step Size and Dual Example
Abstract: Deep neural networks are widely known to be vulnerable to adversarial examples, especially showing significantly poor performance on adversarial examples generated under the white-box setting. However, all white-box attack m... | [
34159,
11143
] | Validation |
19,716 | 16 | Title: TFNet: Exploiting Temporal Cues for Fast and Accurate LiDAR Semantic Segmentation
Abstract: LiDAR semantic segmentation plays a crucial role in enabling autonomous driving and robots to understand their surroundings accurately and robustly. There are different types of methods, such as point-based, range-image-b... | [
16251,
37539,
36551,
30092,
30669,
4443,
2110
] | Validation |
19,717 | 34 | Title: Efficiency of Self-Adjusting Heaps
Abstract: Since the invention of the pairing heap by Fredman et al., it has been an open question whether this or any other simple"self-adjusting"heap supports decrease-key operations on $n$-item heaps in $O(\log\log n)$ time. Using powerful new techniques, we answer this quest... | [] | Train |
19,718 | 30 | Title: A Review of Vision-Language Models and their Performance on the Hateful Memes Challenge
Abstract: Moderation of social media content is currently a highly manual task, yet there is too much content posted daily to do so effectively. With the advent of a number of multimodal models, there is the potential to redu... | [] | Test |
19,719 | 16 | Title: NavGPT: Explicit Reasoning in Vision-and-Language Navigation with Large Language Models
Abstract: Trained with an unprecedented scale of data, large language models (LLMs) like ChatGPT and GPT-4 exhibit the emergence of significant reasoning abilities from model scaling. Such a trend underscored the potential of... | [
10624,
16194,
13700,
3333,
13510,
295,
33220,
28839,
16650,
9518,
26830,
5584,
39089,
45685,
3609,
634,
13564,
22077
] | Validation |
19,720 | 30 | Title: Dissociating language and thought in large language models: a cognitive perspective
Abstract: Today's large language models (LLMs) routinely generate coherent, grammatical and seemingly meaningful paragraphs of text. This achievement has led to speculation that these networks are -- or will soon become --"thinki... | [
34178,
37516,
44173,
3344,
6544,
9105,
10900,
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21401,
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16028,
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7470,
33455,
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38849,
9924,
16837,
7239,
39114,
25291,
2767,
1488,
23252,
2008,
36315,
41566,
3977... | Train |
19,721 | 27 | Title: Simultaneous Position-and-Stiffness Control of Underactuated Antagonistic Tendon-Driven Continuum Robots
Abstract: Continuum robots have gained widespread popularity due to their inherent compliance and flexibility, particularly their adjustable levels of stiffness for various application scenarios. Despite effo... | [
43935
] | Train |
19,722 | 30 | Title: Towards Reliable and Fluent Large Language Models: Incorporating Feedback Learning Loops in QA Systems
Abstract: Large language models (LLMs) have emerged as versatile tools in various daily applications. However, they are fraught with issues that undermine their utility and trustworthiness. These include the in... | [
22286,
889,
634,
15004,
17789
] | Validation |
19,723 | 21 | Title: ChatGPT: ascertaining the self-evident. The use of AI in generating human knowledge
Abstract: The fundamental principles, potential applications, and ethical concerns of ChatGPT are analyzed and discussed in this study. Since ChatGPT emerged, it has gained a rapidly growing popularity, with more than 600 million... | [] | Test |
19,724 | 24 | Title: Wireless Sensor Networks anomaly detection using Machine Learning: A Survey
Abstract: Wireless Sensor Networks (WSNs) have become increasingly valuable in various civil/military applications like industrial process control, civil engineering applications such as buildings structural strength monitoring, environm... | [] | Train |
19,725 | 8 | Title: Oscilloscope: Detecting BGP Hijacks in the Data Plane
Abstract: The lack of security of the Internet routing protocol (BGP) has allowed attackers to divert Internet traffic and consequently perpetrate service disruptions, monetary frauds, and even citizen surveillance for decades. State-of-the-art defenses rely ... | [] | Train |
19,726 | 16 | Title: Investigation of ensemble methods for the detection of deepfake face manipulations
Abstract: The recent wave of AI research has enabled a new brand of synthetic media, called deepfakes. Deepfakes have impressive photorealism, which has generated exciting new use cases but also raised serious threats to our incre... | [] | Test |
19,727 | 30 | Title: Progressive-Hint Prompting Improves Reasoning in Large Language Models
Abstract: The performance of Large Language Models (LLMs) in reasoning tasks depends heavily on prompt design, with Chain-of-Thought (CoT) and self-consistency being critical methods that enhance this ability. However, these methods do not fu... | [
13700,
25737,
34826,
42406,
8103,
1595,
2369,
43970,
15812,
33220,
31431,
30538,
43980,
44246,
25304,
7648,
15973,
27879,
30951,
37994,
9975,
1528
] | Train |
19,728 | 24 | Title: Adaptive Graph Convolutional Subspace Clustering
Abstract: Spectral-type subspace clustering algorithms have shown excellent performance in many subspace clustering applications. The existing spectral-type subspace clustering algorithms either focus on designing constraints for the reconstruction coefficient mat... | [
36370
] | Validation |
19,729 | 10 | Title: Finding an $\epsilon$-close Variation of Parameters in Bayesian Networks
Abstract: This paper addresses the $\epsilon$-close parameter tuning problem for Bayesian Networks (BNs): find a minimal $\epsilon$-close amendment of probability entries in a given set of (rows in) conditional probability tables that make ... | [] | Train |
19,730 | 30 | Title: Ashaar: Automatic Analysis and Generation of Arabic Poetry Using Deep Learning Approaches
Abstract: Poetry holds immense significance within the cultural and traditional fabric of any nation. It serves as a vehicle for poets to articulate their emotions, preserve customs, and convey the essence of their culture.... | [] | Train |
19,731 | 28 | Title: Rate-Adaptive Protograph MacKay-Neal Codes
Abstract: A class of rate-adaptive protograph MacKay-Neal (MN) codes is introduced and analyzed. The code construction employs an outer distribution matcher (DM) to adapt the rate of the scheme. The DM is coupled with an inner protograph-based low-density parity-check (... | [] | Train |
19,732 | 16 | Title: General Image-to-Image Translation with One-Shot Image Guidance
Abstract: Large-scale text-to-image models pre-trained on massive text-image pairs show excellent performance in image synthesis recently. However, image can provide more intuitive visual concepts than plain text. People may ask: how can we integrat... | [
34074
] | Validation |
19,733 | 24 | Title: Monte Carlo Neural Operator for Learning PDEs via Probabilistic Representation
Abstract: Neural operators, which use deep neural networks to approximate the solution mappings of partial differential equation (PDE) systems, are emerging as a new paradigm for PDE simulation. The neural operators could be trained i... | [] | Train |
19,734 | 24 | Title: Differentially Private Optimization for Smooth Nonconvex ERM
Abstract: We develop simple differentially private optimization algorithms that move along directions of (expected) descent to find an approximate second-order solution for nonconvex ERM. We use line search, mini-batching, and a two-phase strategy to i... | [
31296,
10947
] | Train |
19,735 | 27 | Title: Power Line Inspection Tasks With Multi-Aerial Robot Systems Via Signal Temporal Logic Specifications
Abstract: A framework for computing feasible and constrained trajectories for a fleet of quad-rotors leveraging on Signal Temporal Logic (STL) specifications for power line inspection tasks is proposed in this le... | [
4673,
4483,
27877,
38809,
15213,
23666,
24436,
2229,
28469,
17849,
45306,
2431
] | Train |
19,736 | 7 | Title: The Balanced Matrix Factorization for Computational Drug Repositioning
Abstract: —Computational drug repositioning aims to discover new uses of drugs that have been marketed. However, the existing models suffer from the following limitations. Firstly, in the real world, only a minority of diseases have definite t... | [] | Validation |
19,737 | 24 | Title: A Unified Framework for Discovering Discrete Symmetries
Abstract: We consider the problem of learning a function respecting a symmetry from among a class of symmetries. We develop a unified framework that enables symmetry discovery across a broad range of subgroups including locally symmetric, dihedral and cycli... | [
32244
] | Validation |
19,738 | 16 | Title: LFM-3D: Learnable Feature Matching Across Wide Baselines Using 3D Signals
Abstract: Finding localized correspondences across different images of the same object is crucial to understand its geometry. In recent years, this problem has seen remarkable progress with the advent of deep learning-based local image fea... | [
26848,
22996
] | Train |
19,739 | 36 | Title: Generative Adversarial Equilibrium Solvers
Abstract: We introduce the use of generative adversarial learning to compute equilibria in general game-theoretic settings, specifically the generalized Nash equilibrium (GNE) in pseudo-games, and its specific instantiation as the competitive equilibrium (CE) in Arrow-D... | [] | Train |
19,740 | 27 | Title: DeepIPCv2: LiDAR-powered Robust Environmental Perception and Navigational Control for Autonomous Vehicle
Abstract: We present DeepIPCv2, an autonomous driving model that perceives the environment using a LiDAR sensor for more robust drivability, especially when driving under poor illumination conditions where ev... | [] | Validation |
19,741 | 3 | Title: On the conformance of Android applications with children's data protection regulations and safeguarding guidelines
Abstract: With the rapid development of online technologies and the widespread usage of mobile phones among children, it is crucial to protect their online safety. Some studies reported that online ... | [] | Train |
19,742 | 3 | Title: The Overview of Privacy Labels and their Compatibility with Privacy Policies
Abstract: Privacy nutrition labels provide a way to understand an app's key data practices without reading the long and hard-to-read privacy policies. Recently, the app distribution platforms for iOS(Apple) and Android(Google) have impl... | [] | Train |
19,743 | 23 | Title: Interactive, Iterative, Tooled, Rule-Based Migration of Microsoft Access to Web Technologies
Abstract: In the context of a collaboration with Berger-Levrault, an IT company producing information systems, we are working on migrating Microsoft Access monolithic applications to the web front-end and microservices b... | [] | Validation |
19,744 | 24 | Title: Spatiotemporal Graph Neural Networks with Uncertainty Quantification for Traffic Incident Risk Prediction
Abstract: Predicting traffic incident risks at granular spatiotemporal levels is challenging. The datasets predominantly feature zero values, indicating no incidents, with sporadic high-risk values for sever... | [
25113,
38510
] | Train |
19,745 | 16 | Title: SoftMatch Distance: A Novel Distance for Weakly-Supervised Trend Change Detection in Bi-Temporal Images
Abstract: General change detection (GCD) and semantic change detection (SCD) are common methods for identifying changes and distinguishing object categories involved in those changes, respectively. However, th... | [] | Train |
19,746 | 24 | Title: Deep Reinforcement Learning from Hierarchical Weak Preference Feedback
Abstract: Reward design is a fundamental, yet challenging aspect of practical reinforcement learning (RL). For simple tasks, researchers typically handcraft the reward function, e.g., using a linear combination of several reward factors. Howe... | [
33490,
36719
] | Test |
19,747 | 10 | Title: TaskMatrix.AI: Completing Tasks by Connecting Foundation Models with Millions of APIs
Abstract: Artificial Intelligence (AI) has made incredible progress recently. On the one hand, advanced foundation models like ChatGPT can offer powerful conversation, in-context learning and code generation abilities on a broa... | [
7936,
34178,
27138,
22148,
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18059,
5522,
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14920,
18764,
31439,
33104,
9812,
11476,
19159,
1496,
11869,
19936,
1379,
17255... | Validation |
19,748 | 31 | Title: DynInt: Dynamic Interaction Modeling for Large-scale Click-Through Rate Prediction
Abstract: Learning feature interactions is the key to success for the large-scale CTR prediction in Ads ranking and recommender systems. In industry, deep neural network-based models are widely adopted for modeling such problems. ... | [
1759
] | Test |
19,749 | 16 | Title: Rehearsal-Free Domain Continual Face Anti-Spoofing: Generalize More and Forget Less
Abstract: Face Anti-Spoofing (FAS) is recently studied under the continual learning setting, where the FAS models are expected to evolve after encountering the data from new domains. However, existing methods need extra replay bu... | [
15078
] | Test |
19,750 | 16 | Title: The Devil in the Details: Simple and Effective Optical Flow Synthetic Data Generation
Abstract: Recent work on dense optical flow has shown significant progress, primarily in a supervised learning manner requiring a large amount of labeled data. Due to the expensiveness of obtaining large scale real-world data, ... | [] | Validation |
19,751 | 7 | Title: On the Simultaneous Solution of Structural Membranes on all Level Sets within a Bulk Domain
Abstract: nan | [] | Train |
19,752 | 24 | Title: Learning Optimal Admission Control in Partially Observable Queueing Networks
Abstract: We present an efficient reinforcement learning algorithm that learns the optimal admission control policy in a partially observable queueing network. Specifically, only the arrival and departure times from the network are obse... | [
9648
] | Train |
19,753 | 24 | Title: Promises and Pitfalls of the Linearized Laplace in Bayesian Optimization
Abstract: The linearized-Laplace approximation (LLA) has been shown to be effective and efficient in constructing Bayesian neural networks. It is theoretically compelling since it can be seen as a Gaussian process posterior with the mean fu... | [
24557,
13879
] | Validation |
19,754 | 24 | Title: Unsupervised Feature Selection to Identify Important ICD-10 Codes for Machine Learning: A Case Study on a Coronary Artery Disease Patient Cohort
Abstract: The use of International Classification of Diseases (ICD) codes in healthcare presents a challenge in selecting relevant codes as features for machine learnin... | [] | Train |
19,755 | 16 | Title: An Inherent Trade-Off in Noisy Neural Communication with Rank-Order Coding
Abstract: Rank-order coding, a form of temporal coding, has emerged as a promising scheme to explain the rapid ability of the mammalian brain. Owing to its speed as well as efficiency, rank-order coding is increasingly gaining interest in... | [] | Validation |
19,756 | 30 | Title: Simultaneous Machine Translation with Large Language Models
Abstract: Large language models (LLM) have demonstrated their abilities to solve various natural language processing tasks through dialogue-based interactions. For instance, research indicates that LLMs can achieve competitive performance in offline mac... | [
43641,
15358
] | Test |
19,757 | 16 | Title: DREAMWALKER: Mental Planning for Continuous Vision-Language Navigation
Abstract: VLN-CE is a recently released embodied task, where AI agents need to navigate a freely traversable environment to reach a distant target location, given language instructions. It poses great challenges due to the huge space of possi... | [
44726,
35005,
41753,
38330,
35421
] | Train |
19,758 | 10 | Title: Transformers in Healthcare: A Survey
Abstract: With Artificial Intelligence (AI) increasingly permeating various aspects of society, including healthcare, the adoption of the Transformers neural network architecture is rapidly changing many applications. Transformer is a type of deep learning architecture initia... | [
1923,
13700,
13029,
5862,
15301,
17028,
33220,
29396,
24308,
5815,
11929
] | Train |
19,759 | 16 | Title: All-pairs Consistency Learning for Weakly Supervised Semantic Segmentation
Abstract: In this work, we propose a new transformer-based regularization to better localize objects for Weakly supervised semantic segmentation (WSSS). In image-level WSSS, Class Activation Map (CAM) is adopted to generate object localiz... | [
13192
] | Train |
19,760 | 24 | Title: Clustering Human Mobility with Multiple Spaces
Abstract: Human mobility clustering is an important problem for understanding human mobility behaviors (e.g., work and school commutes). Existing methods typically contain two steps: choosing/learning a mobility representation and applying a clustering algorithm to ... | [] | Train |
19,761 | 16 | Title: Knowledge-Enhanced Hierarchical Information Correlation Learning for Multi-Modal Rumor Detection
Abstract: The explosive growth of rumors with text and images on social media platforms has drawn great attention. Existing studies have made significant contributions to cross-modal information interaction and fusio... | [] | Train |
19,762 | 3 | Title: Teaching Digital Manufacturing Experimenting Blended-Learning Models By Combining MOOC And On-site Workshops In FabLabs
Abstract: Teaching digital manufacturing at scale using MOOCs has opened opportunities for IMT, a network of French graduate engineering schools, to work closely with a community of learners an... | [] | Train |
19,763 | 27 | Title: A Comprehensive Introduction of Visual-Inertial Navigation
Abstract: In this article, a tutorial introduction to visual-inertial navigation(VIN) is presented. Visual and inertial perception are two complementary sensing modalities. Cameras and inertial measurement units (IMU) are the corresponding sensors for th... | [] | Train |
19,764 | 24 | Title: WikiCoder: Learning to Write Knowledge-Powered Code
Abstract: We tackle the problem of automatic generation of computer programs from a few pairs of input-output examples. The starting point of this work is the observation that in many applications a solution program must use external knowledge not present in th... | [] | Validation |
19,765 | 16 | Title: Reconstructing the somatotopic organization of the corticospinal tract remains a challenge for modern tractography methods
Abstract: The corticospinal tract (CST) is a critically important white matter fiber tract in the human brain that enables control of voluntary movements of the body. Diffusion MRI tractogra... | [] | Test |
19,766 | 24 | Title: Futures Quantitative Investment with Heterogeneous Continual Graph Neural Network
Abstract: It is a challenging problem to predict trends of futures prices with traditional econometric models as one needs to consider not only futures' historical data but also correlations among different futures. Spatial-tempora... | [] | Train |
19,767 | 24 | Title: Offline Reinforcement Learning with Imbalanced Datasets
Abstract: The prevalent use of benchmarks in current offline reinforcement learning (RL) research has led to a neglect of the imbalance of real-world dataset distributions in the development of models. The real-world offline RL dataset is often imbalanced o... | [] | Train |
19,768 | 6 | Title: Democratizing Chatbot Debugging: A Computational Framework for Evaluating and Explaining Inappropriate Chatbot Responses
Abstract: Evaluating and understanding the inappropriateness of chatbot behaviors can be challenging, particularly for chatbot designers without technical backgrounds. To democratize the debug... | [
13510
] | Test |
19,769 | 28 | Title: Fundamental Limits of Intelligent Reflecting Surface Aided Multiuser Broadcast Channel
Abstract: Intelligent reflecting surface (IRS) has recently received significant attention in wireless networks owing to its ability to smartly control the wireless propagation through passive reflection. Although prior works ... | [] | Validation |
19,770 | 36 | Title: Is Learning in Games Good for the Learners?
Abstract: We consider a number of questions related to tradeoffs between reward and regret in repeated gameplay between two agents. To facilitate this, we introduce a notion of {\it generalized equilibrium} which allows for asymmetric regret constraints, and yields pol... | [
19695
] | Train |
19,771 | 15 | Title: Hardware-Aware Automated Neural Minimization for Printed Multilayer Perceptrons
Abstract: The demand of many application domains for flexibility, stretchability, and porosity cannot be typically met by the silicon VLSI technologies. Printed Electronics (PE) has been introduced as a candidate solution that can sa... | [] | Train |
19,772 | 28 | Title: On The Stability of Approximate Message Passing with Independent Measurement Ensembles
Abstract: Approximate message passing (AMP) is a scalable, iterative approach to signal recovery. For structured random measurement ensembles, including independent and identically distributed (i.i.d.) Gaussian and rotationall... | [] | Train |
19,773 | 3 | Title: Queer In AI: A Case Study in Community-Led Participatory AI
Abstract: Queerness and queer people face an uncertain future in the face of ever more widely deployed and invasive artificial intelligence (AI). These technologies have caused numerous harms to queer people, including privacy violations, censoring and ... | [
22248,
12267,
30261,
37343
] | Validation |
19,774 | 38 | Title: Rank analysis of most cited publications, a new approach for research assessments
Abstract: Citation metrics are the best tools for research assessments. However, current metrics are misleading in research systems that pursue simultaneously different goals, such as the advance of science and incremental innovati... | [] | Train |
19,775 | 26 | Title: Radicalized by Thinness: Using a Model of Radicalization to Understand Pro-Anorexia Communities on Twitter
Abstract: The rise in eating disorders, a condition with serious health complications, has been linked to the proliferation of idealized body images on social media platforms. However, the relationship betw... | [] | Test |
19,776 | 6 | Title: Exploring Natural Language Processing Methods for Interactive Behaviour Modelling
Abstract: Analysing and modelling interactive behaviour is an important topic in human-computer interaction (HCI) and a key requirement for the development of intelligent interactive systems. Interactive behaviour has a sequential ... | [] | Train |
19,777 | 24 | Title: A Joint Time-frequency Domain Transformer for Multivariate Time Series Forecasting
Abstract: To enhance predicting performance while minimizing computational demands, this paper introduces a joint time-frequency domain Transformer (JTFT) for multivariate forecasting. The method exploits the sparsity of time seri... | [
16576
] | Test |
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