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
35,578	16	Title: Leveraging Semi-Supervised Graph Learning for Enhanced Diabetic Retinopathy Detection Abstract: Diabetic Retinopathy (DR) is a significant cause of blindness globally, highlighting the urgent need for early detection and effective treatment. Recent advancements in Machine Learning (ML) techniques have shown prom...	[ 5154, 28036, 10838 ]	Test
35,579	22	Title: Ill-Typed Programs Don't Evaluate Abstract: We introduce two-sided type systems, which are a particular kind of sequent calculi for typing formulas. Two-sided type systems allow for hypothetical reasoning over the typing of compound program expressions, and the refutation of typing formulas. By incorporating a t...	[]	Test
35,580	30	Title: A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity Abstract: This paper proposes a framework for quantitatively evaluating interactive LLMs such as ChatGPT using publicly available data sets. We carry out an extensive technical evaluation of ChatGPT using 2...	[ 1024, 19968, 20993, 27140, 33284, 11273, 5643, 24077, 16401, 29714, 16917, 20502, 5659, 23580, 34843, 36383, 14881, 1572, 2597, 17958, 38950, 45608, 23598, 43566, 30770, 2613, 30775, 40504, 29755, 33340, 32319, 44095, 45131, 10830, 5202, 7765, ...	Test
35,581	16	Title: V2X-Seq: A Large-Scale Sequential Dataset for Vehicle-Infrastructure Cooperative Perception and Forecasting Abstract: Utilizing infrastructure and vehicle-side information to track and forecast the behaviors of surrounding traffic participants can significantly improve decision-making and safety in autonomous dr...	[ 21784, 18283, 4462, 31028, 7416, 44574 ]	Validation
35,582	16	Title: MMASD: A Multimodal Dataset for Autism Intervention Analysis Abstract: Autism spectrum disorder (ASD) is a developmental disorder characterized by significant social communication impairments and difficulties perceiving and presenting communication cues. Machine learning techniques have been broadly adopted to f...	[ 45827 ]	Train
35,583	24	Title: An Algorithm for Computing with Brauer's Group Equivariant Neural Network Layers Abstract: The learnable, linear neural network layers between tensor power spaces of $\mathbb{R}^{n}$ that are equivariant to the orthogonal group, $O(n)$, the special orthogonal group, $SO(n)$, and the symplectic group, $Sp(n)$, we...	[ 38039, 27322, 43247 ]	Train
35,584	10	Title: Exploration by self-supervised exploitation Abstract: Reinforcement learning can solve decision-making problems and train an agent to behave in an environment according to a predesigned reward function. However, such an approach becomes very problematic if the reward is too sparse and the agent does not come acr...	[]	Train
35,585	24	Title: Efficient exploration via epistemic-risk-seeking policy optimization Abstract: Exploration remains a key challenge in deep reinforcement learning (RL). Optimism in the face of uncertainty is a well-known heuristic with theoretical guarantees in the tabular setting, but how best to translate the principle to deep...	[]	Train
35,586	16	Title: More is Better: A Database for Spontaneous Micro-Expression with High Frame Rates Abstract: As one of the most important psychic stress reactions, micro-expressions (MEs), are spontaneous and transient facial expressions that can reveal the genuine emotions of human beings. Thus, recognizing MEs (MER) automatica...	[ 21369 ]	Train
35,587	27	Title: Lighthouses and Global Graph Stabilization: Active SLAM for Low-compute, Narrow-FoV Robots Abstract: Autonomous exploration to build a map of an unknown environment is a fundamental robotics problem. However, the quality of the map directly influences the quality of subsequent robot operation. Instability in a s...	[ 19837 ]	Train
35,588	20	Title: Reducing Nearest Neighbor Training Sets Optimally and Exactly Abstract: In nearest-neighbor classification, a training set $P$ of points in $\mathbb{R}^d$ with given classification is used to classify every point in $\mathbb{R}^d$: Every point gets the same classification as its nearest neighbor in $P$. Recently...	[]	Train
35,589	26	Title: Contagion Source Detection in Epidemic and Infodemic Outbreaks: Mathematical Analysis and Network Algorithms Abstract: This monograph provides an overview of the mathematical theories and computational algorithm design for contagion source detection in large networks. By leveraging network centrality as a tool f...	[]	Validation
35,590	24	Title: Leveraging Old Knowledge to Continually Learn New Classes in Medical Images Abstract: Class-incremental continual learning is a core step towards developing artificial intelligence systems that can continuously adapt to changes in the environment by learning new concepts without forgetting those previously learn...	[]	Train
35,591	24	Title: Optimal Transport Perturbations for Safe Reinforcement Learning with Robustness Guarantees Abstract: Robustness and safety are critical for the trustworthy deployment of deep reinforcement learning in real-world decision making applications. In particular, we require algorithms that can guarantee robust, safe pe...	[ 33309 ]	Train
35,592	36	Title: Min-Max Optimization Made Simple: Approximating the Proximal Point Method via Contraction Maps Abstract: In this paper we present a first-order method that admits near-optimal convergence rates for convex/concave min-max problems while requiring a simple and intuitive analysis. Similarly to the seminal work of N...	[]	Train
35,593	3	Title: Collective moderation of hate, toxicity, and extremity in online discussions Abstract: How can citizens moderate hate, toxicity, and extremism in online discourse? We analyze a large corpus of more than 130,000 discussions on German Twitter over the turbulent four years marked by the migrant crisis and political...	[ 4857 ]	Train
35,594	25	Title: AGS: An Dataset and Taxonomy for Domestic Scene Sound Event Recognition Abstract: Environmental sound scene and sound event recognition is important for the recognition of suspicious events in indoor and outdoor environments (such as nurseries, smart homes, nursing homes, etc.) and is a fundamental task involved...	[]	Train
35,595	5	Title: FlexMoE: Scaling Large-scale Sparse Pre-trained Model Training via Dynamic Device Placement Abstract: With the increasing data volume, there is a trend of using large-scale pre-trained models to store the knowledge into an enormous number of model parameters. The training of these models is composed of lots of d...	[ 13616, 19385, 42165, 21543 ]	Train
35,596	30	Title: Numeracy from Literacy: Data Science as an Emergent Skill from Large Language Models Abstract: Large language models (LLM) such as OpenAI's ChatGPT and GPT-3 offer unique testbeds for exploring the translation challenges of turning literacy into numeracy. Previous publicly-available transformer models from eight...	[ 17570, 34981, 11273, 30026, 1899, 25227, 9777, 5493, 43930 ]	Train
35,597	24	Title: Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey Abstract: With recent advances in sensing technologies, a myriad of spatio-temporal data has been generated and recorded in smart cities. Forecasting the evolution patterns of spatio-temporal data is an important yet deman...	[ 10018, 32869, 15529, 28445, 21550, 38640, 40081, 8146, 23805, 17373 ]	Train
35,598	31	Title: Invariant representation learning for sequential recommendation Abstract: Sequential recommendation involves automatically recommending the next item to users based on their historical item sequence. While most prior research employs RNN or transformer methods to glean information from the item sequence-generati...	[ 9238 ]	Train
35,599	16	Title: TCEIP: Text Condition Embedded Regression Network for Dental Implant Position Prediction Abstract: When deep neural network has been proposed to assist the dentist in designing the location of dental implant, most of them are targeting simple cases where only one missing tooth is available. As a result, literatu...	[ 25236 ]	Validation
35,600	30	Title: The Open-domain Paradox for Chatbots: Common Ground as the Basis for Human-like Dialogue Abstract: There is a surge in interest in the development of open-domain chatbots, driven by the recent advancements of large language models. The"openness"of the dialogue is expected to be maximized by providing minimal inf...	[ 16556 ]	Validation
35,601	24	Title: Eliminating Spurious Correlations from Pre-trained Models via Data Mixing Abstract: Machine learning models pre-trained on large datasets have achieved remarkable convergence and robustness properties. However, these models often exploit spurious correlations between certain attributes and labels, which are prev...	[ 8309 ]	Validation
35,602	24	Title: Kernelized Reinforcement Learning with Order Optimal Regret Bounds Abstract: Reinforcement learning (RL) has shown empirical success in various real world settings with complex models and large state-action spaces. The existing analytical results, however, typically focus on settings with a small number of state...	[]	Train
35,603	16	Title: Boundary-weighted logit consistency improves calibration of segmentation networks Abstract: Neural network prediction probabilities and accuracy are often only weakly-correlated. Inherent label ambiguity in training data for image segmentation aggravates such miscalibration. We show that logit consistency across...	[ 34680 ]	Validation
35,604	10	Title: Is AI Art Another Industrial Revolution in the Making? Abstract: A major shift from skilled to unskilled workers was one of the many changes caused by the Industrial Revolution, when the switch to machines contributed to decline in the social and economic status of artisans, whose skills were dismembered into di...	[ 5227, 30261, 10350 ]	Test
35,605	24	Title: Tuning the perplexity for and computing sampling-based t-SNE embeddings Abstract: Widely used pipelines for the analysis of high-dimensional data utilize two-dimensional visualizations. These are created, e.g., via t-distributed stochastic neighbor embedding (t-SNE). When it comes to large data sets, applying th...	[]	Train
35,606	6	Title: It Takes a Village: A Case for Including Extended Family Members in the Joint Oversight of Family-based Privacy and Security for Mobile Smartphones Abstract: We conducted a user study with 19 parent-teen dyads to understand the perceived benefits and drawbacks of using a mobile app that allows them to co-manage ...	[ 25829 ]	Train
35,607	30	Title: MAQA: A Multimodal QA Benchmark for Negation Abstract: Multimodal learning can benefit from the representation power of pretrained Large Language Models (LLMs). However, state-of-the-art transformer based LLMs often ignore negations in natural language and there is no existing benchmark to quantitatively evaluat...	[ 39273, 42165 ]	Train
35,608	24	Title: Probabilistic Computation with Emerging Covariance: Towards Efficient Uncertainty Quantification Abstract: Building robust, interpretable, and secure artificial intelligence system requires some degree of quantifying and representing uncertainty via a probabilistic perspective, as it allows to mimic human cognit...	[ 921 ]	Validation
35,609	10	Title: A Scalable Space-efficient In-database Interpretability Framework for Embedding-based Semantic SQL Queries Abstract: AI-Powered database (AI-DB) is a novel relational database system that uses a self-supervised neural network, database embedding, to enable semantic SQL queries on relational tables. In this paper...	[]	Train
35,610	24	Title: Tight Regret Bounds for Single-pass Streaming Multi-armed Bandits Abstract: Regret minimization in streaming multi-armed bandits (MABs) has been studied extensively in recent years. In the single-pass setting with $K$ arms and $T$ trials, a regret lower bound of $\Omega(T^{2/3})$ has been proved for any algorith...	[ 15613, 2127 ]	Validation
35,611	4	Title: Protecting User Privacy in Remote Conversational Systems: A Privacy-Preserving framework based on text sanitization Abstract: Large Language Models (LLMs) are gaining increasing attention due to their exceptional performance across numerous tasks. As a result, the general public utilize them as an influential to...	[ 12888, 13700, 44189, 17462 ]	Validation
35,612	16	Title: Binarized Spectral Compressive Imaging Abstract: Existing deep learning models for hyperspectral image (HSI) reconstruction achieve good performance but require powerful hardwares with enormous memory and computational resources. Consequently, these methods can hardly be deployed on resource-limited mobile devic...	[]	Train
35,613	2	Title: Datapath Verification via Word-Level E-Graph Rewriting Abstract: Formal verification of datapath circuits is challenging as they are subject to intense optimization effort in the design phase. Industrial vendors and design companies deploy equivalence checking against a golden or existing reference design to sat...	[ 39351 ]	Train
35,614	24	Title: In-Sample Policy Iteration for Offline Reinforcement Learning Abstract: Offline reinforcement learning (RL) seeks to derive an effective control policy from previously collected data. To circumvent errors due to inadequate data coverage, behavior-regularized methods optimize the control policy while concurrently...	[ 7039 ]	Validation
35,615	16	Title: GeneCIS: A Benchmark for General Conditional Image Similarity Abstract: We argue that there are many notions of ‘similarity’ and that models, like humans, should be able to adapt to these dynamically. This contrasts with most representation learning methods, supervised or self-supervised, which learn a fixed emb...	[ 40079 ]	Train
35,616	30	Title: Mitigating Bias in Conversations: A Hate Speech Classifier and Debiaser with Prompts Abstract: Discriminatory language and biases are often present in hate speech during conversations, which usually lead to negative impacts on targeted groups such as those based on race, gender, and religion. To tackle this issu...	[ 13345 ]	Validation
35,617	16	Title: Treasure in Distribution: A Domain Randomization based Multi-Source Domain Generalization for 2D Medical Image Segmentation Abstract: Although recent years have witnessed the great success of convolutional neural networks (CNNs) in medical image segmentation, the domain shift issue caused by the highly variable ...	[]	Train
35,618	24	Title: Can Directed Graph Neural Networks be Adversarially Robust? Abstract: The existing research on robust Graph Neural Networks (GNNs) fails to acknowledge the significance of directed graphs in providing rich information about networks' inherent structure. This work presents the first investigation into the robustn...	[ 42141 ]	Train
35,619	24	Title: On the Generalization of Learned Structured Representations Abstract: Despite tremendous progress over the past decade, deep learning methods generally fall short of human-level systematic generalization. It has been argued that explicitly capturing the underlying structure of data should allow connectionist sys...	[]	Train
35,620	8	Title: A Cross-Frequency Protective Emblem: Protective Options for Medical Units and Wounded Soldiers in the Context of (fully) Autonomous Warfare Abstract: The protection of non-combatants in times of (fully) autonomous warfare raises the question of the timeliness of the international protective emblem. Incidents in ...	[]	Test
35,621	23	Title: "Oops, Did I Just Say That?" Testing and Repairing Unethical Suggestions of Large Language Models with Suggest-Critique-Reflect Process Abstract: As the popularity of large language models (LLMs) soars across various applications, ensuring their alignment with human values has become a paramount concern. In part...	[ 40192, 13345, 39392, 33220, 13700, 3880, 21739, 43277, 8059, 17789 ]	Train
35,622	30	Title: Learning to generate and corr- uh I mean repair language in real-time Abstract: In conversation, speakers produce language incrementally, word by word, while continuously monitoring the appropriateness of their own contribution in the dynamically unfolding context of the conversation; and this often leads them t...	[ 6150 ]	Train
35,623	16	Title: Toward Reliable Human Pose Forecasting with Uncertainty Abstract: Recently, there has been an arms race of pose forecasting methods aimed at solving the spatio-temporal task of predicting a sequence of future 3D poses of a person given a sequence of past observed ones. However, the lack of unified benchmarks and...	[]	Test
35,624	24	Title: Concept Learning for Interpretable Multi-Agent Reinforcement Learning Abstract: Multi-agent robotic systems are increasingly operating in real-world environments in close proximity to humans, yet are largely controlled by policy models with inscrutable deep neural network representations. We introduce a method f...	[ 15968, 4145, 16436, 18647 ]	Train
35,625	30	Title: Unmasking Nationality Bias: A Study of Human Perception of Nationalities in AI-Generated Articles Abstract: We investigate the potential for nationality biases in natural language processing (NLP) models using human evaluation methods. Biased NLP models can perpetuate stereotypes and lead to algorithmic discrimi...	[ 35081, 45403, 12067 ]	Train
35,626	5	Title: Poster: Enabling Flexible Edge-assisted XR Abstract: Extended reality (XR) is touted as the next frontier of the digital future. XR includes all immersive technologies of augmented reality (AR), virtual reality (VR), and mixed reality (MR). XR applications obtain the real-world context of the user from an underl...	[ 13814 ]	Train
35,627	30	Title: Second Thoughts are Best: Learning to Re-Align With Human Values from Text Edits Abstract: We present Second Thought, a new learning paradigm that enables language models (LMs) to re-align with human values. By modeling the chain-of-edits between value-unaligned and value-aligned text, with LM fine-tuning and ad...	[ 22289, 8482, 20709, 33095 ]	Train
35,628	24	Title: Distributional GFlowNets with Quantile Flows Abstract: Generative Flow Networks (GFlowNets) are a new family of probabilistic samplers where an agent learns a stochastic policy for generating complex combinatorial structure through a series of decision-making steps. Despite being inspired from reinforcement lear...	[ 22816, 40424, 29267, 43749 ]	Train
35,629	30	Title: Dancing Between Success and Failure: Edit-level Simplification Evaluation using SALSA Abstract: Large language models (e.g., GPT-3.5) are uniquely capable of producing highly rated text simplification, yet current human evaluation methods fail to provide a clear understanding of systems' specific strengths and w...	[ 1368, 42424 ]	Train
35,630	27	Title: Dronument: System for Reliable Deployment of Micro Aerial Vehicles in Dark Areas of Large Historical Monuments Abstract: This letter presents a self-contained system for robust deployment of autonomous aerial vehicles in environments without access to global navigation systems and with limited lighting condition...	[ 27877, 22599, 4682, 45306, 35213, 41935, 13049, 36890 ]	Train
35,631	4	Title: Usability of Privacy Controls in Top Health Websites Abstract: With the increasing awareness and concerns around privacy, many service providers offer their users various privacy controls. Through these controls, users gain greater authority over the collection, utilisation, and dissemination of their personal i...	[]	Validation
35,632	27	Title: Graph-based Global Robot Simultaneous Localization and Mapping using Architectural Plans Abstract: In this paper, we propose a solution for graph-based global robot simultaneous localization and mapping (SLAM) using architectural plans. Before the start of the robot operation, the previously available architectu...	[]	Train
35,633	30	Title: Critical Behavioral Traits Foster Peer Engagement in Online Mental Health Communities Abstract: Online Mental Health Communities (OMHCs), such as Reddit, have witnessed a surge in popularity as go-to platforms for seeking information and support in managing mental health needs. Platforms like Reddit offer immedi...	[]	Train
35,634	5	Title: Toward Scalable and Controllable AR Experimentation Abstract: To understand how well a proposed augmented reality (AR) solution works, existing papers often conducted tailored and isolated evaluations for specific AR tasks, e.g., depth or lighting estimation, and compared them to easy-to-setup baselines, either ...	[ 8680, 7795, 16862 ]	Test
35,635	30	Title: Vision Meets Definitions: Unsupervised Visual Word Sense Disambiguation Incorporating Gloss Information Abstract: Visual Word Sense Disambiguation (VWSD) is a task to find the image that most accurately depicts the correct sense of the target word for the given context. Previously, image-text matching models oft...	[ 17188 ]	Train
35,636	16	Title: Efficient Deep Learning Models for Privacy-Preserving People Counting on Low-Resolution Infrared Arrays Abstract: Ultralow-resolution infrared (IR) array sensors offer a low cost, energy efficient, and privacy-preserving solution for people counting, with applications, such as occupancy monitoring and visitor fl...	[ 19031 ]	Train
35,637	30	Title: Quantifying Valence and Arousal in Text with Multilingual Pre-trained Transformers Abstract: The analysis of emotions expressed in text has numerous applications. In contrast to categorical analysis, focused on classifying emotions according to a pre-defined set of common classes, dimensional approaches can offe...	[ 1433, 37242 ]	Train
35,638	10	Title: Amortised Design Optimization for Item Response Theory Abstract: nan	[]	Validation
35,639	16	Title: Visual Transformation Telling Abstract: In this paper, we propose a new visual reasoning task, called Visual Transformation Telling (VTT). This task requires a machine to describe the transformation that occurred between every two adjacent states (i.e. images) in a series. Unlike most existing visual reasoning t...	[ 16676 ]	Test
35,640	27	Title: Two Degree of Freedom Adaptive Control for Hysteresis Compensation of Pneumatic Continuum Bending Actuator Abstract: Soft robotics, with their inherent flexibility and infinite degrees of freedom (DoF), offer promising advancements in human-machine interfaces. Particularly, pneumatic artificial muscles (PAMs) an...	[ 41536 ]	Train
35,641	16	Title: Self-Sampling Meta SAM: Enhancing Few-shot Medical Image Segmentation with Meta-Learning Abstract: While the Segment Anything Model (SAM) excels in semantic segmentation for general-purpose images, its performance significantly deteriorates when applied to medical images, primarily attributable to insufficient r...	[ 17633, 19907, 5864, 6089, 30825, 35263, 16180, 29270, 5821, 1151 ]	Train
35,642	24	Title: FewSOME: One-Class Few Shot Anomaly Detection with Siamese Networks Abstract: Recent Anomaly Detection techniques have progressed the field considerably but at the cost of increasingly complex training pipelines. Such techniques require large amounts of training data, resulting in computationally expensive algor...	[]	Train
35,643	30	Title: Clustering-Aware Negative Sampling for Unsupervised Sentence Representation Abstract: Contrastive learning has been widely studied in sentence representation learning. However, earlier works mainly focus on the construction of positive examples, while in-batch samples are often simply treated as negative example...	[]	Train
35,644	30	Title: Three Ways of Using Large Language Models to Evaluate Chat Abstract: This paper describes the systems submitted by team6 for ChatEval, the DSTC 11 Track 4 competition. We present three different approaches to predicting turn-level qualities of chatbot responses based on large language models (LLMs). We report im...	[ 43641, 39451, 36097 ]	Train
35,645	24	Title: Extracting Diagnosis Pathways from Electronic Health Records Using Deep Reinforcement Learning Abstract: Clinical diagnosis guidelines aim at specifying the steps that may lead to a diagnosis. Inspired by guidelines, we aim to learn the optimal sequence of actions to perform in order to obtain a correct diagnosi...	[ 44048 ]	Train
35,646	24	Title: A Federated Learning-based Industrial Health Prognostics for Heterogeneous Edge Devices using Matched Feature Extraction Abstract: Data-driven industrial health prognostics require rich training data to develop accurate and reliable predictive models. However, stringent data privacy laws and the abundance of edg...	[]	Train
35,647	16	Title: Self-supervised Scene Text Segmentation with Object-centric Layered Representations Augmented by Text Regions Abstract: Text segmentation tasks have a very wide range of application values, such as image editing, style transfer, watermark removal, etc. However, existing public datasets are of poor quality of pix...	[]	Train
35,648	36	Title: Improved Approximation Ratios of Fixed-Price Mechanisms in Bilateral Trades Abstract: We continue the study of the performance for fixed-price mechanisms in the bilateral trade problem, and improve approximation ratios of welfare-optimal mechanisms in several settings. Specifically, in the case where only the bu...	[ 43208, 17374 ]	Train
35,649	27	Title: Intelligent humanoids in manufacturing to address worker shortage and skill gaps: Case of Tesla Optimus Abstract: Technological evolution in the field of robotics is emerging with major breakthroughs in recent years. This was especially fostered by revolutionary new software applications leading to humanoid robo...	[]	Validation
35,650	16	Title: FEDORA: Flying Event Dataset fOr Reactive behAvior Abstract: The ability of living organisms to perform complex high speed manoeuvers in flight with a very small number of neurons and an incredibly low failure rate highlights the efficacy of these resource-constrained biological systems. Event-driven hardware ha...	[]	Train
35,651	27	Title: Stable In-hand Manipulation with Finger Specific Multi-agent Shadow Reward Abstract: Deep Reinforcement Learning has shown its capability to solve the high degrees of freedom in control and the complex interaction with the object in the multi-finger dexterous in-hand manipulation tasks. Current DRL approaches pr...	[]	Train
35,652	24	Title: HNO: Hyena Neural Operator for solving PDEs Abstract: Numerically solving partial differential equations (PDEs) typically requires fine discretization to resolve necessary spatiotemporal scales, which can be computationally expensive. Recent advances in deep learning have provided a new approach to solving PDEs ...	[ 26208, 11082, 32547 ]	Train
35,653	25	Title: Multi-Scale Attention for Audio Question Answering Abstract: Audio question answering (AQA), acting as a widely used proxy task to explore scene understanding, has got more attention. The AQA is challenging for it requires comprehensive temporal reasoning from different scales' events of an audio scene. However,...	[ 40921 ]	Validation
35,654	16	Title: Towards Non-Parametric Models for Confidence Aware Image Prediction from Low Data using Gaussian Processes Abstract: The ability to envision future states is crucial to informed decision making while interacting with dynamic environments. With cameras providing a prevalent and information rich sensing modality, ...	[]	Train
35,655	16	Title: TrainSim: A Railway Simulation Framework for LiDAR and Camera Dataset Generation Abstract: The railway industry is searching for new ways to automate a number of complex train functions, such as object detection, track discrimination, and accurate train positioning, which require the artificial perception of the...	[]	Train
35,656	27	Title: Efficient Deep Learning of Robust, Adaptive Policies using Tube MPC-Guided Data Augmentation Abstract: The deployment of agile autonomous systems in challenging, unstructured environments requires adaptation capabilities and robustness to uncertainties. Existing robust and adaptive controllers, such as the ones ...	[]	Test
35,657	30	Title: Transfer Learning from Pre-trained Language Models Improves End-to-End Speech Summarization Abstract: End-to-end speech summarization (E2E SSum) directly summarizes input speech into easy-to-read short sentences with a single model. This approach is promising because it, in contrast to the conventional cascade a...	[ 2111 ]	Validation
35,658	16	Title: Attention-based Part Assembly for 3D Volumetric Shape Modeling Abstract: Modeling a 3D volumetric shape as an assembly of decomposed shape parts is much more challenging, but semantically more valuable than direct reconstruction from a full shape representation. The neural network needs to implicitly learn part ...	[ 40100 ]	Validation
35,659	27	Title: Heterogeneous Coalition Formation and Scheduling with Multi-Skilled Robots Abstract: We present an approach to task scheduling in heterogeneous multi-robot systems. In our setting, the tasks to complete require diverse skills. We assume that each robot is multi-skilled, i.e., each robot offers a subset of the po...	[]	Train
35,660	15	Title: Algorithms and Hardware for Efficient Processing of Logic-based Neural Networks Abstract: Recent efforts to improve the performance of neural network (NN) accelerators that meet today’s application requirements have given rise to a new trend of logic-based NN inference relying on fixed-function combinational log...	[]	Train
35,661	4	Title: X-CANIDS: Signal-Aware Explainable Intrusion Detection System for Controller Area Network-Based In-Vehicle Network Abstract: Controller Area Network (CAN) is an essential networking protocol that connects multiple electronic control units (ECUs) in a vehicle. However, CAN-based in-vehicle networks (IVNs) face se...	[]	Test
35,662	24	Title: Text2Cohort: Democratizing the NCI Imaging Data Commons with Natural Language Cohort Discovery Abstract: The Imaging Data Commons (IDC) is a cloud-based database that provides researchers with open access to cancer imaging data, with the goal of facilitating collaboration in medical imaging research. However, qu...	[ 21880 ]	Train
35,663	37	Title: Efficient and Compact Spreadsheet Formula Graphs Abstract: Spreadsheets are one of the most popular data analysis tools, wherein users can express computation as formulae alongside data. The ensuing dependencies are tracked as formula graphs. Efficiently querying and maintaining these formula graphs is critical ...	[]	Validation
35,664	16	Title: Rethinking Visual Prompt Learning as Masked Visual Token Modeling Abstract: Prompt learning has achieved great success in efficiently exploiting large-scale pre-trained models in natural language processing (NLP). It reformulates the downstream tasks as the generative pre-training ones, thus narrowing down the g...	[ 30936, 43179 ]	Train
35,665	39	Title: Degree-3 Planar Graphs as Topological Minors of Wall Graphs in Polynomial Time Abstract: In this note, we give a proof of the fact that we can efficiently find degree-3 planar graphs as topological minors of sufficiently large wall graphs. The result is needed as an intermediate step to fix a proof in my PhD the...	[]	Test
35,666	9	Title: The complexity of the Chinese Remainder Theorem Abstract: The Chinese Remainder Theorem for the integers says that every system of congruence equations is solvable as long as the system satisfies an obvious necessary condition. This statement can be generalized in a natural way to arbitrary algebraic structures ...	[]	Train
35,667	16	Title: Mask2Anomaly: Mask Transformer for Universal Open-set Segmentation Abstract: Segmenting unknown or anomalous object instances is a critical task in autonomous driving applications, and it is approached traditionally as a per-pixel classification problem. However, reasoning individually about each pixel without c...	[ 16513 ]	Train
35,668	27	Title: FC Portugal 3D Simulation Team: Team Description Paper 2020 Abstract: The FC Portugal 3D team is developed upon the structure of our previous Simulation league 2D/3D teams and our standard platform league team. Our research concerning the robot low-level skills is focused on developing behaviors that may be appl...	[]	Train
35,669	5	Title: ABS: Adaptive Bounded Staleness Converges Faster and Communicates Less Abstract: Wall-clock convergence time and communication rounds are critical performance metrics in distributed learning with parameter-server setting. While synchronous methods converge fast but are not robust to stragglers; and asynchronous ...	[]	Train
35,670	27	Title: Using an Improved Output Feedback MPC Approach for Developing a Haptic Virtual Training System Abstract: nan	[]	Train
35,671	30	Title: SQuARe: A Large-Scale Dataset of Sensitive Questions and Acceptable Responses Created through Human-Machine Collaboration Abstract: The potential social harms that large language models pose, such as generating offensive content and reinforcing biases, are steeply rising. Existing works focus on coping with this...	[ 10963 ]	Test
35,672	16	Title: Exploration of Lightweight Single Image Denoising with Transformers and Truly Fair Training Abstract: As multimedia content often contains noise from intrinsic defects of digital devices, image denoising is an important step for high-level vision recognition tasks. Although several studies have developed the den...	[ 3565, 28854 ]	Train
35,673	30	Title: Mining Healthcare Procurement Data Using Text Mining and Natural Language Processing - Reflection From An Industrial Project Abstract: . While text mining and NLP research has been established for decades, there remain gaps in the literature that reports the use of these techniques in building real-world applica...	[]	Train
35,674	16	Title: A Survey and Approach to Chart Classification Abstract: Charts represent an essential source of visual information in documents and facilitate a deep understanding and interpretation of information typically conveyed numerically. In the scientific literature, there are many charts, each with its stylistic differ...	[]	Validation
35,675	24	Title: Information Bottleneck Analysis of Deep Neural Networks via Lossy Compression Abstract: The Information Bottleneck (IB) principle offers an information-theoretic framework for analyzing the training process of deep neural networks (DNNs). Its essence lies in tracking the dynamics of two mutual information (MI) v...	[ 5626 ]	Train
35,676	30	Title: Unsupervised Semantic Variation Prediction using the Distribution of Sibling Embeddings Abstract: Languages are dynamic entities, where the meanings associated with words constantly change with time. Detecting the semantic variation of words is an important task for various NLP applications that must make time-s...	[]	Train
35,677	28	Title: Fairness Optimization of RSMA for Uplink Communication based on Intelligent Reflecting Surface Abstract: In this paper, we propose a rate-splitting multiple access (RSMA) scheme for uplink wireless communication systems with intelligent reflecting surface (IRS) aided. In the considered model, IRS is adopted to o...	[]	Train

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