node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
values |
|---|---|---|---|---|
38,478 | 10 | Title: On the Potential of CLIP for Compositional Logical Reasoning
Abstract: In this paper we explore the possibility of using OpenAI's CLIP to perform logically coherent grounded visual reasoning. To that end, we formalize our terms and give a geometric analysis of how embeddings in CLIP's latent space would need to ... | [] | Train |
38,479 | 16 | Title: Meshes Meet Voxels: Abdominal Organ Segmentation via Diffeomorphic Deformations
Abstract: Abdominal multi-organ segmentation from CT and MRI is an essential prerequisite for surgical planning and computer-aided navigation systems. Three-dimensional numeric representations of abdominal shapes are further importan... | [] | Train |
38,480 | 16 | Title: Visual and Textual Prior Guided Mask Assemble for Few-Shot Segmentation and Beyond
Abstract: Few-shot segmentation (FSS) aims to segment the novel classes with a few annotated images. Due to CLIP's advantages of aligning visual and textual information, the integration of CLIP can enhance the generalization abili... | [
32664,
26271
] | Train |
38,481 | 25 | Title: Multi-Dimensional and Multi-Scale Modeling for Speech Separation Optimized by Discriminative Learning
Abstract: Transformer has shown advanced performance in speech separation, benefiting from its ability to capture global features. However, capturing local features and channel information of audio sequences in ... | [] | Train |
38,482 | 26 | Title: Generative Graph Neural Networks for Link Prediction
Abstract: Inferring missing links or detecting spurious ones based on observed graphs, known as link prediction, is a long-standing challenge in graph data analysis. With the recent advances in deep learning, graph neural networks have been used for link predi... | [] | Train |
38,483 | 31 | Title: ATEM: A Topic Evolution Model for the Detection of Emerging Topics in Scientific Archives
Abstract: This paper presents ATEM, a novel framework for studying topic evolution in scientific archives. ATEM is based on dynamic topic modeling and dynamic graph embedding techniques that explore the dynamics of content ... | [] | Validation |
38,484 | 20 | Title: The Parametrized Complexity of the Segment Number
Abstract: Given a straight-line drawing of a graph, a {\em segment} is a maximal set of edges that form a line segment. Given a planar graph $G$, the {\em segment number} of $G$ is the minimum number of segments that can be achieved by any planar straight-line dr... | [] | Train |
38,485 | 28 | Title: TopoSZ: Preserving Topology in Error-Bounded Lossy Compression
Abstract: Existing error-bounded lossy compression techniques control the pointwise error during compression to guarantee the integrity of the decompressed data. However, they typically do not explicitly preserve the topological features in data. Whe... | [] | Train |
38,486 | 6 | Title: The Facebook Algorithm's Active Role in Climate Advertisement Delivery
Abstract: Communication strongly influences attitudes on climate change. Within sponsored communication, high spend and high reach advertising dominates. In the advertising ecosystem we can distinguish actors with adversarial stances: organiz... | [
35434
] | Test |
38,487 | 27 | Title: Resilient Temporal Logic Planning in the Presence of Robot Failures
Abstract: Several task and motion planning algorithms have been proposed recently to design paths for mobile robot teams with collaborative high-level missions specified using formal languages, such as Linear Temporal Logic (LTL). However, the d... | [] | Validation |
38,488 | 27 | Title: Recognition of Heat-Induced Food State Changes by Time-Series Use of Vision-Language Model for Cooking Robot
Abstract: Cooking tasks are characterized by large changes in the state of the food, which is one of the major challenges in robot execution of cooking tasks. In particular, cooking using a stove to apply... | [
6487
] | Train |
38,489 | 16 | Title: Exploring Regions of Interest: Visualizing Histological Image Classification for Breast Cancer using Deep Learning
Abstract: Computer aided detection and diagnosis systems based on deep learning have shown promising performance in breast cancer detection. However, there are cases where the obtained results lack ... | [] | Validation |
38,490 | 30 | Title: Machine Learning Algorithms for Depression Detection and Their Comparison
Abstract: – Textual emotional intelligence is playing a ubiquitously important role in leveraging human emotions on social media platforms. Social media platforms are privileged with emotional contents and are leveraged for various purpose... | [] | Train |
38,491 | 27 | Title: Towards a Reduced Dependency Framework for Autonomous Unified Inspect-Explore Missions
Abstract: The task of establishing and maintaining situational awareness in an unknown environment is a critical step to fulfil in a mission related to the field of rescue robotics. Predominantly, the problem of visual inspect... | [] | Test |
38,492 | 16 | Title: WarpEM: Dynamic Time Warping for Accurate Catheter Registration in EM-guided Procedures
Abstract: Accurate catheter tracking is crucial during minimally invasive endovascular procedures (MIEP), and electromagnetic (EM) tracking is a widely used technology that serves this purpose. However, registration between p... | [] | Validation |
38,493 | 24 | Title: Structure-free Graph Condensation: From Large-scale Graphs to Condensed Graph-free Data
Abstract: Graph condensation, which reduces the size of a large-scale graph by synthesizing a small-scale condensed graph as its substitution, has immediate benefits for various graph learning tasks. However, existing graph c... | [
105,
44122,
5691
] | Train |
38,494 | 30 | Title: AsyncET: Asynchronous Learning for Knowledge Graph Entity Typing with Auxiliary Relations
Abstract: Knowledge graph entity typing (KGET) is a task to predict the missing entity types in knowledge graphs (KG). Previously, KG embedding (KGE) methods tried to solve the KGET task by introducing an auxiliary relation... | [] | Train |
38,495 | 27 | Title: Adaptive Value Decomposition with Greedy Marginal Contribution Computation for Cooperative Multi-Agent Reinforcement Learning
Abstract: Real-world cooperation often requires intensive coordination among agents simultaneously. This task has been extensively studied within the framework of cooperative multi-agent ... | [] | Validation |
38,496 | 28 | Title: Accelerating Graph Neural Networks via Edge Pruning for Power Allocation in Wireless Networks
Abstract: Neural Networks (GNNs) have recently emerged as a promising approach to tackling power allocation problems in wireless networks. Since unpaired transmitters and receivers are often spatially distant, the dista... | [
32568
] | Train |
38,497 | 30 | Title: A Weak Supervision Approach for Few-Shot Aspect Based Sentiment
Abstract: We explore how weak supervision on abundant unlabeled data can be leveraged to improve few-shot performance in aspect-based sentiment analysis (ABSA) tasks. We propose a pipeline approach to construct a noisy ABSA dataset, and we use it to... | [] | Train |
38,498 | 27 | Title: An enhanced motion planning approach by integrating driving heterogeneity and long-term trajectory prediction for automated driving systems
Abstract: Navigating automated driving systems (ADSs) through complex driving environments is difficult. Predicting the driving behavior of surrounding human-driven vehicles... | [] | Validation |
38,499 | 24 | Title: Memorization Capacity of Neural Networks with Conditional Computation
Abstract: Many empirical studies have demonstrated the performance benefits of conditional computation in neural networks, including reduced inference time and power consumption. We study the fundamental limits of neural conditional computatio... | [
3357
] | Train |
38,500 | 4 | Title: X-ray: Discovering DRAM Internal Structure and Error Characteristics by Issuing Memory Commands
Abstract: The demand for accurate information about the internal structure and characteristics of DRAM has been on the rise. Recent studies have explored the structure and characteristics of DRAM to improve processing... | [
37418,
5339
] | Validation |
38,501 | 24 | Title: Spatial-temporal Prompt Learning for Federated Weather Forecasting
Abstract: Federated weather forecasting is a promising collaborative learning framework for analyzing meteorological data across participants from different countries and regions, thus embodying a global-scale real-time weather data predictive an... | [
7715,
6359
] | Train |
38,502 | 27 | Title: Visibility-Constrained Control of Multirotor via Reference Governor
Abstract: For safe vision-based control applications, perception-related constraints have to be satisfied in addition to other state constraints. In this paper, we deal with the problem where a multirotor equipped with a camera needs to maintain... | [] | Test |
38,503 | 24 | Title: Tighter PAC-Bayes Bounds Through Coin-Betting
Abstract: We consider the problem of estimating the mean of a sequence of random elements $f(X_1, \theta)$ $, \ldots, $ $f(X_n, \theta)$ where $f$ is a fixed scalar function, $S=(X_1, \ldots, X_n)$ are independent random variables, and $\theta$ is a possibly $S$-depe... | [] | Train |
38,504 | 16 | Title: XMem++: Production-level Video Segmentation From Few Annotated Frames
Abstract: Despite advancements in user-guided video segmentation, extracting complex objects consistently for highly complex scenes is still a labor-intensive task, especially for production. It is not uncommon that a majority of frames need t... | [
11894
] | Test |
38,505 | 30 | Title: Bridging the KB-Text Gap: Leveraging Structured Knowledge-aware Pre-training for KBQA
Abstract: Knowledge Base Question Answering (KBQA) aims to answer natural language questions with factual information such as entities and relations in KBs. However, traditional Pre-trained Language Models (PLMs) are directly p... | [
28892,
19636,
29115
] | Test |
38,506 | 24 | Title: Exploring Antitrust and Platform Power in Generative AI
Abstract: The concentration of power in a few digital technology companies has become a subject of increasing interest in both academic and non-academic discussions. One of the most noteworthy contributions to the debate is Lina Khan's Amazon's Antitrust Pa... | [
24308
] | Train |
38,507 | 16 | Title: Raw Data Is All You Need: Virtual Axle Detector with Enhanced Receptive Field
Abstract: Rising maintenance costs of ageing infrastructure necessitate innovative monitoring techniques. This paper presents a new approach for axle detection, enabling real-time application of Bridge Weigh-In-Motion (BWIM) systems wi... | [] | Validation |
38,508 | 5 | Title: Massive Data-Centric Parallelism in the Chiplet Era
Abstract: Recent works have introduced task-based parallelization schemes to accelerate graph search and sparse data-structure traversal, where some solutions scale up to thousands of processing units (PUs) on a single chip. However parallelizing these memory-i... | [
18243
] | Train |
38,509 | 24 | Title: An Empirical Study of the Effectiveness of Using a Replay Buffer on Mode Discovery in GFlowNets
Abstract: Reinforcement Learning (RL) algorithms aim to learn an optimal policy by iteratively sampling actions to learn how to maximize the total expected return, $R(x)$. GFlowNets are a special class of algorithms d... | [] | Train |
38,510 | 24 | Title: Adaptive Modeling of Uncertainties for Traffic Forecasting
Abstract: Deep neural networks (DNNs) have emerged as a dominant approach for developing traffic forecasting models. These models are typically trained to minimize error on averaged test cases and produce a single-point prediction, such as a scalar value... | [
19744
] | Train |
38,511 | 10 | Title: Agent-Based Model: Simulating a Virus Expansion Based on the Acceptance of Containment Measures
Abstract: Compartmental epidemiological models categorize individuals based on their disease status, such as the SEIRD model (Susceptible-Exposed-Infected-Recovered-Dead). These models determine the parameters that in... | [] | Test |
38,512 | 24 | Title: Sensitivity-Aware Mixed-Precision Quantization and Width Optimization of Deep Neural Networks Through Cluster-Based Tree-Structured Parzen Estimation
Abstract: As the complexity and computational demands of deep learning models rise, the need for effective optimization methods for neural network designs becomes ... | [
13700
] | Train |
38,513 | 24 | Title: Evaluating Pedestrian Trajectory Prediction Methods for the Application in Autonomous Driving
Abstract: In this paper, the state of the art in the field of pedestrian trajectory prediction is evaluated alongside the constant velocity model (CVM) with respect to its applicability in autonomous vehicles. The evalu... | [
29686
] | Validation |
38,514 | 24 | Title: Offline Recommender System Evaluation under Unobserved Confounding
Abstract: Off-Policy Estimation (OPE) methods allow us to learn and evaluate decision-making policies from logged data. This makes them an attractive choice for the offline evaluation of recommender systems, and several recent works have reported... | [
8881,
2067
] | Train |
38,515 | 16 | Title: Knowledge Distillation Layer that Lets the Student Decide
Abstract: Typical technique in knowledge distillation (KD) is regularizing the learning of a limited capacity model (student) by pushing its responses to match a powerful model's (teacher). Albeit useful especially in the penultimate layer and beyond, its... | [] | Train |
38,516 | 16 | Title: Bokeh Rendering Based on Adaptive Depth Calibration Network
Abstract: Bokeh rendering is a popular and effective technique used in photography to create an aesthetically pleasing effect. It is widely used to blur the background and highlight the subject in the foreground, thereby drawing the viewer's attention t... | [] | Train |
38,517 | 13 | Title: Multi-scale Evolutionary Neural Architecture Search for Deep Spiking Neural Networks
Abstract: Spiking Neural Networks (SNNs) have received considerable attention not only for their superiority in energy efficiency with discrete signal processing but also for their natural suitability to integrate multi-scale bi... | [] | Train |
38,518 | 28 | Title: Target-Mounted Intelligent Reflecting Surface for Secure Wireless Sensing
Abstract: In this paper, we consider a challenging secure wireless sensing scenario where a legitimate radar station (LRS) intends to detect a target at unknown location in the presence of an unauthorized radar station (URS). We aim to enh... | [] | Train |
38,519 | 24 | Title: Can Euclidean Symmetry be Leveraged in Reinforcement Learning and Planning?
Abstract: In robotic tasks, changes in reference frames typically do not influence the underlying physical properties of the system, which has been known as invariance of physical laws.These changes, which preserve distance, encompass is... | [] | Test |
38,520 | 24 | Title: Jointly Exploring Client Drift and Catastrophic Forgetting in Dynamic Learning
Abstract: Federated and Continual Learning have emerged as potential paradigms for the robust and privacy-aware use of Deep Learning in dynamic environments. However, Client Drift and Catastrophic Forgetting are fundamental obstacles ... | [] | Test |
38,521 | 16 | Title: VCVW-3D: A Virtual Construction Vehicles and Workers Dataset with 3D Annotations
Abstract: Currently, object detection applications in construction are almost based on pure 2D data (both image and annotation are 2D-based), resulting in the developed artificial intelligence (AI) applications only applicable to so... | [] | Train |
38,522 | 23 | Title: Moving on from the Software Engineers' Gambit: An Approach to Support the Defense of Software Effort Estimates
Abstract: Pressure for higher productivity and faster delivery is increasingly pervading software organizations. This can lead software engineers to act like chess players playing a gambit—making sacrif... | [] | Train |
38,523 | 6 | Title: Improving of Robotic Virtual Agent's errors that are accepted by reaction and human's preference
Abstract: One way to improve the relationship between humans and anthropomorphic agents is to have humans empathize with the agents. In this study, we focused on a task between an agent and a human in which the agent... | [] | Validation |
38,524 | 10 | Title: Double A3C: Deep Reinforcement Learning on OpenAI Gym Games
Abstract: Reinforcement Learning (RL) is an area of machine learning figuring out how agents take actions in an unknown environment to maximize its rewards. Unlike classical Markov Decision Process (MDP) in which agent has full knowledge of its state, r... | [] | Train |
38,525 | 3 | Title: Fairness and Sequential Decision Making: Limits, Lessons, and Opportunities
Abstract: As automated decision making and decision assistance systems become common in everyday life, research on the prevention or mitigation of potential harms that arise from decisions made by these systems has proliferated. However,... | [] | Train |
38,526 | 8 | Title: Aggressive Internet-Wide Scanners: Network Impact and Longitudinal Characterization
Abstract: Aggressive network scanners, i.e., ones with immoderate and persistent behaviors, ubiquitously search the Internet to identify insecure and publicly accessible hosts. These scanners generally lie within two main categor... | [] | Test |
38,527 | 27 | Title: Puppeteer and Marionette: Learning Anticipatory Quadrupedal Locomotion Based on Interactions of a Central Pattern Generator and Supraspinal Drive
Abstract: Quadruped animal locomotion emerges from the interactions between the spinal central pattern generator (CPG), sensory feedback, and supraspinal drive signals... | [
6559
] | Train |
38,528 | 16 | Title: Transfer-Ensemble Learning based Deep Convolutional Neural Networks for Diabetic Retinopathy Classification
Abstract: This article aims to classify diabetic retinopathy (DR) disease into five different classes using an ensemble approach based on two popular pre-trained convolutional neural networks: VGG16 and In... | [] | Train |
38,529 | 16 | Title: Object-centric Learning with Cyclic Walks between Parts and Whole
Abstract: Learning object-centric representations from complex natural environments enables both humans and machines with reasoning abilities from low-level perceptual features. To capture compositional entities of the scene, we proposed cyclic wa... | [] | Validation |
38,530 | 16 | Title: Bandwidth-efficient Inference for Neural Image Compression
Abstract: With neural networks growing deeper and feature maps growing larger, limited communication bandwidth with external memory (or DRAM) and power constraints become a bottleneck in implementing network inference on mobile and edge devices. In this ... | [] | Train |
38,531 | 30 | Title: SI-LSTM: Speaker Hybrid Long-short Term Memory and Cross Modal Attention for Emotion Recognition in Conversation
Abstract: Emotion Recognition in Conversation~(ERC) across modalities is of vital importance for a variety of applications, including intelligent healthcare, artificial intelligence for conversation, ... | [] | Train |
38,532 | 16 | Title: Graph Convolution Based Efficient Re-Ranking for Visual Retrieval
Abstract: Visual retrieval tasks such as image retrieval and person re-identification (Re-ID) aim at effectively and thoroughly searching images with similar content or the same identity. After obtaining retrieved examples, re-ranking is a widely ... | [
43546,
4830
] | Validation |
38,533 | 6 | Title: Observations on LLMs for Telecom Domain: Capabilities and Limitations
Abstract: The landscape for building conversational interfaces (chatbots) has witnessed a paradigm shift with recent developments in generative Artificial Intelligence (AI) based Large Language Models (LLMs), such as ChatGPT by OpenAI (GPT3.5 ... | [
13700,
33220,
13510,
2347,
36179
] | Train |
38,534 | 16 | Title: Learning-based Spatial and Angular Information Separation for Light Field Compression
Abstract: Light fields are a type of image data that capture both spatial and angular scene information by recording light rays emitted by a scene from different orientations. In this context, spatial information is defined as ... | [] | Train |
38,535 | 16 | Title: Few-Shot Rotation-Invariant Aerial Image Semantic Segmentation
Abstract: Few-shot aerial image segmentation is a challenging task that involves precisely parsing objects in query aerial images with limited annotated support. Conventional matching methods without consideration of varying object orientations can f... | [] | Validation |
38,536 | 24 | Title: Deep COVID-19 Forecasting for Multiple States with Data Augmentation
Abstract: In this work, we propose a deep learning approach to forecasting state-level COVID-19 trends of weekly cumulative death in the United States (US) and incident cases in Germany. This approach includes a transformer model, an ensemble m... | [] | Train |
38,537 | 24 | Title: Adversarial Sample Detection Through Neural Network Transport Dynamics
Abstract: We propose a detector of adversarial samples that is based on the view of neural networks as discrete dynamic systems. The detector tells clean inputs from abnormal ones by comparing the discrete vector fields they follow through th... | [] | Train |
38,538 | 8 | Title: Exploring the Cookieverse: A Multi-Perspective Analysis of Web Cookies
Abstract: Web cookies have been the subject of many research studies over the last few years. However, most existing research does not consider multiple crucial perspectives that can influence the cookie landscape, such as the client's locati... | [
34102
] | Train |
38,539 | 16 | Title: Regression-free Blind Image Quality Assessment
Abstract: Regression-based blind image quality assessment (IQA) models are susceptible to biased training samples, leading to a biased estimation of model parameters. To mitigate this issue, we propose a regression-free framework for image quality evaluation, which ... | [] | Train |
38,540 | 30 | Title: Will Sentiment Analysis Need Subculture? A New Data Augmentation Approach
Abstract: The renowned proverb that"The pen is mightier than the sword"underscores the formidable influence wielded by text expressions in shaping sentiments. Indeed, well-crafted written can deeply resonate within cultures, conveying prof... | [
29965
] | Train |
38,541 | 24 | Title: MERLIN: Multi-agent offline and transfer learning for occupant-centric energy flexible operation of grid-interactive communities using smart meter data and CityLearn
Abstract: nan | [] | Train |
38,542 | 31 | Title: Feature Decomposition for Reducing Negative Transfer: A Novel Multi-task Learning Method for Recommender System
Abstract: We propose a novel multi-task learning method termed Feature Decomposition Network (FDN). The key idea of the proposed FDN is to reduce the phenomenon of feature redundancy by explicitly deco... | [] | Test |
38,543 | 23 | Title: A study on Prompt Design, Advantages and Limitations of ChatGPT for Deep Learning Program Repair
Abstract: ChatGPT has revolutionized many research and industrial fields. ChatGPT has shown great potential in software engineering to boost various traditional tasks such as program repair, code understanding, and c... | [
34336,
15047,
30026,
25227,
24749,
12367,
22097,
44246,
14007,
35289,
43930,
35580,
45342
] | Train |
38,544 | 30 | Title: Uncovering and Categorizing Social Biases in Text-to-SQL
Abstract: Large pre-trained language models are acknowledged to carry social bias towards different demographics, which can further amplify existing stereotypes in our society and cause even more harm. Text-to-SQL is an important task, models of which are ... | [
19114,
36030,
1895
] | Train |
38,545 | 24 | Title: SAILOR: Structural Augmentation Based Tail Node Representation Learning
Abstract: Graph Neural Networks (GNNs) have achieved state-of-the-art performance in representation learning for graphs recently. However, the effectiveness of GNNs, which capitalize on the key operation of message propagation, highly depend... | [] | Validation |
38,546 | 24 | Title: Data-Dependent Bounds for Online Portfolio Selection Without Lipschitzness and Smoothness
Abstract: This work introduces the first small-loss and gradual-variation regret bounds for online portfolio selection, marking the first instances of data-dependent bounds for online convex optimization with non-Lipschitz,... | [
28384
] | Train |
38,547 | 16 | Title: Performance-Aware Approximation of Global Channel Pruning for Multitask CNNs
Abstract: Global channel pruning (GCP) aims to remove a subset of channels (filters) across different layers from a deep model without hurting the performance. Previous works focus on either single task model pruning or simply adapting ... | [
31156
] | Test |
38,548 | 4 | Title: FedEdge AI-TC: A Semi-supervised Traffic Classification Method based on Trusted Federated Deep Learning for Mobile Edge Computing
Abstract: As a typical entity of MEC (Mobile Edge Computing), 5G CPE (Customer Premise Equipment)/HGU (Home Gateway Unit) has proven to be a promising alternative to traditional Smart... | [] | Validation |
38,549 | 26 | Title: A multi-platform collection of social media posts about the 2022 U.S. midterm elections
Abstract: Social media are utilized by millions of citizens to discuss important political issues. Politicians use these platforms to connect with the public and broadcast policy positions. Therefore, data from social media h... | [
29555
] | Train |
38,550 | 24 | Title: MKOR: Momentum-Enabled Kronecker-Factor-Based Optimizer Using Rank-1 Updates
Abstract: This work proposes a Momentum-Enabled Kronecker-Factor-Based Optimizer Using Rank-1 updates, called MKOR, that improves the training time and convergence properties of deep neural networks (DNNs). Second-order techniques, whil... | [] | Validation |
38,551 | 16 | Title: LayoutNUWA: Revealing the Hidden Layout Expertise of Large Language Models
Abstract: Graphic layout generation, a growing research field, plays a significant role in user engagement and information perception. Existing methods primarily treat layout generation as a numerical optimization task, focusing on quanti... | [
14592,
24096,
2211,
35556,
11077,
13510,
21477,
45160,
2633,
42597,
15950,
43641,
43478,
4569
] | Train |
38,552 | 16 | Title: Zero-shot Composed Text-Image Retrieval
Abstract: In this paper, we consider the problem of composed image retrieval (CIR), it aims to train a model that can fuse multi-modal information, e.g., text and images, to accurately retrieve images that match the query, extending the user's expression ability. We make t... | [
37861,
11113,
9198,
20535,
38135
] | Train |
38,553 | 24 | Title: A priori compression of convolutional neural networks for wave simulators
Abstract: Convolutional neural networks are now seeing widespread use in a variety of fields, including image classification, facial and object recognition, medical imaging analysis, and many more. In addition, there are applications such ... | [] | Train |
38,554 | 27 | Title: Granular Gym: High Performance Simulation for Robotic Tasks with Granular Materials
Abstract: Granular materials are of critical interest to many robotic tasks in planetary science, construction, and manufacturing. However, the dynamics of granular materials are complex and often computationally very expensive t... | [] | Validation |
38,555 | 24 | Title: Difference-Masking: Choosing What to Mask in Continued Pretraining
Abstract: Self-supervised learning (SSL) and the objective of masking-and-predicting in particular have led to promising SSL performance on a variety of downstream tasks. However, while most approaches randomly mask tokens, there is strong intuit... | [] | Train |
38,556 | 36 | Title: Active Inverse Learning in Stackelberg Trajectory Games
Abstract: Game-theoretic inverse learning is the problem of inferring the players' objectives from their actions. We formulate an inverse learning problem in a Stackelberg game between a leader and a follower, where each player's action is the trajectory of... | [
21615
] | Train |
38,557 | 6 | Title: Skip, Skip, Skip, Accept!!!: A Study on the Usability of Smartphone Manufacturer Provided Default Features and User Privacy
Abstract: Abstract Smartphone manufacturer provided default features (e.g., default location services, iCloud, Google Assistant, ad tracking) enhance the usability and extend the functional... | [
9697
] | Train |
38,558 | 24 | Title: Learning Provably Robust Estimators for Inverse Problems via Jittering
Abstract: Deep neural networks provide excellent performance for inverse problems such as denoising. However, neural networks can be sensitive to adversarial or worst-case perturbations. This raises the question of whether such networks can b... | [] | Train |
38,559 | 38 | Title: GraphLED: A graph-based approach to process and visualise linked engineering documents
Abstract: The architecture, engineering and construction (AEC) sector extensively uses documents supporting product and process development. As part of this, organisations should handle big data of hundreds, or even thousands,... | [] | Validation |
38,560 | 8 | Title: Decoding the Divide: Analyzing Disparities in Broadband Plans Offered by Major US ISPs
Abstract: Digital equity in Internet access is often measured along three axes: availability, affordability, and adoption. Most prior work focuses on availability; the other two aspects have received less attention. In this pa... | [] | Validation |
38,561 | 28 | Title: Improved upper bounds on the number of non-zero weights of cyclic codes
Abstract: Let C be an arbitrary simple-root cyclic code and let G be the subgroup of Aut(C) (the automorphism group of C) generated by the multiplier, the cyclic shift and the scalar multiplications. To the best of our knowledge, the subgrou... | [] | Train |
38,562 | 27 | Title: Clarifying the Half Full or Half Empty Question: Multimodal Container Classification
Abstract: Multimodal integration is a key component of allowing robots to perceive the world. Multimodality comes with multiple challenges that have to be considered, such as how to integrate and fuse the data. In this paper, we... | [
35493
] | Test |
38,563 | 27 | Title: Localization under consistent assumptions over dynamics
Abstract: Accurate maps are a prerequisite for virtually all autonomous vehicle tasks. Most state-of-the-art maps assume a static world, and therefore dynamic objects are filtered out of the measurements. However, this division ignores movable but non-movin... | [] | Train |
38,564 | 16 | Title: DAD++: Improved Data-free Test Time Adversarial Defense
Abstract: With the increasing deployment of deep neural networks in safety-critical applications such as self-driving cars, medical imaging, anomaly detection, etc., adversarial robustness has become a crucial concern in the reliability of these networks in... | [] | Validation |
38,565 | 24 | Title: LLM4TS: Two-Stage Fine-Tuning for Time-Series Forecasting with Pre-Trained LLMs
Abstract: In this work, we leverage pre-trained Large Language Models (LLMs) to enhance time-series forecasting. Mirroring the growing interest in unifying models for Natural Language Processing and Computer Vision, we envision creat... | [
44482,
42794,
15190
] | Validation |
38,566 | 17 | Title: TACHYON: Efficient Shared Memory Parallel Computation of Extremum Graphs
Abstract: The extremum graph is a succinct representation of the Morse decomposition of a scalar field. It has increasingly become a useful data structure that supports topological feature directed visualization of 2D / 3D scalar fields, an... | [] | Train |
38,567 | 8 | Title: RayNet: A Simulation Platform for Developing Reinforcement Learning-Driven Network Protocols
Abstract: Reinforcement Learning has gained significant momentum in the development of network protocols. However, learning-based protocols are still in their infancy, and substantial research is required to build deploy... | [] | Test |
38,568 | 39 | Title: Condorcet Domains of Degree at most Seven
Abstract: In this paper we give the first explicit enumeration of all maximal Condorcet domains on $n\leq 7$ alternatives. This has been accomplished by developing a new algorithm for constructing Condorcet domains, and an implementation of that algorithm which has been ... | [
28370,
766
] | Train |
38,569 | 24 | Title: Label-efficient Time Series Representation Learning: A Review
Abstract: The scarcity of labeled data is one of the main challenges of applying deep learning models on time series data in the real world. Therefore, several approaches, e.g., transfer learning, self-supervised learning, and semi-supervised learning... | [
21632,
29857,
15783
] | Test |
38,570 | 6 | Title: FocusFlow: Leveraging Focal Depth for Gaze Interaction in Virtual Reality
Abstract: Current gaze input methods for VR headsets predominantly utilize the gaze ray as a pointing cursor, often neglecting depth information in it. This study introduces FocusFlow, a novel gaze interaction technique that integrates foc... | [] | Validation |
38,571 | 10 | Title: Reflections from the Workshop on AI-Assisted Decision Making for Conservation
Abstract: In this white paper, we synthesize key points made during presentations and discussions from the AI-Assisted Decision Making for Conservation workshop, hosted by the Center for Research on Computation and Society at Harvard U... | [
3471
] | Test |
38,572 | 24 | Title: Deep Joint Source-Channel Coding with Iterative Source Error Correction
Abstract: In this paper, we propose an iterative source error correction (ISEC) decoding scheme for deep-learning-based joint source-channel coding (Deep JSCC). Given a noisy codeword received through the channel, we use a Deep JSCC encoder ... | [] | Test |
38,573 | 28 | Title: Adversarial Channels with O(1)-Bit Partial Feedback
Abstract: We consider point-to-point communication over $q$-ary adversarial channels with partial noiseless feedback. In this setting, a sender Alice transmits $n$ symbols from a $q$-ary alphabet over a noisy forward channel to a receiver Bob, while Bob sends f... | [] | Train |
38,574 | 30 | Title: ITALIC: An Italian Intent Classification Dataset
Abstract: Recent large-scale Spoken Language Understanding datasets focus predominantly on English and do not account for language-specific phenomena such as particular phonemes or words in different lects. We introduce ITALIC, the first large-scale speech dataset... | [
40065
] | Train |
38,575 | 30 | Title: Zero-shot Learning with Minimum Instruction to Extract Social Determinants and Family History from Clinical Notes using GPT Model
Abstract: Demographics, Social determinants of health, and family history documented in the unstructured text within the electronic health records are increasingly being studied to un... | [
27232,
36547,
15301,
9840,
38454,
42111
] | Train |
38,576 | 23 | Title: Reusing Deep Neural Network Models through Model Re-engineering
Abstract: Training deep neural network (DNN) models, which has become an important task in today's software development, is often costly in terms of computational resources and time. With the inspiration of software reuse, building DNN models throug... | [
31744,
40074
] | Validation |
38,577 | 16 | Title: Multi-Modal Mutual Attention and Iterative Interaction for Referring Image Segmentation
Abstract: We address the problem of referring image segmentation that aims to generate a mask for the object specified by a natural language expression. Many recent works utilize Transformer to extract features for the target... | [
5024,
38753,
29733,
25222,
34982,
28592,
41109,
11894
] | Train |
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