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31,978
24
Title: Efficiently Learning the Graph for Semi-supervised Learning Abstract: Computational efficiency is a major bottleneck in using classic graph-based approaches for semi-supervised learning on datasets with a large number of unlabeled examples. Known techniques to improve efficiency typically involve an approximatio...
[]
Validation
31,979
8
Title: Modified Ring-Oscillator Physical Unclonable Function (RO-PUF) based PRBS Generation as a Device Signature in Distributed Brain Implants Abstract: In this paper, we propose and evaluate a method of generating low-cost device signatures for distributed wireless brain implants, using a Pseudo-Random Binary Sequenc...
[]
Test
31,980
31
Title: Practical Cross-system Shilling Attacks with Limited Access to Data Abstract: In shilling attacks, an adversarial party injects a few fake user profiles into a Recommender System (RS) so that the target item can be promoted or demoted. Although much effort has been devoted to developing shilling attack methods, ...
[ 25639 ]
Train
31,981
24
Title: Non-Parametric Learning of Stochastic Differential Equations with Fast Rates of Convergence Abstract: We propose a novel non-parametric learning paradigm for the identification of drift and diffusion coefficients of non-linear stochastic differential equations, which relies upon discrete-time observations of the...
[]
Train
31,982
24
Title: Emergent Communication in Multi-Agent Reinforcement Learning for Future Wireless Networks Abstract: In different wireless network scenarios, multiple network entities need to cooperate in order to achieve a common task with minimum delay and energy consumption. Future wireless networks mandate exchanging high di...
[]
Validation
31,983
16
Title: ABLE-NeRF: Attention-Based Rendering with Learnable Embeddings for Neural Radiance Field Abstract: Neural Radiance Field (NeRF) is a popular method in representing 3D scenes by optimising a continuous volumetric scene function. Its large success which lies in applying volumetric rendering (VR) is also its Achill...
[ 13010, 15051 ]
Train
31,984
30
Title: MasonNLP+ at SemEval-2023 Task 8: Extracting Medical Questions, Experiences and Claims from Social Media using Knowledge-Augmented Pre-trained Language Models Abstract: In online forums like Reddit, users share their experiences with medical conditions and treatments, including making claims, asking questions, a...
[ 42238 ]
Train
31,985
16
Title: Interactive Segmentation as Gaussian Process Classification Abstract: Click-based interactive segmentation (IS) aims to extract the target objects under user interaction. For this task, most of the current deep learning (DL)-based methods mainly follow the general pipelines of semantic segmentation. Albeit achie...
[ 39169, 3595, 342 ]
Validation
31,986
15
Title: A Storage-Effective BTB Organization for Servers Abstract: Many contemporary applications feature multi-megabyte instruction footprints that overwhelm the capacity of branch target buffers (BTB) and instruction caches (L1-I), causing frequent front-end stalls that inevitably hurt performance. BTB capacity is cru...
[]
Train
31,987
30
Title: LMGQS: A Large-scale Dataset for Query-focused Summarization Abstract: Query-focused summarization (QFS) aims to extract or generate a summary of an input document that directly answers or is relevant to a given query. The lack of large-scale datasets in the form of documents, queries, and summaries has hindered...
[]
Train
31,988
16
Title: Tame a Wild Camera: In-the-Wild Monocular Camera Calibration Abstract: 3D sensing for monocular in-the-wild images, e.g., depth estimation and 3D object detection, has become increasingly important. However, the unknown intrinsic parameter hinders their development and deployment. Previous methods for the monocu...
[ 9217, 35761 ]
Train
31,989
23
Title: Detecting and Optimising Team Interactions in Software Development Abstract: The functional interaction structure of a team captures the preferences with which members of different roles interact. This paper presents a data-driven approach to detect the functional interaction structure for software development t...
[]
Train
31,990
16
Title: Leveraging Hidden Positives for Unsupervised Semantic Segmentation Abstract: Dramatic demand for manpower to label pixel-level annotations triggered the advent of unsupervised semantic segmentation. Although the recent work employing the vision transformer (ViT) backbone shows exceptional performance, there is s...
[ 21239 ]
Test
31,991
30
Title: Towards Zero-Shot Personalized Table-to-Text Generation with Contrastive Persona Distillation Abstract: Existing neural methods have shown great potentials towards generating informative text from structured tabular data as well as maintaining high content fidelity. However, few of them shed light on generating ...
[]
Train
31,992
24
Title: Learning from Invalid Data: On Constraint Satisfaction in Generative Models Abstract: Generative models have demonstrated impressive results in vision, language, and speech. However, even with massive datasets, they struggle with precision, generating physically invalid or factually incorrect data. This is parti...
[ 42595, 30197 ]
Validation
31,993
36
Title: Abstracting Imperfect Information Away from Two-Player Zero-Sum Games Abstract: In their seminal work, Nayyar et al. (2013) showed that imperfect information can be abstracted away from common-payoff games by having players publicly announce their policies as they play. This insight underpins sound solvers and d...
[ 3848 ]
Test
31,994
15
Title: SPAIC: A sub-μW/Channel, 16-Channel General-Purpose Event-Based Analog Front-End with Dual-Mode Encoders Abstract: Low-power event-based analog front-ends (AFE) are a crucial component required to build efficient end-to-end neuromorphic processing systems for edge computing. Although several neuromorphic chips h...
[]
Train
31,995
8
Title: Sustainable Radio Frequency Wireless Energy Transfer for Massive Internet of Things Abstract: Reliable energy supply remains a crucial challenge in the Internet of Things (IoT). Although relying on batteries is cost-effective for a few devices, it is neither a scalable nor a sustainable charging solution as the ...
[ 10461 ]
Train
31,996
30
Title: Computational Language Assessment in patients with speech, language, and communication impairments Abstract: Speech, language, and communication symptoms enable the early detection, diagnosis, treatment planning, and monitoring of neurocognitive disease progression. Nevertheless, traditional manual neurologic as...
[]
Train
31,997
13
Title: Neural Algorithmic Reasoning for Combinatorial Optimisation Abstract: Solving NP-hard/complete combinatorial problems with neural networks is a challenging research area that aims to surpass classical approximate algorithms. The long-term objective is to outperform hand-designed heuristics for NP-hard/complete p...
[ 41734 ]
Train
31,998
14
Title: Faster real root decision algorithm for symmetric polynomials Abstract: In this paper, we consider the problem of deciding the existence of real solutions to a system of polynomial equations having real coefficients, and which are invariant under the action of the symmetric group. We construct and analyze a Mont...
[]
Train
31,999
24
Title: U-Turn Diffusion Abstract: We present a comprehensive examination of score-based diffusion models of AI for generating synthetic images. These models hinge upon a dynamic auxiliary time mechanism driven by stochastic differential equations, wherein the score function is acquired from input images. Our investigat...
[]
Train
32,000
30
Title: Curricular Transfer Learning for Sentence Encoded Tasks Abstract: Fine-tuning language models in a downstream task is the standard approach for many state-of-the-art methodologies in the field of NLP. However, when the distribution between the source task and target task drifts, \textit{e.g.}, conversational env...
[]
Train
32,001
16
Title: MAGVLT: Masked Generative Vision-and-Language Transformer Abstract: While generative modeling on multimodal image-text data has been actively developed with large-scale paired datasets, there have been limited attempts to generate both image and text data by a single model rather than a generation of one fixed m...
[ 25159 ]
Train
32,002
30
Title: Leveraging Open Information Extraction for Improving Few-Shot Trigger Detection Domain Transfer Abstract: Event detection is a crucial information extraction task in many domains, such as Wikipedia or news. The task typically relies on trigger detection (TD) -- identifying token spans in the text that evoke spec...
[]
Test
32,003
16
Title: FasterViT: Fast Vision Transformers with Hierarchical Attention Abstract: We design a new family of hybrid CNN-ViT neural networks, named FasterViT, with a focus on high image throughput for computer vision (CV) applications. FasterViT combines the benefits of fast local representation learning in CNNs and globa...
[ 20026, 16260 ]
Train
32,004
16
Title: StereoVAE: A lightweight stereo matching system through embedded GPUs Abstract: We present a lightweight system for stereo matching through embedded GPUs. It breaks the trade-off between accuracy and processing speed in stereo matching, enabling our embedded system to further improve the matching accuracy while ...
[]
Train
32,005
34
Title: Fast Partitioned Learned Bloom Filter Abstract: A Bloom filter is a memory-efficient data structure for approximate membership queries used in numerous fields of computer science. Recently, learned Bloom filters that achieve better memory efficiency using machine learning models have attracted attention. One suc...
[]
Validation
32,006
24
Title: Look Beyond Bias with Entropic Adversarial Data Augmentation Abstract: Deep neural networks do not discriminate between spurious and causal patterns, and will only learn the most predictive ones while ignoring the others. This shortcut learning behaviour is detrimental to a network’s ability to generalize to an ...
[ 16098 ]
Train
32,007
28
Title: Designing Cellular Networks for UAV Corridors via Bayesian Optimization Abstract: As traditional cellular base stations (BSs) are optimized for 2D ground service, providing 3D connectivity to uncrewed aerial vehicles (UAVs) requires re-engineering of the existing infrastructure. In this paper, we propose a new m...
[ 18088, 19587 ]
Train
32,008
30
Title: Contextual Dynamic Prompting for Response Generation in Task-oriented Dialog Systems Abstract: Response generation is one of the critical components in task-oriented dialog systems. Existing studies have shown that large pre-trained language models can be adapted to this task. The typical paradigm of adapting su...
[]
Train
32,009
27
Title: Autonomous Navigation in Rows of Trees and High Crops with Deep Semantic Segmentation Abstract: Segmentation-based autonomous navigation has recently been proposed as a promising methodology to guide robotic platforms through crop rows without requiring precise GPS localization. However, existing methods are lim...
[ 3528, 40442 ]
Validation
32,010
10
Title: Explaining SAT Solving Using Causal Reasoning Abstract: The past three decades have witnessed notable success in designing efficient SAT solvers, with modern solvers capable of solving industrial benchmarks containing millions of variables in just a few seconds. The success of modern SAT solvers owes to the wide...
[]
Test
32,011
28
Title: Codes and Pseudo-Geometric Designs from the Ternary m-Sequences with Welch-type decimation d=2·3(n-1)/2+1 Abstract: Pseudo-geometric designs are combinatorial designs which share the same parameters as a finite geometry design, but which are not isomorphic to that design. As far as we know, many pseudo-geometric...
[]
Train
32,012
30
Title: Automatic Discrimination of Human and Neural Machine Translation in Multilingual Scenarios Abstract: We tackle the task of automatically discriminating between human and machine translations. As opposed to most previous work, we perform experiments in a multilingual setting, considering multiple languages and mu...
[]
Train
32,013
27
Title: Fast Path Planning Through Large Collections of Safe Boxes Abstract: We present a fast algorithm for the design of smooth paths (or trajectories) that are constrained to lie in a collection of axis-aligned boxes. We consider the case where the number of these safe boxes is large, and basic preprocessing of them ...
[ 7104, 17060, 10927 ]
Train
32,014
30
Title: Guiding Language Models of Code with Global Context using Monitors Abstract: Language models of code (LMs) work well when the surrounding code in the vicinity of generation provides sufficient context. This is not true when it becomes necessary to use types or functionality defined in another module or library, ...
[ 2353, 32450, 14869, 29215 ]
Train
32,015
10
Title: Measure of Uncertainty in Human Emotions Abstract: Many research explore how well computers are able to examine emotions displayed by humans and use that data to perform different tasks. However, there have been very few research which evaluate the computers ability to generate emotion classification information...
[]
Train
32,016
24
Title: Physical Knowledge-Enhanced Deep Neural Network for Sea Surface Temperature Prediction Abstract: Traditionally, numerical models have been deployed in oceanography studies to simulate ocean dynamics by representing physical equations. However, many factors pertaining to ocean dynamics seem to be ill-defined. We ...
[]
Test
32,017
26
Title: Phase Transitions of Diversity in Stochastic Block Model Dynamics Abstract: This paper proposes a stochastic block model with dynamics where the population grows using preferential attachment. Nodes with higher weighted degree are more likely to recruit new nodes, and nodes always recruit nodes from their own co...
[]
Train
32,018
30
Title: RET-LLM: Towards a General Read-Write Memory for Large Language Models Abstract: Large language models (LLMs) have significantly advanced the field of natural language processing (NLP) through their extensive parameters and comprehensive data utilization. However, existing LLMs lack a dedicated memory unit, limi...
[ 8226, 13700, 33477, 13510, 28294, 16556, 634 ]
Test
32,019
30
Title: Toward More Accurate and Generalizable Evaluation Metrics for Task-Oriented Dialogs Abstract: Measurement of interaction quality is a critical task for the improvement of large-scale spoken dialog systems. Existing approaches to dialog quality estimation either focus on evaluating the quality of individual turns...
[]
Test
32,020
25
Title: SlideSpeech: A Large-Scale Slide-Enriched Audio-Visual Corpus Abstract: Multi-Modal automatic speech recognition (ASR) techniques aim to leverage additional modalities to improve the performance of speech recognition systems. While existing approaches primarily focus on video or contextual information, the utili...
[ 40186, 8687 ]
Validation
32,021
24
Title: Near-Minimax-Optimal Risk-Sensitive Reinforcement Learning with CVaR Abstract: In this paper, we study risk-sensitive Reinforcement Learning (RL), focusing on the objective of Conditional Value at Risk (CVaR) with risk tolerance $\tau$. Starting with multi-arm bandits (MABs), we show the minimax CVaR regret rate...
[ 22384, 28791, 10572, 12159 ]
Train
32,022
4
Title: Securing Semantic Communications with Physical-layer Semantic Encryption and Obfuscation Abstract: Deep learning based semantic communication(DLSC) systems have shown great potential of making wireless networks significantly more efficient by only transmitting the semantics of the data. However, the open nature ...
[ 6697 ]
Train
32,023
24
Title: Audiovisual Moments in Time: A Large-Scale Annotated Dataset of Audiovisual Actions Abstract: We present Audiovisual Moments in Time (AVMIT), a large-scale dataset of audiovisual action events. In an extensive annotation task 11 participants labelled a subset of 3-second audiovisual videos from the Moments in Ti...
[]
Train
32,024
4
Title: An Empirical Study on Using Large Language Models to Analyze Software Supply Chain Security Failures Abstract: As we increasingly depend on software systems, the consequences of breaches in the software supply chain become more severe. High-profile cyber attacks like those on SolarWinds and ShadowHammer have res...
[ 18411, 43566, 28783 ]
Train
32,025
24
Title: A Coupled Flow Approach to Imitation Learning Abstract: In reinforcement learning and imitation learning, an object of central importance is the state distribution induced by the policy. It plays a crucial role in the policy gradient theorem, and references to it--along with the related state-action distribution...
[]
Validation
32,026
27
Title: Passive Shape Locking for Multi-Bend Growing Inflated Beam Robots Abstract: Shape change enables new capabilities for robots. One class of robots capable of dramatic shape change is soft growing “vine” robots. These robots usually feature global actuation methods for bending that limit them to simple, constant-c...
[ 34483, 44620, 8429 ]
Train
32,027
6
Title: InkSight: Leveraging Sketch Interaction for Documenting Chart Findings in Computational Notebooks Abstract: Computational notebooks have become increasingly popular for exploratory data analysis due to their ability to support data exploration and explanation within a single document. Effective documentation for...
[ 29472, 41267, 33220 ]
Test
32,028
16
Title: CSP: Self-Supervised Contrastive Spatial Pre-Training for Geospatial-Visual Representations Abstract: Geo-tagged images are publicly available in large quantities, whereas labels such as object classes are rather scarce and expensive to collect. Meanwhile, contrastive learning has achieved tremendous success in ...
[ 26468, 11497, 6124, 35041 ]
Validation
32,029
23
Title: StaticFixer: From Static Analysis to Static Repair Abstract: Static analysis tools are traditionally used to detect and flag programs that violate properties. We show that static analysis tools can also be used to perturb programs that satisfy a property to construct variants that violate the property. Using thi...
[]
Train
32,030
27
Title: COLA: Characterizing and Optimizing the Tail Latency for Safe Level-4 Autonomous Vehicle Systems Abstract: Autonomous vehicles (AVs) are envisioned to revolutionize our life by providing safe, relaxing, and convenient ground transportation. The computing systems in such vehicles are required to interpret various...
[]
Test
32,031
24
Title: Towards Sustainable Development: A Novel Integrated Machine Learning Model for Holistic Environmental Health Monitoring Abstract: Urbanization enables economic growth but also harms the environment through degradation. Traditional methods of detecting environmental issues have proven inefficient. Machine learnin...
[]
Test
32,032
23
Title: Tool-Supported Architecture-Based Data Flow Analysis for Confidentiality Abstract: Through the increasing interconnection between various systems, the need for confidential systems is increasing. Confidential systems share data only with authorized entities. However, estimating the confidentiality of a system is...
[]
Validation
32,033
16
Title: Look around and learn: self-improving object detection by exploration Abstract: Object detectors often experience a drop in performance when new environmental conditions are insufficiently represented in the training data. This paper studies how to automatically fine-tune a pre-existing object detector while exp...
[]
Train
32,034
16
Title: Cheap and Quick: Efficient Vision-Language Instruction Tuning for Large Language Models Abstract: Recently, growing interest has been aroused in extending the multimodal capability of large language models (LLMs), e.g., vision-language (VL) learning, which is regarded as the next milestone of artificial general ...
[ 10624, 13700, 38796, 3853, 41104, 27282, 3609, 4251, 30243, 7982, 10163, 32947, 6453, 45242, 33981, 1854, 24259, 33220, 13408, 37987, 42983, 6770, 13564 ]
Test
32,035
16
Title: You Can Mask More For Extremely Low-Bitrate Image Compression Abstract: Learned image compression (LIC) methods have experienced significant progress during recent years. However, these methods are primarily dedicated to optimizing the rate-distortion (R-D) performance at medium and high bitrates (>0.1 bits per ...
[ 1377 ]
Train
32,036
27
Title: Drive Like a Human: Rethinking Autonomous Driving with Large Language Models Abstract: In this paper, we explore the potential of using a large language model (LLM) to understand the driving environment in a human-like manner and analyze its ability to reason, interpret, and memorize when facing complex scenario...
[ 35427, 13510, 295, 16556, 28396, 16078, 37742, 5104, 36174, 20345, 18459, 13564 ]
Train
32,037
24
Title: The Snowflake Hypothesis: Training Deep GNN with One Node One Receptive field Abstract: Despite Graph Neural Networks demonstrating considerable promise in graph representation learning tasks, GNNs predominantly face significant issues with over-fitting and over-smoothing as they go deeper as models of computer ...
[]
Train
32,038
16
Title: Towards Robust Real-Time Scene Text Detection: From Semantic to Instance Representation Learning Abstract: Due to the flexible representation of arbitrary-shaped scene text and simple pipeline, bottom-up segmentation-based methods begin to be mainstream in real-time scene text detection. Despite great progress, ...
[ 40219 ]
Train
32,039
24
Title: Don't blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy Abstract: Common explanations for shortcut learning assume that the shortcut improves prediction under the training distribution but not in the test distribution. Thus, models trained via the typical gradient-based optimization of cr...
[]
Test
32,040
16
Title: SqueezerFaceNet: Reducing a Small Face Recognition CNN Even More Via Filter Pruning Abstract: The widespread use of mobile devices for various digital services has created a need for reliable and real-time person authentication. In this context, facial recognition technologies have emerged as a dependable method...
[]
Train
32,041
27
Title: Polar Collision Grids: Effective Interaction Modelling for Pedestrian Trajectory Prediction in Shared Space Using Collision Checks Abstract: Predicting pedestrians' trajectories is a crucial capability for autonomous vehicles' safe navigation, especially in spaces shared with pedestrians. Pedestrian motion in sh...
[ 26891 ]
Train
32,042
24
Title: On Exploring Node-feature and Graph-structure Diversities for Node Drop Graph Pooling Abstract: Graph Neural Networks (GNNs) have been successfully applied to graph-level tasks in various fields such as biology, social networks, computer vision, and natural language processing. For the graph-level representation...
[]
Train
32,043
28
Title: Full-Duplex Wireless for 6G: Progress Brings New Opportunities and Challenges Abstract: The use of in-band full-duplex (FD) enables nodes to simultaneously transmit and receive on the same frequency band, which challenges the traditional assumption in wireless network design. The full-duplex capability enhances ...
[ 32233, 12770, 262, 35218 ]
Test
32,044
26
Title: The Looming Threat of Fake and LLM-generated LinkedIn Profiles: Challenges and Opportunities for Detection and Prevention Abstract: In this paper, we present a novel method for detecting fake and Large Language Model (LLM)-generated profiles in the LinkedIn Online Social Network immediately upon registration and...
[ 38235 ]
Train
32,045
27
Title: ERRA: An Embodied Representation and Reasoning Architecture for Long-Horizon Language-Conditioned Manipulation Tasks Abstract: This letter introduces ERRA, an embodied learning architecture that enables robots to jointly obtain three fundamental capabilities (reasoning, planning, and interaction) for solving lon...
[ 22115, 8084, 20013 ]
Train
32,046
30
Title: Revealing the impact of social circumstances on the selection of cancer therapy through natural language processing of social work notes Abstract: We aimed to investigate the impact of social circumstances on cancer therapy selection using natural language processing to derive insights from social worker documen...
[]
Train
32,047
31
Title: On Manipulating Signals of User-Item Graph: A Jacobi Polynomial-based Graph Collaborative Filtering Abstract: Collaborative filtering (CF) is an important research direction in recommender systems that aims to make recommendations given the information on user-item interactions. Graph CF has attracted more and m...
[ 30632, 31020, 2450, 26678, 23355, 1758 ]
Train
32,048
34
Title: Order-Preserving Squares in Strings Abstract: An order-preserving square in a string is a fragment of the form $uv$ where $u\neq v$ and $u$ is order-isomorphic to $v$. We show that a string $w$ of length $n$ over an alphabet of size $\sigma$ contains $\mathcal{O}(\sigma n)$ order-preserving squares that are dist...
[]
Train
32,049
15
Title: A Survey on Deep Learning Hardware Accelerators for Heterogeneous HPC Platforms Abstract: Recent trends in deep learning (DL) imposed hardware accelerators as the most viable solution for several classes of high-performance computing (HPC) applications such as image classification, computer vision, and speech re...
[]
Train
32,050
16
Title: Improving Pseudo Labels for Open-Vocabulary Object Detection Abstract: Recent studies show promising performance in open-vocabulary object detection (OVD) using pseudo labels (PLs) from pretrained vision and language models (VLMs). However, PLs generated by VLMs are extremely noisy due to the gap between the pre...
[ 23152, 27421, 16341 ]
Test
32,051
24
Title: Plan To Predict: Learning an Uncertainty-Foreseeing Model for Model-Based Reinforcement Learning Abstract: In Model-based Reinforcement Learning (MBRL), model learning is critical since an inaccurate model can bias policy learning via generating misleading samples. However, learning an accurate model can be diff...
[ 14402, 19314 ]
Train
32,052
16
Title: A Dual-branch Self-supervised Representation Learning Framework for Tumour Segmentation in Whole Slide Images Abstract: Supervised deep learning methods have achieved considerable success in medical image analysis, owing to the availability of large-scale and well-annotated datasets. However, creating such datas...
[]
Train
32,053
30
Title: Detecting Propaganda Techniques in Code-Switched Social Media Text Abstract: Propaganda is a form of communication intended to influence the opinions and the mindset of the public to promote a particular agenda. With the rise of social media, propaganda has spread rapidly, leading to the need for automatic propa...
[]
Validation
32,054
16
Title: Perceive, Excavate and Purify: A Novel Object Mining Framework for Instance Segmentation Abstract: Recently, instance segmentation has made great progress with the rapid development of deep neural networks. However, there still exist two main challenges including discovering indistinguishable objects and modelin...
[]
Validation
32,055
24
Title: Pruning Deep Neural Networks from a Sparsity Perspective Abstract: In recent years, deep network pruning has attracted significant attention in order to enable the rapid deployment of AI into small devices with computation and memory constraints. Pruning is often achieved by dropping redundant weights, neurons, ...
[]
Train
32,056
30
Title: Cascading and Direct Approaches to Unsupervised Constituency Parsing on Spoken Sentences Abstract: Past work on unsupervised parsing is constrained to written form. In this paper, we present the first study on unsupervised spoken constituency parsing given unlabeled spoken sentences and unpaired textual data. Th...
[]
Train
32,057
24
Title: Harnessing Mixed Offline Reinforcement Learning Datasets via Trajectory Weighting Abstract: Most offline reinforcement learning (RL) algorithms return a target policy maximizing a trade-off between (1) the expected performance gain over the behavior policy that collected the dataset, and (2) the risk stemming fr...
[ 4078 ]
Test
32,058
16
Title: Patch-wise Features for Blur Image Classification Abstract: Images captured through smartphone cameras often suffer from degradation, blur being one of the major ones, posing a challenge in processing these images for downstream tasks. In this paper we propose low-compute lightweight patch-wise features for imag...
[]
Test
32,059
24
Title: Benign Shortcut for Debiasing: Fair Visual Recognition via Intervention with Shortcut Features Abstract: Machine learning models often learn to make predictions that rely on sensitive social attributes like gender and race, which poses significant fairness risks, especially in societal applications, such as hiri...
[]
Validation
32,060
24
Title: Towards Arbitrarily Expressive GNNs in O(n2) Space by Rethinking Folklore Weisfeiler-Lehman Abstract: Message passing neural networks (MPNNs) have emerged as the most popular framework of graph neural networks (GNNs) in recent years. However, their expressive power is limited by the 1-dimensional Weisfeiler-Lehm...
[ 21891, 35910, 26191, 8660, 692, 38747 ]
Validation
32,061
27
Title: Direct LiDAR-Inertial Odometry and Mapping: Perceptive and Connective SLAM Abstract: This paper presents Direct LiDAR-Inertial Odometry and Mapping (DLIOM), a robust SLAM algorithm with an explicit focus on computational efficiency, operational reliability, and real-world efficacy. DLIOM contains several key alg...
[ 10953, 36666, 34274, 14335 ]
Train
32,062
24
Title: GiGaMAE: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction Abstract: Self-supervised learning with masked autoencoders has recently gained popularity for its ability to produce effective image or textual representations, which can be applied to various downstream tasks without ...
[ 8481, 43981, 14744, 37531, 13661 ]
Test
32,063
24
Title: Wasserstein Auto-encoded MDPs: Formal Verification of Efficiently Distilled RL Policies with Many-sided Guarantees Abstract: Although deep reinforcement learning (DRL) has many success stories, the large-scale deployment of policies learned through these advanced techniques in safety-critical scenarios is hinder...
[ 11226 ]
Train
32,064
10
Title: Ontology Pre-training for Poison Prediction Abstract: ,
[]
Train
32,065
22
Title: Descend: A Safe GPU Systems Programming Language Abstract: Graphics Processing Units (GPU) offer tremendous computational power by following a throughput oriented computing paradigm where many thousand computational units operate in parallel. Programming this massively parallel hardware is challenging. Programme...
[]
Train
32,066
24
Title: Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts Abstract: Multivariate probabilistic time series forecasts are commonly evaluated via proper scoring rules, i.e., functions that are minimal in expectation for the ground-truth distribution. However, this property is not sufficient ...
[]
Test
32,067
3
Title: Evidence of Demographic rather than Ideological Segregation in News Discussion on Reddit Abstract: We evaluate homophily and heterophily among ideological and demographic groups in a typical opinion formation context: online discussions of current news. We analyze user interactions across five years in the r/new...
[]
Train
32,068
5
Title: Recoverable and Detectable Self-Implementations of Swap Abstract: Recoverable algorithms tolerate failures and recoveries of processes by using non-volatile memory. Of particular interest are self-implementations of key operations, in which a recoverable operation is implemented from its non-recoverable counterp...
[ 34557 ]
Train
32,069
6
Title: Dance with You: The Diversity Controllable Dancer Generation via Diffusion Models Abstract: Recently, digital humans for interpersonal interaction in virtual environments have gained significant attention. In this paper, we introduce a novel multi-dancer synthesis task called partner dancer generation, which inv...
[ 12489, 954, 26702, 40183 ]
Train
32,070
16
Title: AdvMono3D: Advanced Monocular 3D Object Detection with Depth-Aware Robust Adversarial Training Abstract: Monocular 3D object detection plays a pivotal role in the field of autonomous driving and numerous deep learning-based methods have made significant breakthroughs in this area. Despite the advancements in det...
[ 31163, 36829 ]
Test
32,071
16
Title: Grand Challenge On Detecting Cheapfakes Abstract: Cheapfake is a recently coined term that encompasses non-AI ("cheap") manipulations of multimedia content. Cheapfakes are known to be more prevalent than deepfakes. Cheapfake media can be created using editing software for image/video manipulations, or even witho...
[ 16856 ]
Train
32,072
30
Title: Abductive Commonsense Reasoning Exploiting Mutually Exclusive Explanations Abstract: Abductive reasoning aims to find plausible explanations for an event. This style of reasoning is critical for commonsense tasks where there are often multiple plausible explanations. Existing approaches for abductive reasoning i...
[]
Validation
32,073
39
Title: A simple model of influence Abstract: We propose a simple model of influence in a network, based on edge density. In the model vertices (people) follow the opinion of the group they belong to. The opinion percolates down from an active vertex, the influencer, at the head of the group. Groups can merge, based on ...
[]
Test
32,074
16
Title: General Neural Gauge Fields Abstract: The recent advance of neural fields, such as neural radiance fields, has significantly pushed the boundary of scene representation learning. Aiming to boost the computation efficiency and rendering quality of 3D scenes, a popular line of research maps the 3D coordinate syste...
[]
Train
32,075
6
Title: Comparing How a Chatbot References User Utterances from Previous Chatting Sessions: An Investigation of Users' Privacy Concerns and Perceptions Abstract: Chatbots are capable of remembering and referencing previous conversations, but does this enhance user engagement or infringe on privacy? To explore this trade...
[ 16556 ]
Validation
32,076
25
Title: STARSS23: An Audio-Visual Dataset of Spatial Recordings of Real Scenes with Spatiotemporal Annotations of Sound Events Abstract: While direction of arrival (DOA) of sound events is generally estimated from multichannel audio data recorded in a microphone array, sound events usually derive from visually perceptib...
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Train
32,077
24
Title: LUT-NN: Empower Efficient Neural Network Inference with Centroid Learning and Table Lookup Abstract: On-device Deep Neural Network (DNN) inference consumes significant computing resources and development efforts. To alleviate that, we propose LUT-NN, the first system to empower inference by table lookup, to redu...
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Validation