Split (1)

train · 203k rows

node_id int64 0 76.9k	label int64 0 39	text stringlengths 13 124k	neighbors listlengths 0 3.32k	mask stringclasses 4 values
32,178	28	Title: Reconstruction of Sequences Distorted by Two Insertions Abstract: Reconstruction codes are generalizations of error-correcting codes that can correct errors by a given number of noisy reads. The study of such codes was initiated by Levenshtein in 2001 and developed recently due to applications in modern storage ...	[]	Test
32,179	16	Title: Measured Albedo in the Wild: Filling the Gap in Intrinsics Evaluation Abstract: Intrinsic image decomposition and inverse rendering are long-standing problems in computer vision. To evaluate albedo recovery, most algorithms report their quantitative performance with a mean Weighted Human Disagreement Rate (WHDR)...	[]	Train
32,180	16	Title: Cross-Modality Proposal-guided Feature Mining for Unregistered RGB-Thermal Pedestrian Detection Abstract: RGB-Thermal (RGB-T) pedestrian detection aims to locate the pedestrians in RGB-T image pairs to exploit the complementation between the two modalities for improving detection robustness in extreme conditions...	[]	Train
32,181	24	Title: From Pseudorandomness to Multi-Group Fairness and Back Abstract: We identify and explore connections between the recent literature on multi-group fairness for prediction algorithms and the pseudorandomness notions of leakage-resilience and graph regularity. We frame our investigation using new, statistical dista...	[ 19937 ]	Test
32,182	3	Title: Visualizing Relation Between (De)Motivating Topics and Public Stance toward COVID-19 Vaccine Abstract: While social media plays a vital role in communication nowadays, misinformation and trolls can easily take over the conversation and steer public opinion on these platforms. We saw the effect of misinformation ...	[]	Train
32,183	30	Title: DeltaScore: Story Evaluation with Perturbations Abstract: Numerous evaluation metrics have been developed for natural language generation tasks but their effectiveness in evaluating stories is limited as they are not specifically tailored to assess intricate story aspects such as fluency and interestingness. In ...	[ 40192, 38208 ]	Validation
32,184	30	Title: Zhongjing: Enhancing the Chinese Medical Capabilities of Large Language Model through Expert Feedback and Real-world Multi-turn Dialogue Abstract: Recent advances in Large Language Models (LLMs) have achieved remarkable breakthroughs in understanding and responding to user intents. However, their performance lag...	[ 40192, 13345, 15075, 13700, 13029, 33220, 31218, 22772, 14133, 2102, 19671, 6328, 25786, 11614 ]	Train
32,185	30	Title: LLMDet: A Large Language Models Detection Tool Abstract: With the advancement of generative language models, the generated text has come remarkably close to high-quality human-authored text in terms of fluency and diversity. This calls for a highly practical detection tool that can identify the source of text, p...	[ 31362, 6531, 13700, 22476, 497, 38235, 7796, 29396, 44603 ]	Test
32,186	16	Title: LPMM: Intuitive Pose Control for Neural Talking-Head Model via Landmark-Parameter Morphable Model Abstract: While current talking head models are capable of generating photorealistic talking head videos, they provide limited pose controllability. Most methods require specific video sequences that should exactly ...	[]	Train
32,187	23	Title: Can An Old Fashioned Feature Extraction and A Light-weight Model Improve Vulnerability Type Identification Performance? Abstract: Recent advances in automated vulnerability detection have achieved potential results in helping developers determine vulnerable components. However, after detecting vulnerabilities, i...	[ 10381 ]	Train
32,188	5	Title: Eventually-Consistent Federated Scheduling for Data Center Workloads Abstract: Data center schedulers operate at unprecedented scales today to accommodate the growing demand for computing and storage power. The challenge that schedulers face is meeting the requirements of scheduling speeds despite the scale. To ...	[]	Train
32,189	5	Title: Hulk: Graph Neural Networks for Optimizing Regionally Distributed Computing Systems Abstract: Large deep learning models have shown great potential for delivering exceptional results in various applications. However, the training process can be incredibly challenging due to the models' vast parameter sizes, ofte...	[]	Validation
32,190	27	Title: SIM-Sync: From Certifiably Optimal Synchronization over the 3D Similarity Group to Scene Reconstruction with Learned Depth Abstract: This paper presents SIM-Sync, a certifiably optimal algorithm that estimates camera trajectory and 3D scene structure directly from multiview image keypoints. SIM-Sync fills the ga...	[]	Validation
32,191	30	Title: NoisywikiHow: A Benchmark for Learning with Real-world Noisy Labels in Natural Language Processing Abstract: Large-scale datasets in the real world inevitably involve label noise. Deep models can gradually overfit noisy labels and thus degrade model generalization. To mitigate the effects of label noise, learnin...	[]	Test
32,192	16	Title: Occlusion-Aware Detection and Re-ID Calibrated Network for Multi-Object Tracking Abstract: Multi-Object Tracking (MOT) is a crucial computer vision task that aims to predict the bounding boxes and identities of objects simultaneously. While state-of-the-art methods have made remarkable progress by jointly optimi...	[]	Train
32,193	24	Title: Fast Machine Unlearning Without Retraining Through Selective Synaptic Dampening Abstract: Machine unlearning, the ability for a machine learning model to forget, is becoming increasingly important to comply with data privacy regulations, as well as to remove harmful, manipulated, or outdated information. The key...	[]	Train
32,194	28	Title: Rate-Splitting and Sum-DoF for the K-User MISO Broadcast Channel with Mixed CSIT and Order-(K-1) Messages Abstract: In this paper, we propose a rate-splitting design and characterize the sum-degrees-of-freedom (DoF) for the K-user multiple-input-single-output (MISO) broadcast channel with mixed channel state inf...	[ 44259 ]	Validation
32,195	27	Title: Realistic Pedestrian Behaviour in the CARLA Simulator Using VR and Mocap Abstract: nan	[ 2766 ]	Train
32,196	16	Title: Rethinking Voxelization and Classification for 3D Object Detection Abstract: The main challenge in 3D object detection from LiDAR point clouds is achieving real-time performance without affecting the reliability of the network. In other words, the detecting network must be confident enough about its predictions....	[]	Train
32,197	24	Title: Improving Prediction Performance and Model Interpretability through Attention Mechanisms from Basic and Applied Research Perspectives Abstract: With the dramatic advances in deep learning technology, machine learning research is focusing on improving the interpretability of model predictions as well as predictio...	[]	Train
32,198	16	Title: Learning to Summarize Videos by Contrasting Clips Abstract: Video summarization aims at choosing parts of a video that narrate a story as close as possible to the original one. Most of the existing video summarization approaches focus on hand-crafted labels. As the number of videos grows exponentially, there eme...	[]	Train
32,199	3	Title: Applications and Societal Implications of Artificial Intelligence in Manufacturing: A Systematic Review Abstract: This paper undertakes a systematic review of relevant extant literature to consider the potential societal implications of the growth of AI in manufacturing. We analyze the extensive range of AI appl...	[]	Train
32,200	2	Title: Automated Polyhedral Abstraction Proving Abstract: nan	[ 32129, 12806 ]	Test
32,201	16	Title: “Let’s not Quote out of Context”: Unified Vision-Language Pretraining for Context Assisted Image Captioning Abstract: Well-formed context aware image captions and tags in enterprise content such as marketing material are critical to ensure their brand presence and content recall. Manual creation and updates to e...	[ 10624 ]	Train
32,202	16	Title: BS3D: Building-scale 3D Reconstruction from RGB-D Images Abstract: Various datasets have been proposed for simultaneous localization and mapping (SLAM) and related problems. Existing datasets often include small environments, have incomplete ground truth, or lack important sensor data, such as depth and infrared...	[]	Train
32,203	4	Title: SecureFalcon: The Next Cyber Reasoning System for Cyber Security Abstract: Software vulnerabilities leading to various detriments such as crashes, data loss, and security breaches, significantly hinder the quality, affecting the market adoption of software applications and systems. Although traditional methods s...	[ 7936, 13700, 33220, 7942, 651, 109, 24749, 35062 ]	Train
32,204	10	Title: Integrating Generative Artificial Intelligence in Intelligent Vehicle Systems Abstract: This paper aims to serve as a comprehensive guide for researchers and practitioners, offering insights into the current state, potential applications, and future research directions for generative artificial intelligence and ...	[ 7936, 21778 ]	Validation
32,205	24	Title: Dropout Attacks Abstract: Dropout is a common operator in deep learning, aiming to prevent overfitting by randomly dropping neurons during training. This paper introduces a new family of poisoning attacks against neural networks named DROPOUTATTACK. DROPOUTATTACK attacks the dropout operator by manipulating the ...	[]	Validation
32,206	30	Title: Measuring Inductive Biases of In-Context Learning with Underspecified Demonstrations Abstract: In-context learning (ICL) is an important paradigm for adapting large language models (LLMs) to new tasks, but the generalization behavior of ICL remains poorly understood. We investigate the inductive biases of ICL fr...	[ 43906, 25192, 26792, 3795, 1654, 37179, 43327 ]	Validation
32,207	16	Title: Spyker: High-performance Library for Spiking Deep Neural Networks Abstract: Spiking neural networks (SNNs) have been recently brought to light due to their promising capabilities. SNNs simulate the brain with higher biological plausibility compared to previous generations of neural networks. Learning with fewer ...	[]	Train
32,208	24	Title: A Deep Learning Approach for Overall Survival Prediction in Lung Cancer with Missing Values Abstract: One of the most challenging fields where Artificial Intelligence (AI) can be applied is lung cancer research, specifically non-small cell lung cancer (NSCLC). In particular, overall survival (OS), the time betwe...	[ 7351 ]	Validation
32,209	16	Title: Breaking Down the Task: A Unit-Grained Hybrid Training Framework for Vision and Language Decision Making Abstract: Vision language decision making (VLDM) is a challenging multimodal task. The agent have to understand complex human instructions and complete compositional tasks involving environment navigation and...	[]	Train
32,210	24	Title: Transformers Meet Directed Graphs Abstract: Transformers were originally proposed as a sequence-to-sequence model for text but have become vital for a wide range of modalities, including images, audio, video, and undirected graphs. However, transformers for directed graphs are a surprisingly underexplored topic,...	[ 9649, 11323, 44836, 27630 ]	Train
32,211	31	Title: Testing different Log Bases For Vector Model Weighting Technique Abstract: Information retrieval systems retrieves relevant documents based on a query submitted by the user. The documents are initially indexed and the words in the documents are assigned weights using a weighting technique called TFIDF which is t...	[]	Train
32,212	10	Title: Generative Logic with Time: Beyond Logical Consistency and Statistical Possibility Abstract: This paper gives a simple theory of inference to logically reason symbolic knowledge fully from data over time. We take a Bayesian approach to model how data causes symbolic knowledge. Probabilistic reasoning with symbol...	[]	Train
32,213	30	Title: In-Context Retrieval-Augmented Language Models Abstract: Retrieval-Augmented Language Modeling (RALM) methods, which condition a language model (LM) on relevant documents from a grounding corpus during generation, were shown to significantly improve language modeling performance. In addition, they can mitigate t...	[ 42752, 34563, 13700, 18572, 397, 43668, 27669, 43925, 10903, 32287, 44323, 31397, 35375, 41392, 30641, 15410, 43060, 43327, 39873, 28878, 42574, 39377, 11476, 9429, 32856, 21593, 36709, 7661, 17777, 38900, 24311, 10363, 41724 ]	Test
32,214	10	Title: Building Safe and Reliable AI Systems for Safety Critical Tasks with Vision-Language Processing Abstract: nan	[]	Test
32,215	16	Title: Retrieval-Enhanced Visual Prompt Learning for Few-shot Classification Abstract: Prompt learning has become a popular approach for adapting large vision-language models, such as CLIP, to downstream tasks. Typically, prompt learning relies on a fixed prompt token or an input-conditional token to fit a small amount...	[ 29521 ]	Train
32,216	24	Title: Cost-effective On-device Continual Learning over Memory Hierarchy with Miro Abstract: Continual learning (CL) trains NN models incrementally from a continuous stream of tasks. To remember previously learned knowledge, prior studies store old samples over a memory hierarchy and replay them when new tasks arrive. ...	[ 41032, 20340 ]	Train
32,217	24	Title: GTV: Generating Tabular Data via Vertical Federated Learning Abstract: Generative Adversarial Networks (GANs) have achieved state-of-the-art results in tabular data synthesis, under the presumption of direct accessible training data. Vertical Federated Learning (VFL) is a paradigm which allows to distributedly t...	[]	Train
32,218	7	Title: Scientific modeling of optical 3D measuring devices based on GPU-accelerated ray tracing using the NVIDIA OptiX engine Abstract: Scientific optical 3D modeling requires the possibility to implement highly flexible and customizable mathematical models as well as high computing power. However, established ray trac...	[]	Test
32,219	24	Title: Wasserstein Distributionally Robust Policy Evaluation and Learning for Contextual Bandits Abstract: Off-policy evaluation and learning are concerned with assessing a given policy and learning an optimal policy from offline data without direct interaction with the environment. Often, the environment in which the ...	[ 30807 ]	Test
32,220	24	Title: Efficient Learning of High Level Plans from Play Abstract: Real-world robotic manipulation tasks remain an elusive challenge, since they involve both fine-grained environment interaction, as well as the ability to plan for long-horizon goals. Although deep reinforcement learning (RL) methods have shown encouragi...	[]	Test
32,221	16	Title: Revisiting Pre-training in Audio-Visual Learning Abstract: Pre-training technique has gained tremendous success in enhancing model performance on various tasks, but found to perform worse than training from scratch in some uni-modal situations. This inspires us to think: are the pre-trained models always effecti...	[]	Test
32,222	16	Title: Learning Heavily-Degraded Prior for Underwater Object Detection Abstract: Underwater object detection suffers from low detection performance because the distance and wavelength dependent imaging process yield evident image quality degradations such as haze-like effects, low visibility, and color distortions. The...	[ 30680 ]	Train
32,223	16	Title: $\mathcal {S}^{2}$Net: Accurate Panorama Depth Estimation on Spherical Surface Abstract: Monocular depth estimation is an ambiguous problem, thus global structural cues play an important role in current data-driven single-view depth estimation methods. Panorama images capture the complete spatial information of ...	[]	Test
32,224	30	Title: NoRefER: a Referenceless Quality Metric for Automatic Speech Recognition via Semi-Supervised Language Model Fine-Tuning with Contrastive Learning Abstract: This paper introduces NoRefER, a novel referenceless quality metric for automatic speech recognition (ASR) systems. Traditional reference-based metrics for e...	[]	Train
32,225	30	Title: Stanford MLab at SemEval-2023 Task 10: Exploring GloVe- and Transformer-Based Methods for the Explainable Detection of Online Sexism Abstract: In this paper, we discuss the methods we applied at SemEval-2023 Task 10: Towards the Explainable Detection of Online Sexism. Given an input text, we perform three classi...	[]	Train
32,226	10	Title: A Novel Point-based Algorithm for Multi-agent Control Using the Common Information Approach Abstract: The Common Information (CI) approach provides a systematic way to transform a multi-agent stochastic control problem to a single-agent partially observed Markov decision problem (POMDP) called the coordinator's ...	[]	Train
32,227	30	Title: The Impact of Positional Encoding on Length Generalization in Transformers Abstract: Length generalization, the ability to generalize from small training context sizes to larger ones, is a critical challenge in the development of Transformer-based language models. Positional encoding (PE) has been identified as ...	[ 13700, 25892, 13063, 40719, 11633, 10163, 2013, 9470 ]	Train
32,228	8	Title: 3D UAV Trajectory Design for Fair and Energy-Efficient Communication: A Deep Reinforcement Learning Technique Abstract: In different situations, like disaster communication and network connectivity for rural locations, unmanned aerial vehicles (UAVs) could indeed be utilized as airborne base stations to improve ...	[]	Train
32,229	25	Title: emoDARTS : Enhancing Speech Emotion Recognition Through Differentiable Architecture Search Abstract: Speech Emotion Recognition (SER) is a critical enabler of emotion-aware communication in human-computer interactions. Recent advancements in Deep Learning (DL) have substantially enhanced the performance of SER m...	[]	Train
32,230	24	Title: A Novel Fuzzy Bi-Clustering Algorithm with AFS for Identification of Co-Regulated Genes Abstract: The identification of co-regulated genes and their transcription-factor binding sites (TFBS) are the key steps toward understanding transcription regulation. In addition to effective laboratory assays, various bi-cl...	[]	Test
32,231	4	Title: ESAFL: Efficient Secure Additively Homomorphic Encryption for Cross-Silo Federated Learning Abstract: Cross-silo federated learning (FL) enables multiple clients to collaboratively train a machine learning model without sharing training data, but privacy in FL remains a major challenge. Techniques using homomorp...	[]	Test
32,232	16	Title: Evaluating Post-hoc Interpretability with Intrinsic Interpretability Abstract: Despite Convolutional Neural Networks having reached human-level performance in some medical tasks, their clinical use has been hindered by their lack of interpretability. Two major interpretability strategies have been proposed to ta...	[ 40066 ]	Test
32,233	28	Title: Full Duplex Holographic MIMO for Near-Field Integrated Sensing and Communications Abstract: This paper presents an in-band Full Duplex (FD) integrated sensing and communications system comprising a holographic Multiple-Input Multiple-Output (MIMO) base station, which is capable to simultaneously communicate with...	[ 32043 ]	Train
32,234	16	Title: RayMVSNet++: Learning Ray-based 1D Implicit Fields for Accurate Multi-View Stereo Abstract: Learning-based multi-view stereo (MVS) has by far centered around 3D convolution on cost volumes. Due to the high computation and memory consumption of 3D CNN, the resolution of output depth is often considerably limited....	[ 22480, 13119 ]	Validation
32,235	28	Title: Imperfect CSI: A Key Factor of Uncertainty to Over-the-Air Federated Learning Abstract: Over-the-air computation (AirComp) has recently been identified as a prominent technique to enhance communication efficiency of wireless federated learning (FL). This letter investigates the impact of channel state informatio...	[]	Train
32,236	8	Title: Predicting Wireless Channel Quality by Means of Moving Averages and Regression Models Abstract: The ability to reliably predict the future quality of a wireless channel, as seen by the media access control layer, is a key enabler to improve performance of future industrial networks that do not rely on wires. Kno...	[]	Test
32,237	27	Title: Leveraging Symbolic Algebra Systems to Simulate Contact Dynamics in Rigid Body Systems Abstract: Collision detection plays a key role in the simulation of interacting rigid bodies. However, owing to its computational complexity current methods typically prioritize either maximizing processing speed or fidelity t...	[]	Train
32,238	16	Title: HDTR-Net: A Real-Time High-Definition Teeth Restoration Network for Arbitrary Talking Face Generation Methods Abstract: Talking Face Generation (TFG) aims to reconstruct facial movements to achieve high natural lip movements from audio and facial features that are under potential connections. Existing TFG method...	[ 16369, 34851 ]	Train
32,239	10	Title: An Appraisal-Based Chain-Of-Emotion Architecture for Affective Language Model Game Agents Abstract: The development of believable, natural, and interactive digital artificial agents is a field of growing interest. Theoretical uncertainties and technical barriers present considerable challenges to the field, part...	[ 32921, 16556, 43566, 4071 ]	Train
32,240	24	Title: PFSL: Personalized & Fair Split Learning with Data & Label Privacy for thin clients Abstract: The traditional framework of federated learning (FL) requires each client to re-train their models in every iteration, making it infeasible for resource-constrained mobile devices to train deep-learning (DL) models. Spl...	[ 1053 ]	Test
32,241	16	Title: Variations of Squeeze and Excitation networks Abstract: Convolutional neural networks learns spatial features and are heavily interlinked within kernels. The SE module have broken the traditional route of neural networks passing the entire result to next layer. Instead SE only passes important features to be lea...	[]	Train
32,242	11	Title: Fair Healthcare Rationing to Maximize Dynamic Utilities Abstract: Allocation of scarce healthcare resources under limited logistic and infrastructural facilities is a major issue in the modern society. We consider the problem of allocation of healthcare resources like vaccines to people or hospital beds to patie...	[]	Train
32,243	27	Title: UVIO: An UWB-Aided Visual-Inertial Odometry Framework with Bias-Compensated Anchors Initialization Abstract: This paper introduces UVIO, a multi-sensor framework that leverages Ultra Wide Band (UWB) technology and Visual-Inertial Odometry (VIO) to provide robust and low-drift localization. In order to include ra...	[]	Test
32,244	24	Title: Neural Discovery of Permutation Subgroups Abstract: We consider the problem of discovering subgroup $H$ of permutation group $S_{n}$. Unlike the traditional $H$-invariant networks wherein $H$ is assumed to be known, we present a method to discover the underlying subgroup, given that it satisfies certain conditio...	[ 19737 ]	Train
32,245	6	Title: Enabling the Evaluation of Driver Physiology Via Vehicle Dynamics Abstract: Driving is a daily routine for many individuals across the globe. This paper presents the configuration and methodologies used to transform a vehicle into a connected ecosystem capable of assessing driver physiology. We integrated an arr...	[]	Validation
32,246	28	Title: Private Read-Update-Write with Controllable Information Leakage for Storage-Efficient Federated Learning with Top r Sparsification Abstract: In federated learning (FL), a machine learning (ML) model is collectively trained by a large number of users, using their private data in their local devices. With top $r$ ...	[ 31889, 25606 ]	Train
32,247	16	Title: Planting a SEED of Vision in Large Language Model Abstract: We present SEED, an elaborate image tokenizer that empowers Large Language Models (LLMs) with the emergent ability to SEE and Draw at the same time. Research on image tokenizers has previously reached an impasse, as frameworks employing quantized visual...	[ 10624, 11745, 37987, 13700, 969, 16682, 38858, 16878, 41104, 5969, 27282, 41146, 13564 ]	Train
32,248	5	Title: Evaluating FAIR Digital Object and Linked Data as distributed object systems Abstract: FAIR Digital Object (FDO) is an emerging concept that is highlighted by European Open Science Cloud (EOSC) as a potential candidate for building a ecosystem of machine-actionable research outputs. In this work we systematicall...	[ 10325 ]	Train
32,249	24	Title: Modular Deep Learning Abstract: Transfer learning has recently become the dominant paradigm of machine learning. Pre-trained models fine-tuned for downstream tasks achieve better performance with fewer labelled examples. Nonetheless, it remains unclear how to develop models that specialise towards multiple tasks...	[ 33760, 44482, 24964, 10756, 20996, 43099, 31158, 36343, 44312, 29755 ]	Train
32,250	3	Title: A Model for Integrating Generative AI into Course Content Development Abstract: As Generative AI (GenAI) models continue to gain prominence, a new frontier is emerging in the field of computer science education. Results from initial anonymous surveys reveal that nearly half (48.5%) of our students now turn to Ge...	[ 100, 4937, 6410, 43566, 39164, 28607 ]	Train
32,251	24	Title: Differentiable Forward Projector for X-ray Computed Tomography Abstract: Data-driven deep learning has been successfully applied to various computed tomographic reconstruction problems. The deep inference models may outperform existing analytical and iterative algorithms, especially in ill-posed CT reconstructio...	[]	Train
32,252	30	Title: Controlled Text Generation with Natural Language Instructions Abstract: Large language models generate fluent texts and can follow natural language instructions to solve a wide range of tasks without task-specific training. Nevertheless, it is notoriously difficult to control their generation to satisfy the vari...	[ 13700, 26186, 3088, 46097, 44434, 4340, 12445 ]	Train
32,253	8	Title: 5Greplay: a 5G Network Traffic Fuzzer - Application to Attack Injection Abstract: The fifth generation of mobile broadband is more than just an evolution to provide more mobile bandwidth, massive machine-type communications, and ultra-reliable and low-latency communications. It relies on a complex, dynamic and h...	[ 34245, 21995, 39741 ]	Train
32,254	16	Title: AVFace: Towards Detailed Audio-Visual 4D Face Reconstruction Abstract: In this work, we present a multimodal solution to the problem of 4D face reconstruction from monocular videos. 3D face reconstruction from 2D images is an under-constrained problem due to the ambiguity of depth. State-of-the-art methods try t...	[]	Validation
32,255	23	Title: Verified Scalable Parallel Computing with Why3 Abstract: BSML is a pure functional library for the multi-paradigm language OCaml. BSML embodies the principles of the Bulk Synchronous Parallel (BSP) model, a model of scalable parallel computing. We propose a formalization of BSML primitives with WhyML, the specif...	[]	Validation
32,256	16	Title: EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge: Mixed Sequences Prediction Abstract: This report presents the technical details of our approach for the EPIC-Kitchens-100 Unsupervised Domain Adaptation (UDA) Challenge in Action Recognition. Our approach is based on the idea that the order in which act...	[]	Train
32,257	27	Title: 3D Skeletonization of Complex Grapevines for Robotic Pruning Abstract: Robotic pruning of dormant grapevines is an area of active research in order to promote vine balance and grape quality, but so far robotic efforts have largely focused on planar, simplified vines not representative of commercial vineyards. Th...	[]	Train
32,258	8	Title: Towards Optimal Serverless Function Scaling in Edge Computing Network Abstract: Serverless computing has emerged as a new execution model which gained a lot of attention in cloud computing thanks to the latest advances in containerization technologies. Recently, serverless has been adopted at the edge, where it ...	[]	Train
32,259	24	Title: On the Minimax Regret in Online Ranking with Top-k Feedback Abstract: In online ranking, a learning algorithm sequentially ranks a set of items and receives feedback on its ranking in the form of relevance scores. Since obtaining relevance scores typically involves human annotation, it is of great interest to co...	[]	Test
32,260	25	Title: The CHiME-7 UDASE task: Unsupervised domain adaptation for conversational speech enhancement Abstract: Supervised speech enhancement models are trained using artificially generated mixtures of clean speech and noise signals, which may not match real-world recording conditions at test time. This mismatch can lead...	[]	Test
32,261	16	Title: A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondence Abstract: Text-to-image diffusion models have made significant advances in generating and editing high-quality images. As a result, numerous approaches have explored the ability of diffusion model features to understa...	[ 25666, 4643, 43394, 37254, 3015, 28647, 34184, 8234, 21578, 38739, 8308, 27508, 34009, 34074, 4220 ]	Train
32,262	16	Title: SNAP: Self-Supervised Neural Maps for Visual Positioning and Semantic Understanding Abstract: Semantic 2D maps are commonly used by humans and machines for navigation purposes, whether it's walking or driving. However, these maps have limitations: they lack detail, often contain inaccuracies, and are difficult t...	[ 18218, 4643 ]	Validation
32,263	30	Title: Rewarding Chatbots for Real-World Engagement with Millions of Users Abstract: The emergence of pretrained large language models has led to the deployment of a range of social chatbots for chitchat. Although these chatbots demonstrate language ability and fluency, they are not guaranteed to be engaging and can st...	[ 44537, 17876, 10716, 21483 ]	Train
32,264	16	Title: 3rd Place Solution for PVUW2023 VSS Track: A Large Model for Semantic Segmentation on VSPW Abstract: In this paper, we introduce 3rd place solution for PVUW2023 VSS track. Semantic segmentation is a fundamental task in computer vision with numerous real-world applications. We have explored various image-level vi...	[]	Train
32,265	16	Title: Parameters, Properties, and Process: Conditional Neural Generation of Realistic SEM Imagery Toward ML-Assisted Advanced Manufacturing Abstract: nan	[]	Train
32,266	30	Title: GlyphDiffusion: Text Generation as Image Generation Abstract: Diffusion models have become a new generative paradigm for text generation. Considering the discrete categorical nature of text, in this paper, we propose GlyphDiffusion, a novel diffusion approach for text generation via text-guided image generation....	[ 34351 ]	Train
32,267	8	Title: A Tutorial on Resilience in Smart Grids Abstract: A key quality of any kind of system is its ability to deliver its respective service correctly. Often the unavailability of commercial systems may lead to lost revenue, which are minor compared to what may be at stake when critical infrastructures fail. A failure...	[]	Train
32,268	20	Title: Maximum overlap area of a convex polyhedron and a convex polygon under translation Abstract: Let $P$ be a convex polyhedron and $Q$ be a convex polygon with $n$ vertices in total in three-dimensional space. We present a deterministic algorithm that finds a translation vector $v \in \mathbb{R}^3$ maximizing the o...	[ 25731 ]	Test
32,269	27	Title: The Hierarchical Newton’s Method for Numerically Stable Prioritized Dynamic Control Abstract: This work links optimization approaches from hierarchical least-squares programming to instantaneous prioritized whole-body robot control. Concretely, we formulate the hierarchical Newton’s method which solves prioritiz...	[ 3832, 774 ]	Validation
32,270	22	Title: Polymorphic Reachability Types: Tracking Freshness, Aliasing, and Separation in Higher-Order Generic Programs Abstract: Reachability types are a recent proposal that has shown promise in scaling to higher-order but monomorphic settings, tracking aliasing and separation on top of a substrate inspired by separatio...	[ 26011 ]	Test
32,271	24	Title: Co-design Hardware and Algorithm for Vector Search Abstract: Vector search has emerged as the foundation for large-scale information retrieval and machine learning systems, with search engines like Google and Bing processing tens of thousands of queries per second on petabyte-scale document datasets by evaluatin...	[ 17483 ]	Test
32,272	16	Title: Diversity is Definitely Needed: Improving Model-Agnostic Zero-shot Classification via Stable Diffusion Abstract: In this work, we investigate the problem of Model-Agnostic Zero-Shot Classification (MA-ZSC), which refers to training non-specific classification architectures (downstream models) to classify real im...	[ 14213, 45703, 6957, 20562, 13660, 12764 ]	Train
32,273	24	Title: Scalable Optimal Multiway-Split Decision Trees with Constraints Abstract: There has been a surge of interest in learning optimal decision trees using mixed-integer programs (MIP) in recent years, as heuristic-based methods do not guarantee optimality and find it challenging to incorporate constraints that are cr...	[ 38890 ]	Train
32,274	24	Title: Constrained Empirical Risk Minimization: Theory and Practice Abstract: Deep Neural Networks (DNNs) are widely used for their ability to effectively approximate large classes of functions. This flexibility, however, makes the strict enforcement of constraints on DNNs an open problem. Here we present a framework t...	[]	Train
32,275	27	Title: Actuator Trajectory Planning for UAVs with Overhead Manipulator using Reinforcement Learning Abstract: In this paper, we investigate the operation of an aerial manipulator system, namely an Unmanned Aerial Vehicle (UAV) equipped with a controllable arm with two degrees of freedom to carry out actuation tasks on ...	[]	Train
32,276	30	Title: Where’s the Point? Self-Supervised Multilingual Punctuation-Agnostic Sentence Segmentation Abstract: Many NLP pipelines split text into sentences as one of the crucial preprocessing steps. Prior sentence segmentation tools either rely on punctuation or require a considerable amount of sentence-segmented training...	[ 17890 ]	Validation
32,277	24	Title: TS-MoCo: Time-Series Momentum Contrast for Self-Supervised Physiological Representation Learning Abstract: Limited availability of labeled physiological data often prohibits the use of powerful supervised deep learning models in the biomedical machine intelligence domain. We approach this problem and propose a n...	[]	Train

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