node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
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|---|---|---|---|---|
17,878 | 16 | Title: Improving Generalization in Visual Reinforcement Learning via Conflict-aware Gradient Agreement Augmentation
Abstract: Learning a policy with great generalization to unseen environments remains challenging but critical in visual reinforcement learning. Despite the success of augmentation combination in the super... | [
43945,
19211,
42771,
14677,
19871
] | Validation |
17,879 | 34 | Title: Time-limited Bloom Filter
Abstract: A Bloom Filter is a probabilistic data structure designed to check, rapidly and memory-efficiently, whether an element is present in a set. It has been vastly used in various computing areas and several variants, allowing deletions, dynamic sets and working with sliding window... | [] | Train |
17,880 | 9 | Title: Complexity of Reasoning with Cardinality Minimality Conditions
Abstract: Many AI-related reasoning problems are based on the problem of satisfiability of propositional formulas with some cardinality-minimality condition. While the complexity of the satisfiability problem (SAT) is well understood when considering... | [] | Test |
17,881 | 37 | Title: CAESURA: Language Models as Multi-Modal Query Planners
Abstract: Traditional query planners translate SQL queries into query plans to be executed over relational data. However, it is impossible to query other data modalities, such as images, text, or video stored in modern data systems such as data lakes using t... | [
10624,
3609,
45242,
1854
] | Train |
17,882 | 10 | Title: Customer Profiling, Segmentation, and Sales Prediction using AI in Direct Marketing
Abstract: In an increasingly customer-centric business environment, effective communication between marketing and senior management is crucial for success. With the rise of globalization and increased competition, utilizing new d... | [] | Train |
17,883 | 30 | Title: A Comparative Study between Full-Parameter and LoRA-based Fine-Tuning on Chinese Instruction Data for Instruction Following Large Language Model
Abstract: Recently, the instruction-tuning of large language models is a crucial area of research in the field of natural language processing. Due to resource and cost ... | [
33220,
45388,
4658,
17076,
4635
] | Train |
17,884 | 16 | Title: Clinically Labeled Contrastive Learning for OCT Biomarker Classification
Abstract: This article presents a novel positive and negative set selection strategy for contrastive learning of medical images based on labels that can be extracted from clinical data. In the medical field, there exists a variety of labels... | [
44756
] | Train |
17,885 | 16 | Title: NeuralPCI: Spatio-Temporal Neural Field for 3D Point Cloud Multi-Frame Non-Linear Interpolation
Abstract: In recent years, there has been a significant increase in focus on the interpolation task of computer vision. Despite the tremendous advancement of video interpolation, point cloud interpolation remains insu... | [] | Train |
17,886 | 39 | Title: Reconstructing Graphs from Connected Triples
Abstract: We introduce a new model of indeterminacy in graphs: instead of specifying all the edges of the graph, the input contains all triples of vertices that form a connected subgraph. In general, different (labelled) graphs may have the same set of connected tripl... | [] | Test |
17,887 | 16 | Title: One at A Time: Multi-step Volumetric Probability Distribution Diffusion for Depth Estimation
Abstract: Recent works have explored the fundamental role of depth estimation in multi-view stereo (MVS) and semantic scene completion (SSC). They generally construct 3D cost volumes to explore geometric correspondence i... | [
17612,
6389,
42982
] | Test |
17,888 | 2 | Title: Probabilistic Operational Correspondence (Technical Report)
Abstract: Encodings are the main way to compare process calculi. By applying quality criteria to encodings we analyse their quality and rule out trivial or meaningless encodings. Thereby, operational correspondence is one of the most common and most imp... | [] | Validation |
17,889 | 30 | Title: RobuT: A Systematic Study of Table QA Robustness Against Human-Annotated Adversarial Perturbations
Abstract: Despite significant progress having been made in question answering on tabular data (Table QA), it’s unclear whether, and to what extent existing Table QA models are robust to task-specific perturbations,... | [
36545,
4351
] | Train |
17,890 | 30 | Title: CompoundPiece: Evaluating and Improving Decompounding Performance of Language Models
Abstract: While many languages possess processes of joining two or more words to create compound words, previous studies have been typically limited only to languages with excessively productive compound formation (e.g., German,... | [
32276
] | Test |
17,891 | 16 | Title: High-Fidelity Zero-Shot Texture Anomaly Localization Using Feature Correspondence Analysis
Abstract: We propose a novel method for Zero-Shot Anomaly Localization that leverages a bidirectional mapping derived from the 1-dimensional Wasserstein Distance. The proposed approach allows pinpointing the anomalous regi... | [
27414
] | Train |
17,892 | 24 | Title: Towards Sustainable Deep Learning for Multi-Label Classification on NILM
Abstract: Non-intrusive load monitoring (NILM) is the process of obtaining appliance-level data from a single metering point, measuring total electricity consumption of a household or a business. Appliance-level data can be directly used fo... | [] | Train |
17,893 | 36 | Title: Markov chains applied to Parrondo's paradox: The coin tossing problem
Abstract: Parrondo’s paradox was introduced by Juan Parrondo in 1996. In game theory, this paradox is described as: A combination of losing strategies becomes a winning strategy. At first glance, this paradox is quite surprising, but we can ea... | [] | Train |
17,894 | 34 | Title: Kernelization for Finding Lineal Topologies (Depth-First Spanning Trees) with Many or Few Leaves
Abstract: For a given graph $G$, a depth-first search (DFS) tree $T$ of $G$ is an $r$-rooted spanning tree such that every edge of $G$ is either an edge of $T$ or is between a \textit{descendant} and an \textit{ances... | [] | Validation |
17,895 | 5 | Title: PIGEON: Optimizing CUDA Code Generator for End-to-End Training and Inference of Relational Graph Neural Networks
Abstract: Relational graph neural networks (RGNNs) are graph neural networks (GNNs) with dedicated structures for modeling the different types of nodes and/or edges in heterogeneous graphs. While RGNN... | [
23156
] | Test |
17,896 | 10 | Title: Intent-aligned AI systems deplete human agency: the need for agency foundations research in AI safety
Abstract: The rapid advancement of artificial intelligence (AI) systems suggests that artificial general intelligence (AGI) systems may soon arrive. Many researchers are concerned that AIs and AGIs will harm hum... | [
22994
] | Validation |
17,897 | 8 | Title: WiFi Physical Layer Stays Awake and Responds When it Should Not
Abstract: WiFi communication should be possible only between devices inside the same network. However, we find that all existing WiFi devices send back acknowledgments (ACK) to even fake packets received from unauthorized WiFi devices outside of the... | [
11264
] | Train |
17,898 | 10 | Title: Toward A Logical Theory Of Fairness and Bias
Abstract:
Fairness in machine learning is of considerable interest in recent years owing to the propensity of algorithms trained on historical data to amplify and perpetuate historical biases. In this paper, we argue for a formal reconstruction of fairness definitio... | [] | Train |
17,899 | 2 | Title: Folding interpretations
Abstract: We study the polyregular string-to-string functions, which are certain functions of polynomial output size that can be described using automata and logic. We describe a system of combinators that generates exactly these functions. Unlike previous systems, the present system incl... | [] | Test |
17,900 | 16 | Title: Sit Back and Relax: Learning to Drive Incrementally in All Weather Conditions
Abstract: In autonomous driving scenarios, current object detection models show strong performance when tested in clear weather. However, their performance deteriorates significantly when tested in degrading weather conditions. In addi... | [] | Train |
17,901 | 34 | Title: Warehouse Problem with Bounds, Fixed Costs and Complementarity Constraints
Abstract: This paper studies an open question in the warehouse problem where a merchant trading a commodity tries to find an optimal inventory-trading policy to decide on purchase and sale quantities during a fixed time horizon in order t... | [] | Train |
17,902 | 30 | Title: Few-shot Unified Question Answering: Tuning Models or Prompts?
Abstract: Question-answering (QA) tasks often investigate specific question types, knowledge domains, or reasoning skills, leading to specialized models catering to specific categories of QA tasks. While recent research has explored the idea of unifi... | [] | Train |
17,903 | 16 | Title: FETNet: Feature erasing and transferring network for scene text removal
Abstract: nan | [
35077,
42653
] | Validation |
17,904 | 5 | Title: Adaptive parallelization of multi-agent simulations with localized dynamics
Abstract: Agent-based modelling constitutes a versatile approach to representing and simulating complex systems. Studying large-scale systems is challenging because of the computational time required for the simulation runs: scaling is a... | [] | Train |
17,905 | 34 | Title: Semi-online Scheduling with Lookahead
Abstract: The knowledge of future partial information in the form of a lookahead to design efficient online algorithms is a theoretically-efficient and realistic approach to solving computational problems. Design and analysis of semi-online algorithms with extra-piece-of-inf... | [] | Validation |
17,906 | 27 | Title: A Palm-Shape Variable-Stiffness Gripper Based on 3D-Printed Fabric Jamming
Abstract: Soft grippers have excellent adaptability for a variety of objects and tasks. Jamming-based variable stiffness materials can further increase soft grippers' gripping force and capacity. Previous universal grippers enabled by gra... | [] | Test |
17,907 | 16 | Title: PGformer: Proxy-Bridged Game Transformer for Multi-Person Extremely Interactive Motion Prediction
Abstract: Multi-person motion prediction is a challenging task, especially for real-world scenarios of densely interacted persons. Most previous works have been devoted to studying the case of weak interactions (e.g... | [] | Train |
17,908 | 24 | Title: Network Fault-tolerant and Byzantine-resilient Social Learning via Collaborative Hierarchical Non-Bayesian Learning
Abstract: As the network scale increases, existing fully distributed solutions start to lag behind the real-world challenges such as (1) slow information propagation, (2) network communication fail... | [] | Train |
17,909 | 16 | Title: Optimal Linear Subspace Search: Learning to Construct Fast and High-Quality Schedulers for Diffusion Models
Abstract: In recent years, diffusion models have become the most popular and powerful methods in the field of image synthesis, even rivaling human artists in artistic creativity. However, the key issue cur... | [
42272,
5682,
8308
] | Train |
17,910 | 11 | Title: Multi-Agent Reinforcement Learning for Fast-Timescale Demand Response of Residential Loads
Abstract: To integrate high amounts of renewable energy resources, electrical power grids must be able to cope with high amplitude, fast timescale variations in power generation. Frequency regulation through demand respons... | [
19541
] | Train |
17,911 | 34 | Title: On Coresets for Clustering in Small Dimensional Euclidean Spaces
Abstract: We consider the problem of constructing small coresets for $k$-Median in Euclidean spaces. Given a large set of data points $P\subset \mathbb{R}^d$, a coreset is a much smaller set $S\subset \mathbb{R}^d$, so that the $k$-Median costs of ... | [] | Test |
17,912 | 24 | Title: Deep Attention Q-Network for Personalized Treatment Recommendation
Abstract: Tailoring treatment for individual patients is crucial yet challenging in order to achieve optimal healthcare outcomes. Recent advances in reinforcement learning offer promising personalized treatment recommendations; however, they rely... | [] | Test |
17,913 | 38 | Title: ChatGPT Creates a Review Article: State of the Art in the Most-Cited Articles on ChatGPT in Health Science, Computer Science, Communication, and Culture, According to Altmetric in Dimensions.ai
Abstract: We have analyzed all preprints on ChatGPT (N=501) and selected the most influential preprints (according to A... | [
3811,
29109
] | Validation |
17,914 | 16 | Title: Explainable Multi-View Deep Networks Methodology for Experimental Physics
Abstract: Physical experiments often involve multiple imaging representations, such as X-ray scans and microscopic images. Deep learning models have been widely used for supervised analysis in these experiments. Combining different image r... | [
2526
] | Validation |
17,915 | 5 | Title: Mystique: Enabling Accurate and Scalable Generation of Production AI Benchmarks
Abstract: Building large AI fleets to support the rapidly growing DL workloads is an active research topic for modern cloud providers. Generating accurate benchmarks plays an essential role in designing the fast-paced software and ha... | [
37190
] | Train |
17,916 | 4 | Title: Diff-CAPTCHA: An Image-based CAPTCHA with Security Enhanced by Denoising Diffusion Model
Abstract: To enhance the security of text CAPTCHAs, various methods have been employed, such as adding the interference lines on the text, randomly distorting the characters, and overlapping multiple characters. These method... | [] | Train |
17,917 | 10 | Title: Multi-Agent Reinforcement Learning Guided by Signal Temporal Logic Specifications
Abstract: There has been growing interest in deep reinforcement learning (DRL) algorithm design, and reward design is one key component of DRL. Among the various techniques, formal methods integrated with DRL have garnered consider... | [] | Train |
17,918 | 39 | Title: Link Residual Closeness of Harary Graphs
Abstract: The study of networks characteristics is an important subject in different fields, like math, chemistry, transportation, social network analysis etc. The residual closeness is one of the most sensitive measure of graphs vulnerability. In this article we calculat... | [] | Train |
17,919 | 16 | Title: Select2Col: Leveraging Spatial-Temporal Importance of Semantic Information for Efficient Collaborative Perception
Abstract: Collaboration by leveraging the shared semantic information plays a crucial role in overcoming the perception capability limitations of isolated agents. However, existing collaborative perc... | [] | Train |
17,920 | 30 | Title: The political ideology of conversational AI: Converging evidence on ChatGPT's pro-environmental, left-libertarian orientation
Abstract: Conversational artificial intelligence (AI) disrupts how humans interact with technology. Recently, OpenAI introduced ChatGPT, a state-of-the-art dialogue model that can convers... | [
17668,
11273,
40585,
38157,
44173,
668,
690,
24886,
12602,
18764,
846,
28242,
12500,
26199,
13278,
45923,
13413,
1899,
40693,
26357,
23159
] | Train |
17,921 | 10 | Title: Towards Theory-based Moral AI: Moral AI with Aggregating Models Based on Normative Ethical Theory
Abstract: Moral AI has been studied in the fields of philosophy and artificial intelligence. Although most existing studies are only theoretical, recent developments in AI have made it increasingly necessary to impl... | [] | Test |
17,922 | 15 | Title: The Case for Replication-Aware Memory-Error Protection in Disaggregated Memory
Abstract: Disaggregated memory leverages recent technology advances in high-density, byte-addressable non-volatile memory and high-performance interconnects to provide a large memory pool shared across multiple compute nodes. Due to h... | [] | Train |
17,923 | 16 | Title: Scan2LoD3: Reconstructing semantic 3D building models at LoD3 using ray casting and Bayesian networks
Abstract: Reconstructing semantic 3D building models at the level of detail (LoD) 3 is a long-standing challenge. Unlike mesh-based models, they require watertight geometry and object-wise semantics at the façad... | [
13222
] | Train |
17,924 | 24 | Title: A benchmark of categorical encoders for binary classification
Abstract: Categorical encoders transform categorical features into numerical representations that are indispensable for a wide range of machine learning models. Existing encoder benchmark studies lack generalizability because of their limited choice o... | [] | Train |
17,925 | 30 | Title: Compressing Sentence Representation with Maximum Coding Rate Reduction
Abstract: In most natural language inference problems, sentence representation is needed for semantic retrieval tasks. In recent years, pre-trained large language models have been quite effective for computing such representations. These mode... | [] | Train |
17,926 | 28 | Title: Capacity-Achieving Polar-Based Codes With Sparsity Constraints on the Generator Matrices
Abstract: In general, the generator matrix sparsity is a critical factor in determining the encoding complexity of a linear code. Further, certain applications, e.g., distributed crowdsourcing schemes utilizing linear codes,... | [] | Validation |
17,927 | 16 | Title: Seeing the Pose in the Pixels: Learning Pose-Aware Representations in Vision Transformers
Abstract: Human perception of surroundings is often guided by the various poses present within the environment. Many computer vision tasks, such as human action recognition and robot imitation learning, rely on pose-based e... | [] | Train |
17,928 | 16 | Title: Multi-Scale and Multi-Layer Contrastive Learning for Domain Generalization
Abstract: During the past decade, deep neural networks have led to fast-paced progress and significant achievements in computer vision problems, for both academia and industry. Yet despite their success, state-of-the-art image classificat... | [] | Train |
17,929 | 30 | Title: Text Classification in the Wild: a Large-scale Long-tailed Name Normalization Dataset
Abstract: Real-world data usually exhibits a long-tailed distribution,with a few frequent labels and a lot of few-shot labels. The study of institution name normalization is a perfect application case showing this phenomenon. T... | [] | Train |
17,930 | 30 | Title: Grading Conversational Responses Of Chatbots
Abstract: Chatbots have long been capable of answering basic questions and even responding to obscure prompts, but recently their improvements have been far more significant. Modern chatbots like Open AIs ChatGPT3 not only have the ability to answer basic questions bu... | [
9777,
17570,
18055
] | Train |
17,931 | 24 | Title: Gradient-Based Post-Training Quantization: Challenging the Status Quo
Abstract: Quantization has become a crucial step for the efficient deployment of deep neural networks, where floating point operations are converted to simpler fixed point operations. In its most naive form, it simply consists in a combination... | [
40514
] | Train |
17,932 | 16 | Title: A Vision for Cleaner Rivers: Harnessing Snapshot Hyperspectral Imaging to Detect Macro-Plastic Litter
Abstract: Plastic waste entering the riverine harms local ecosystems leading to negative ecological and economic impacts. Large parcels of plastic waste are transported from inland to oceans leading to a global ... | [
20835
] | Test |
17,933 | 27 | Title: Graph-Based Interaction-Aware Multimodal 2D Vehicle Trajectory Prediction using Diffusion Graph Convolutional Networks
Abstract: Predicting vehicle trajectories is crucial for ensuring automated vehicle operation efficiency and safety, particularly on congested multi-lane highways. In such dynamic environments, ... | [
41469
] | Train |
17,934 | 24 | Title: A Lite Fireworks Algorithm with Fractal Dimension Constraint for Feature Selection
Abstract: As the use of robotics becomes more widespread, the huge amount of vision data leads to a dramatic increase in data dimensionality. Although deep learning methods can effectively process these high-dimensional vision dat... | [] | Train |
17,935 | 24 | Title: Learning Choice Functions with Gaussian Processes
Abstract: In consumer theory, ranking available objects by means of preference relations yields the most common description of individual choices. However, preference-based models assume that individuals: (1) give their preferences only between pairs of objects; ... | [] | Train |
17,936 | 24 | Title: Physics-informed Machine Learning for Calibrating Macroscopic Traffic Flow Models
Abstract: Well-calibrated traffic flow models are fundamental to understanding traffic phenomena and designing control strategies. Traditional calibration has been developed base on optimization methods. In this paper, we propose a... | [] | Validation |
17,937 | 16 | Title: An Efficient Convex Hull-Based Vehicle Pose Estimation Method for 3D LiDAR
Abstract: Vehicle pose estimation with LiDAR is essential in the perception technology of autonomous driving. However, due to incomplete observation measurements and sparsity of the LiDAR point cloud, it is challenging to achieve satisfac... | [] | Train |
17,938 | 6 | Title: Next Steps for Human-Centered Generative AI: A Technical Perspective
Abstract: Through iterative, cross-disciplinary discussions, we define and propose next-steps for Human-centered Generative AI (HGAI) from a technical perspective. We contribute a roadmap that lays out future directions of Generative AI spannin... | [
3861,
34074,
15258,
30748,
1065,
9513,
28458,
16556,
42666,
27059,
25786,
35388,
2493,
1094,
846,
19930,
38235,
33120,
31334,
35327
] | Train |
17,939 | 31 | Title: ChatGPT Chemistry Assistant for Text Mining and Prediction of MOF Synthesis
Abstract: We use prompt engineering to guide ChatGPT in the automation of text mining of metal-organic framework (MOF) synthesis conditions from diverse formats and styles of the scientific literature. This effectively mitigates ChatGPT'... | [
6805,
40735
] | Train |
17,940 | 30 | Title: CLaC at SemEval-2023 Task 2: Comparing Span-Prediction and Sequence-Labeling Approaches for NER
Abstract: This paper summarizes the CLaC submission for the MultiCoNER 2 task which concerns the recognition of complex, fine-grained named entities. We compare two popular approaches for NER, namely SequenceLabeling ... | [
36903
] | Validation |
17,941 | 24 | Title: A Comprehensive Survey on Generative Diffusion Models for Structured Data
Abstract: In recent years, generative diffusion models have achieved a rapid paradigm shift in deep generative models by showing groundbreaking performance across various applications. Meanwhile, structured data, encompassing tabular and t... | [
45177,
13219,
28932,
42339,
14214,
42726,
34247,
38377,
684,
24658,
26644,
27257,
42779,
39837
] | Test |
17,942 | 16 | Title: Rethinking matching-based few-shot action recognition
Abstract: Few-shot action recognition, i.e. recognizing new action classes given only a few examples, benefits from incorporating temporal information. Prior work either encodes such information in the representation itself and learns classifiers at test time... | [] | Test |
17,943 | 16 | Title: Enabling Calibration In The Zero-Shot Inference of Large Vision-Language Models
Abstract: Calibration of deep learning models is crucial to their trustworthiness and safe usage, and as such, has been extensively studied in supervised classification models, with methods crafted to decrease miscalibration. However... | [
205,
510
] | Train |
17,944 | 23 | Title: Is unsafe an Achilles' Heel? A Comprehensive Study of Safety Requirements in Unsafe Rust Programming
Abstract: Rust is an emerging, strongly-typed programming language focusing on efficiency and memory safety. With increasing projects adopting Rust, knowing how to use Unsafe Rust is crucial for Rust security. We... | [
11644,
25781
] | Test |
17,945 | 28 | Title: Secrecy Design of Indoor Visible Light Communication Network under Downlink NOMA Transmission
Abstract: In this work, we investigate the transmission sum rate as well as the secrecy sum rate of indoor visible light communication (VLC) networks for mobile devices with the power domain non-orthogonal multiple acce... | [
4137
] | Train |
17,946 | 16 | Title: Multimodal Prompt Learning for Product Title Generation with Extremely Limited Labels
Abstract: Generating an informative and attractive title for the product is a crucial task for e-commerce. Most existing works follow the standard multimodal natural language generation approaches, e.g., image captioning, and e... | [
27704,
27397
] | Test |
17,947 | 16 | Title: AURA : Automatic Mask Generator using Randomized Input Sampling for Object Removal
Abstract: The objective of the image inpainting task is to fill missing regions of an image in a visually plausible way. Recently, deep-learning-based image inpainting networks have generated outstanding results, and some utilize ... | [] | Validation |
17,948 | 33 | Title: Deciding minimal distinguishing DFAs is NP-complete
Abstract: In this paper, we present a proof of the NP-completeness of computing the smallest Deterministic Finite Automaton (DFA) that distinguishes two given regular languages as DFAs. A distinguishing DFA is an automaton that recognizes a language which is a ... | [] | Train |
17,949 | 10 | Title: Measuring Board Game Distance
Abstract: This paper presents a general approach for measuring distances between board games within the Ludii general game system. These distances are calculated using a previously published set of general board game concepts, each of which represents a common game idea or shared pr... | [] | Test |
17,950 | 16 | Title: Hybrid Transformer and CNN Attention Network for Stereo Image Super-resolution
Abstract: Multi-stage strategies are frequently employed in image restoration tasks. While transformer-based methods have exhibited high efficiency in single-image super-resolution tasks, they have not yet shown significant advantages... | [
11891
] | Train |
17,951 | 24 | Title: Are demographically invariant models and representations in medical imaging fair?
Abstract: Medical imaging models have been shown to encode information about patient demographics such as age, race, and sex in their latent representation, raising concerns about their potential for discrimination. Here, we ask wh... | [
3992,
8931,
2053,
4407
] | Train |
17,952 | 30 | Title: Vārta: A Large-Scale Headline-Generation Dataset for Indic Languages
Abstract: We present V\=arta, a large-scale multilingual dataset for headline generation in Indic languages. This dataset includes 41.8 million news articles in 14 different Indic languages (and English), which come from a variety of high-quali... | [
24524,
23615
] | Train |
17,953 | 30 | Title: Interactive Acquisition of Fine-grained Visual Concepts by Exploiting Semantics of Generic Characterizations in Discourse
Abstract: Interactive Task Learning (ITL) concerns learning about unforeseen domain concepts via natural interactions with human users. The learner faces a number of significant constraints: ... | [] | Train |
17,954 | 24 | Title: Improving Resnet-9 Generalization Trained on Small Datasets
Abstract: This paper presents our proposed approach that won the first prize at the ICLR competition on Hardware Aware Efficient Training. The challenge is to achieve the highest possible accuracy in an image classification task in less than 10 minutes.... | [
6260
] | Train |
17,955 | 34 | Title: Maximum Independent Set when excluding an induced minor: K1 + tK2 and tC3 ⊎ C4
Abstract: Dallard, Milani\v{c}, and \v{S}torgel [arXiv '22] ask if for every class excluding a fixed planar graph $H$ as an induced minor, Maximum Independent Set can be solved in polynomial time, and show that this is indeed the case... | [
20006
] | Test |
17,956 | 24 | Title: Deep Ensembles to Improve Uncertainty Quantification of Statistical Downscaling Models under Climate Change Conditions
Abstract: Recently, deep learning has emerged as a promising tool for statistical downscaling, the set of methods for generating high-resolution climate fields from coarse low-resolution variabl... | [] | Test |
17,957 | 28 | Title: Delay-Doppler Domain Tomlinson-Harashima Precoding for OTFS-Based Downlink MU-MIMO Transmissions: Linear Complexity Implementation and Scaling Law Analysis
Abstract: Orthogonal time frequency space (OTFS) modulation is a recently proposed delay-Doppler (DD) domain communication scheme, which has shown promising ... | [
10779,
34430,
41175
] | Train |
17,958 | 30 | Title: Multimodal Multi-Hop Question Answering Through a Conversation Between Tools and Efficiently Finetuned Large Language Models
Abstract: We employ a tool-interacting divide-and-conquer strategy enabling large language models (LLMs) to answer complex multimodal multi-hop questions. In particular, we harness the pow... | [
10624,
14569,
9518,
6963,
33853,
5815,
3609,
634,
35580,
29757,
1854
] | Train |
17,959 | 24 | Title: Toward Understanding Generative Data Augmentation
Abstract: Generative data augmentation, which scales datasets by obtaining fake labeled examples from a trained conditional generative model, boosts classification performance in various learning tasks including (semi-)supervised learning, few-shot learning, and ... | [
33220,
33414,
6957,
10332,
26831,
16827,
12764,
33725
] | Train |
17,960 | 7 | Title: Isogeometric Multi-Resolution Full Waveform Inversion based on the Finite Cell Method
Abstract: Full waveform inversion (FWI) is an iterative identification process that serves to minimize the misfit of model-based simulated and experimentally measured wave field data, with the goal of identifying a field of par... | [] | Train |
17,961 | 16 | Title: SUVR: A Search-based Approach to Unsupervised Visual Representation Learning
Abstract: Unsupervised learning has grown in popularity because of the difficulty of collecting annotated data and the development of modern frameworks that allow us to learn from unlabeled data. Existing studies, however, either disreg... | [] | Train |
17,962 | 16 | Title: Uncovering the Inner Workings of STEGO for Safe Unsupervised Semantic Segmentation
Abstract: Self-supervised pre-training strategies have recently shown impressive results for training general-purpose feature extraction backbones in computer vision. In combination with the Vision Transformer architecture, the DI... | [
31543
] | Validation |
17,963 | 23 | Title: On the Reliability and Explainability of Automated Code Generation Approaches
Abstract: Automatic code generation, the task of generating new code snippets from existing code or comments, has long been of interest. Numerous code generation models have been proposed and proven on different benchmark datasets. How... | [
1200,
30242
] | Test |
17,964 | 3 | Title: A Next-Generation Digital Procurement Workspace Focusing on Information Integration, Automation, Analytics, and Sustainability
Abstract: Recent events such as wars, sanctions, pandemics, and climate change have shown the importance of proper supply network management. A key step in managing supply networks is pr... | [] | Train |
17,965 | 24 | Title: Self-supervised Learning and Graph Classification under Heterophily
Abstract: Self-supervised learning has shown its promising capability in graph representation learning in recent work. Most existing pre-training strategies usually choose the popular Graph neural networks (GNNs), which can be seen as a special ... | [] | Train |
17,966 | 15 | Title: SatIn: Hardware for Boolean Satisfiability Inference
Abstract: This paper describes SatIn, a hardware accelerator for determining boolean satisfiability (SAT) -- an important problem in many domains including verification, security analysis, and planning. SatIn is based on a distributed associative array which p... | [] | Train |
17,967 | 17 | Title: B-rep Matching for Collaborating Across CAD Systems
Abstract: Large Computer-Aided Design (CAD) projects usually require collaboration across many different CAD systems as well as applications that interoperate with them for manufacturing, visualization, or simulation. A fundamental barrier to such collaboration... | [] | Train |
17,968 | 16 | Title: InstructDiffusion: A Generalist Modeling Interface for Vision Tasks
Abstract: We present InstructDiffusion, a unifying and generic framework for aligning computer vision tasks with human instructions. Unlike existing approaches that integrate prior knowledge and pre-define the output space (e.g., categories and ... | [
10624,
37987,
13700,
837,
34982,
26854,
33220,
30243,
20174,
5583,
10706,
29396,
27454
] | Test |
17,969 | 27 | Title: A Fast and Optimal Learning-based Path Planning Method for Planetary Rovers
Abstract: Intelligent autonomous path planning is crucial to improve the exploration efficiency of planetary rovers. In this paper, we propose a learning-based method to quickly search for optimal paths in an elevation map, which is call... | [] | Validation |
17,970 | 16 | Title: Depth and DOF Cues Make A Better Defocus Blur Detector
Abstract: Defocus blur detection (DBD) separates in-focus and out-of-focus regions in an image. Previous approaches mistakenly mistook homogeneous areas in focus for defocus blur regions, likely due to not considering the internal factors that cause defocus ... | [] | Train |
17,971 | 24 | Title: No-Regret Linear Bandits beyond Realizability
Abstract: We study linear bandits when the underlying reward function is not linear. Existing work relies on a uniform misspecification parameter $\epsilon$ that measures the sup-norm error of the best linear approximation. This results in an unavoidable linear regre... | [] | Train |
17,972 | 24 | Title: Differentially Private Neural Tangent Kernels for Privacy-Preserving Data Generation
Abstract: Maximum mean discrepancy (MMD) is a particularly useful distance metric for differentially private data generation: when used with finite-dimensional features it allows us to summarize and privatize the data distributi... | [] | Validation |
17,973 | 16 | Title: LaRS: A Diverse Panoptic Maritime Obstacle Detection Dataset and Benchmark
Abstract: The progress in maritime obstacle detection is hindered by the lack of a diverse dataset that adequately captures the complexity of general maritime environments. We present the first maritime panoptic obstacle detection benchma... | [] | Test |
17,974 | 24 | Title: DiffusAL: Coupling Active Learning with Graph Diffusion for Label-Efficient Node Classification
Abstract: Node classification is one of the core tasks on attributed graphs, but successful graph learning solutions require sufficiently labeled data. To keep annotation costs low, active graph learning focuses on se... | [] | Train |
17,975 | 24 | Title: Weight Prediction Boosts the Convergence of AdamW
Abstract: In this paper, we introduce weight prediction into the AdamW optimizer to boost its convergence when training the deep neural network (DNN) models. In particular, ahead of each mini-batch training, we predict the future weights according to the update r... | [
1561
] | Test |
17,976 | 30 | Title: Faithfulness-Aware Decoding Strategies for Abstractive Summarization
Abstract: Despite significant progress in understanding and improving faithfulness in abstractive summarization, the question of how decoding strategies affect faithfulness is less studied. We present a systematic study of the effect of generat... | [
25409,
30244
] | Train |
17,977 | 16 | Title: Weakly-Supervised Action Localization by Hierarchically-structured Latent Attention Modeling
Abstract: Weakly-supervised action localization aims to recognize and localize action instancese in untrimmed videos with only video-level labels. Most existing models rely on multiple instance learning(MIL), where the p... | [] | Train |
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