node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
values |
|---|---|---|---|---|
44,178 | 30 | Title: Electoral Agitation Dataset: The Use Case of the Polish Election
Abstract: The popularity of social media makes politicians use it for political advertisement. Therefore, social media is full of electoral agitation (electioneering), especially during the election campaigns. The election administration cannot tra... | [] | Train |
44,179 | 16 | Title: Visual Place Recognition with Low-Resolution Images
Abstract: Images incorporate a wealth of information from a robot's surroundings. With the widespread availability of compact cameras, visual information has become increasingly popular for addressing the localisation problem, which is then termed as Visual Pla... | [] | Test |
44,180 | 5 | Title: Evaluating performance and portability of high-level programming models: Julia, Python/Numba, and Kokkos on exascale nodes
Abstract: We explore the performance and portability of the high-level programming models: the LLVM-based Julia and Python/Numba, and Kokkos on high-performance computing (HPC) nodes: AMD Ep... | [
39033,
13418,
32604
] | Train |
44,181 | 27 | Title: Trust-Region Neural Moving Horizon Estimation for Robots
Abstract: Accurate disturbance estimation is essential for safe robot operations. The recently proposed neural moving horizon estimation (NeuroMHE), which uses a portable neural network to model the MHE's weightings, has shown promise in further pushing th... | [] | Train |
44,182 | 16 | Title: VanillaKD: Revisit the Power of Vanilla Knowledge Distillation from Small Scale to Large Scale
Abstract: The tremendous success of large models trained on extensive datasets demonstrates that scale is a key ingredient in achieving superior results. Therefore, the reflection on the rationality of designing knowle... | [
29873,
44260,
35773
] | Train |
44,183 | 6 | Title: Co-Designing Alternatives for the Future of Gig Worker Well-Being: Navigating Multi-Stakeholder Incentives and Preferences
Abstract: Gig workers, and the products and services they provide, play an increasingly ubiquitous role in our daily lives. But despite growing evidence suggesting that worker well-being in ... | [
12113,
42763,
10815
] | Train |
44,184 | 16 | Title: Test-Time Amendment with a Coarse Classifier for Fine-Grained Classification
Abstract: We investigate the problem of reducing mistake severity for fine-grained classification. Fine-grained classification can be challenging, mainly due to the requirement of knowledge or domain expertise for accurate annotation. H... | [] | Test |
44,185 | 24 | Title: Improving Generalization of Adversarial Training via Robust Critical Fine-Tuning
Abstract: Deep neural networks are susceptible to adversarial examples, posing a significant security risk in critical applications. Adversarial Training (AT) is a well-established technique to enhance adversarial robustness, but it... | [] | Train |
44,186 | 34 | Title: A Fair and Memory/Time-efficient Hashmap
Abstract: There is a large amount of work constructing hashmaps to minimize the number of collisions. However, to the best of our knowledge no known hashing technique guarantees group fairness among different groups of items. We are given a set $P$ of $n$ tuples in $\math... | [
26677,
3727
] | Validation |
44,187 | 16 | Title: Retrieving-to-Answer: Zero-Shot Video Question Answering with Frozen Large Language Models
Abstract: Video Question Answering (VideoQA) has been significantly advanced from the scaling of recent Large Language Models (LLMs). The key idea is to convert the visual information into the language feature space so tha... | [
8084,
8733,
7982
] | Train |
44,188 | 24 | Title: Applications of Machine Learning in Detecting Afghan Fake Banknotes
Abstract: Fake currency, unauthorized imitation money lacking government approval, constitutes a form of fraud. Particularly in Afghanistan, the prevalence of fake currency poses significant challenges and detrimentally impacts the economy. Whil... | [] | Train |
44,189 | 30 | Title: Exploring the Feasibility of ChatGPT for Event Extraction
Abstract: Event extraction is a fundamental task in natural language processing that involves identifying and extracting information about events mentioned in text. However, it is a challenging task due to the lack of annotated data, which is expensive an... | [
8450,
24071,
11273,
36233,
25227,
44687,
35611,
5659,
40103,
4779,
39600,
2100,
38849,
36178,
23252,
16598,
8286,
35556,
24422,
22130,
35580
] | Test |
44,190 | 4 | Title: Review of the NIST Light-weight Cryptography Finalists
Abstract: Since 2016, NIST has been assessing lightweight encryption methods, and, in 2022, NIST published the final 10: ASCON, Elephant, GIFT-COFB, Grain128-AEAD, ISAP, Photon-Beetle, Romulus, Sparkle, TinyJambu, and Xoodyak. At the time that the article wa... | [] | Validation |
44,191 | 16 | Title: Language Knowledge-Assisted Representation Learning for Skeleton-Based Action Recognition
Abstract: How humans understand and recognize the actions of others is a complex neuroscientific problem that involves a combination of cognitive mechanisms and neural networks. Research has shown that humans have brain are... | [] | Train |
44,192 | 16 | Title: The Treasure Beneath Multiple Annotations: An Uncertainty-Aware Edge Detector
Abstract: Deep learning-based edge detectors heavily rely on pixel-wise labels which are often provided by multiple annotators. Existing methods fuse multiple annotations using a simple voting process, ignoring the inherent ambiguity o... | [
1228
] | Test |
44,193 | 8 | Title: An Intrusion Detection Mechanism for MANETs Based on Deep Learning Artificial Neural Networks (ANNs)
Abstract: Mobile Ad-hoc Network (MANET) is a distributed, decentralized network of wireless portable nodes connecting directly without any fixed communication base station or centralized administration. Nodes in ... | [] | Train |
44,194 | 4 | Title: Confidential Computing in Edge-Cloud Hierarchy
Abstract: The paper introduces confidential computing approaches focused on protecting hierarchical data within edge-cloud network. Edge-cloud network suggests splitting and sharing data between the main cloud and the range of networks near the endpoint devices. The... | [] | Test |
44,195 | 4 | Title: Training-free Lexical Backdoor Attacks on Language Models
Abstract: Large-scale language models have achieved tremendous success across various natural language processing (NLP) applications. Nevertheless, language models are vulnerable to backdoor attacks, which inject stealthy triggers into models for steering... | [
35170,
38695,
23225,
34076,
13215
] | Test |
44,196 | 5 | Title: Distributed Compressed Sparse Row Format for Spiking Neural Network Simulation, Serialization, and Interoperability
Abstract: With the increasing development of neuromorphic platforms and their related software tools as well as the increasing scale of spiking neural network (SNN) models, there is a pressure for ... | [] | Train |
44,197 | 16 | Title: Ref-Diff: Zero-shot Referring Image Segmentation with Generative Models
Abstract: Zero-shot referring image segmentation is a challenging task because it aims to find an instance segmentation mask based on the given referring descriptions, without training on this type of paired data. Current zero-shot methods m... | [
3015,
6472,
8234,
42221,
15983,
23570,
27508,
28148,
26809,
34074,
4220,
1021,
34943
] | Train |
44,198 | 28 | Title: Adaptive Coding and Modulation Aided Mobile Relaying for Millimeter-Wave Flying Ad-Hoc Networks
Abstract: The emerging drone swarms are capable of carrying out sophisticated tasks in support of demanding Internet-of-Things (IoT) applications by synergistically working together. However, the target area may be ou... | [] | Train |
44,199 | 16 | Title: Learning Multiscale Consistency for Self-supervised Electron Microscopy Instance Segmentation
Abstract: Instance segmentation in electron microscopy (EM) volumes is tough due to complex shapes and sparse annotations. Self-supervised learning helps but still struggles with intricate visual patterns in EM. To addr... | [
43494,
8967,
27817,
2638,
23283
] | Validation |
44,200 | 30 | Title: NAIL: Lexical Retrieval Indices with Efficient Non-Autoregressive Decoders
Abstract: Neural document rerankers are extremely effective in terms of accuracy. However, the best models require dedicated hardware for serving, which is costly and often not feasible. To avoid this serving-time requirement, we present ... | [
3214
] | Validation |
44,201 | 4 | Title: X-Adv: Physical Adversarial Object Attacks against X-ray Prohibited Item Detection
Abstract: Adversarial attacks are valuable for evaluating the robustness of deep learning models. Existing attacks are primarily conducted on the visible light spectrum (e.g., pixel-wise texture perturbation). However, attacks tar... | [
4544,
27260,
32170,
18347,
36875,
13520,
34712,
8665,
4124
] | Train |
44,202 | 23 | Title: Prompt Sapper: A LLM-Empowered Production Tool for Building AI Chains
Abstract: The emergence of foundation models, such as large language models (LLMs) GPT-4 and text-to-image models DALL-E, has opened up numerous possibilities across various domains. People can now use natural language (i.e. prompts) to commun... | [
42024,
36986,
33220,
6958
] | Train |
44,203 | 10 | Title: A Deep Behavior Path Matching Network for Click-Through Rate Prediction
Abstract: User behaviors on an e-commerce app not only contain different kinds of feedback on items but also sometimes imply the cognitive clue of the user’s decision-making. For understanding the psychological procedure behind user decision... | [
4297
] | Test |
44,204 | 24 | Title: Arithmetic Intensity Balancing Convolution for Hardware-aware Efficient Block Design
Abstract: As deep learning advances, edge devices and lightweight neural networks are becoming more important. To reduce latency in the AI accelerator, it's essential to not only reduce FLOPs but also enhance hardware performanc... | [] | Train |
44,205 | 36 | Title: Concave Pro-rata Games
Abstract: In this paper, we introduce a family of games called concave pro-rata games. In such a game, players place their assets into a pool, and the pool pays out some concave function of all assets placed into it. Each player then receives a pro-rata share of the payout; i.e., each play... | [] | Validation |
44,206 | 30 | Title: Complementing GPT-3 with Few-Shot Sequence-to-Sequence Semantic Parsing over Wikidata
Abstract: As the largest knowledge base, Wikidata is a massive source of knowledge, complementing large language models with well-structured data. In this paper, we present WikiWebQuestions, a high-quality knowledge base questi... | [] | Validation |
44,207 | 16 | Title: Optimized Machine Learning for CHD Detection using 3D CNN-based Segmentation, Transfer Learning and Adagrad Optimization
Abstract: Globally, Coronary Heart Disease (CHD) is one of the main causes of death. Early detection of CHD can improve patient outcomes and reduce mortality rates. We propose a novel framewor... | [
5154,
25547,
28036,
10838
] | Test |
44,208 | 16 | Title: Fast Diffusion EM: a diffusion model for blind inverse problems with application to deconvolution
Abstract: Using diffusion models to solve inverse problems is a growing field of research. Current methods assume the degradation to be known and provide impressive results in terms of restoration quality and divers... | [] | Test |
44,209 | 3 | Title: Mitigating the Risk of Knowledge Leakage in Knowledge Intensive Organizations: a Mobile Device Perspective
Abstract: In the current knowledge economy, knowledge represents the most strategically significant resource of organizations. Knowledge-intensive activities advance innovation and create and sustain econom... | [] | Train |
44,210 | 27 | Title: Modelling, Analysis and Control of OmniMorph: an Omnidirectional Morphing Multi-rotor UAV
Abstract: This paper introduces for the first time the design, modelling, and control of a novel morphing multi-rotor Unmanned Aerial Vehicle (UAV) that we call the OmniMorph. The morphing ability allows the selection of th... | [] | Train |
44,211 | 24 | Title: Inducing Neural Collapse in Deep Long-tailed Learning
Abstract: Although deep neural networks achieve tremendous success on various classification tasks, the generalization ability drops sheer when training datasets exhibit long-tailed distributions. One of the reasons is that the learned representations (i.e. f... | [
16411,
1843
] | Test |
44,212 | 6 | Title: Trauma-Informed Social Media: Towards Solutions for Reducing and Healing Online Harm
Abstract: Social media platforms exacerbate trauma, and many users experience various forms of trauma unique to them (e.g., doxxing and swatting). Trauma is the psychological and physical response to experiencing a deeply distur... | [] | Test |
44,213 | 24 | Title: Disentangled Multi-Fidelity Deep Bayesian Active Learning
Abstract: To balance quality and cost, various domain areas of science and engineering run simulations at multiple levels of sophistication. Multi-fidelity active learning aims to learn a direct mapping from input parameters to simulation outputs at the h... | [] | Train |
44,214 | 23 | Title: An Energy-Aware Approach to Design Self-Adaptive AI-based Applications on the Edge
Abstract: The advent of edge devices dedicated to machine learning tasks enabled the execution of AI-based applications that efficiently process and classify the data acquired by the resource-constrained devices populating the Int... | [
11345
] | Train |
44,215 | 24 | Title: MLOps Spanning Whole Machine Learning Life Cycle: A Survey
Abstract: Google AlphaGos win has significantly motivated and sped up machine learning (ML) research and development, which led to tremendous ML technical advances and wider adoptions in various domains (e.g., Finance, Health, Defense, and Education). Th... | [] | Train |
44,216 | 24 | Title: A Theory of Human-Like Few-Shot Learning
Abstract: We aim to bridge the gap between our common-sense few-sample human learning and large-data machine learning. We derive a theory of human-like few-shot learning from von-Neuman-Landauer's principle. modelling human learning is difficult as how people learn varies... | [
8181
] | Train |
44,217 | 31 | Title: Retrieving Supporting Evidence for LLMs Generated Answers
Abstract: Current large language models (LLMs) can exhibit near-human levels of performance on many natural language tasks, including open-domain question answering. Unfortunately, they also convincingly hallucinate incorrect answers, so that responses to... | [
43566,
35580,
38102
] | Train |
44,218 | 30 | Title: Exploring Large Language Models for Knowledge Graph Completion
Abstract: Knowledge graphs play a vital role in numerous artificial intelligence tasks, yet they frequently face the issue of incompleteness. In this study, we explore utilizing Large Language Models (LLM) for knowledge graph completion. We consider ... | [
39600,
40192,
13700
] | Train |
44,219 | 24 | Title: DynaMIX: Resource Optimization for DNN-Based Real-Time Applications on a Multi-Tasking System
Abstract: As deep neural networks (DNNs) prove their importance and feasibility, more and more DNN-based apps, such as detection and classification of objects, have been developed and deployed on autonomous vehicles (AV... | [] | Test |
44,220 | 24 | Title: Geometric Graph Filters and Neural Networks: Limit Properties and Discriminability Trade-offs
Abstract: This paper studies the relationship between a graph neural network (GNN) and a manifold neural network (MNN) when the graph is constructed from a set of points sampled from the manifold, thus encoding geometri... | [] | Test |
44,221 | 31 | Title: COPR: Consistency-Oriented Pre-Ranking for Online Advertising
Abstract: Cascading architecture has been widely adopted in large-scale advertising systems to balance efficiency and effectiveness. In this architecture, the pre-ranking model is expected to be a lightweight approximation of the ranking model, which ... | [] | Test |
44,222 | 6 | Title: Gotta Assess 'Em All: A Risk Analysis of Criminal Offenses Facilitated through PokemonGO
Abstract: Location-based games have come to the forefront of popularity in casual and mobile gaming over the past six years. However, there is no hard data on crimes that these games enable, ranging from assault to cyberstal... | [] | Validation |
44,223 | 24 | Title: Async-HFL: Efficient and Robust Asynchronous Federated Learning in Hierarchical IoT Networks
Abstract: Federated Learning (FL) has gained increasing interest in recent years as a distributed on-device learning paradigm. However, multiple challenges remain to be addressed for deploying FL in real-world Internet-o... | [] | Train |
44,224 | 30 | Title: How word semantics and phonology affect handwriting of Alzheimer's patients: a machine learning based analysis
Abstract: Using kinematic properties of handwriting to support the diagnosis of neurodegenerative disease is a real challenge: non-invasive detection techniques combined with machine learning approaches... | [] | Test |
44,225 | 27 | Title: Reward Shaping for Building Trustworthy Robots in Sequential Human-Robot Interaction
Abstract: Trust-aware human-robot interaction (HRI) has received increasing research attention, as trust has been shown to be a crucial factor for effective HRI. Research in trust-aware HRI discovered a dilemma -- maximizing tas... | [
18926
] | Validation |
44,226 | 37 | Title: Efficient Computation of Quantiles over Joins
Abstract: We present efficient algorithms for Quantile Join Queries, abbreviated as %JQ. A %JQ asks for the answer at a specified relative position (e.g., 50% for the median) under some ordering over the answers to a Join Query (JQ). Our goal is to avoid materializin... | [] | Train |
44,227 | 3 | Title: Auditing Recommender Systems - Putting the DSA into practice with a risk-scenario-based approach
Abstract: Today's online platforms rely heavily on recommendation systems to serve content to their users; social media is a prime example. In turn, recommendation systems largely depend on artificial intelligence al... | [] | Train |
44,228 | 24 | Title: Distributionally Robust Model-based Reinforcement Learning with Large State Spaces
Abstract: Three major challenges in reinforcement learning are the complex dynamical systems with large state spaces, the costly data acquisition processes, and the deviation of real-world dynamics from the training environment de... | [] | Test |
44,229 | 16 | Title: Age-Invariant Face Embedding using the Wasserstein Distance
Abstract: In this work, we study face verification in datasets where images of the same individuals exhibit significant age differences. This poses a major challenge for current face recognition and verification techniques. To address this issue, we pro... | [] | Test |
44,230 | 24 | Title: FedGH: Heterogeneous Federated Learning with Generalized Global Header
Abstract: Federated learning (FL) is an emerging machine learning paradigm that allows multiple parties to train a shared model collaboratively in a privacy-preserving manner. Existing horizontal FL methods generally assume that the FL server... | [
8700,
40982
] | Train |
44,231 | 16 | Title: DocDiff: Document Enhancement via Residual Diffusion Models
Abstract: Removing degradation from document images not only improves their visual quality and readability, but also enhances the performance of numerous automated document analysis and recognition tasks. However, existing regression-based methods optim... | [
3844,
32909
] | Train |
44,232 | 6 | Title: Improving Human-AI Collaboration With Descriptions of AI Behavior
Abstract: People work with AI systems to improve their decision making, but often under- or over-rely on AI predictions and perform worse than they would have unassisted. To help people appropriately rely on AI aids, we propose showing them behavi... | [
29170,
18515,
16439
] | Train |
44,233 | 28 | Title: NOMA-based Improper Signaling for MIMO STAR-RIS-assisted Broadcast Channels with Hardware Impairments
Abstract: This paper proposes schemes to improve the spectral efficiency of a multiple-input multiple-output (MIMO) broadcast channel (BC) with I/Q imbalance (IQI) at transceivers by employing a combination of i... | [
20602,
23331,
20788,
2533
] | Train |
44,234 | 4 | Title: Improvise, Adapt, Overcome: Dynamic Resiliency Against Unknown Attack Vectors in Microgrid Cybersecurity Games
Abstract: Cyber-physical microgrids are vulnerable to rootkit attacks that manipulate system dynamics to create instabilities in the network. Rootkits tend to hide their access level within microgrid sy... | [
39221
] | Test |
44,235 | 24 | Title: Self-Compatibility: Evaluating Causal Discovery without Ground Truth
Abstract: As causal ground truth is incredibly rare, causal discovery algorithms are commonly only evaluated on simulated data. This is concerning, given that simulations reflect common preconceptions about generating processes regarding noise ... | [] | Train |
44,236 | 28 | Title: How Costly Was That (In)Decision?
Abstract: In this paper, we introduce a new metric, named Penalty upon Decision (PuD), for measuring the impact of communication delays and state changes at the source on a remote decision maker. Specifically, the metric quantifies the performance degradation at the decision mak... | [] | Train |
44,237 | 2 | Title: Decidable (Ac)counting with Parikh and Muller: Adding Presburger Arithmetic to Monadic Second-Order Logic over Tree-Interpretable Structures
Abstract: We propose $\omega$MSO$\Join$BAPA, an expressive logic for describing countable structures, which subsumes and transcends both Counting Monadic Second-Order Logic... | [
27393,
17166
] | Train |
44,238 | 16 | Title: Multi-Modal Classifiers for Open-Vocabulary Object Detection
Abstract: The goal of this paper is open-vocabulary object detection (OVOD) $\unicode{x2013}$ building a model that can detect objects beyond the set of categories seen at training, thus enabling the user to specify categories of interest at inference ... | [] | Train |
44,239 | 16 | Title: TransNet: A Transfer Learning-Based Network for Human Action Recognition
Abstract: Human action recognition (HAR) is a high-level and significant research area in computer vision due to its ubiquitous applications. The main limitations of the current HAR models are their complex structures and lengthy training t... | [
14207
] | Test |
44,240 | 24 | Title: Towards Learning Rubik's Cube with N-tuple-based Reinforcement Learning
Abstract: This work describes in detail how to learn and solve the Rubik's cube game (or puzzle) in the General Board Game (GBG) learning and playing framework. We cover the cube sizes 2x2x2 and 3x3x3. We describe in detail the cube's state ... | [] | Train |
44,241 | 36 | Title: Contract-Based Distributed Synthesis in Two-Objective Parity Games
Abstract: We present a novel method to compute $\textit{assume-guarantee contracts}$ in non-zerosum two-player games over finite graphs where each player has a different $ \omega $-regular winning condition. Given a game graph $G$ and two parity ... | [
1013,
45237
] | Validation |
44,242 | 34 | Title: Space-Efficient Parameterized Algorithms on Graphs of Low Shrubdepth
Abstract: Dynamic programming on various graph decompositions is one of the most fundamental techniques used in parameterized complexity. Unfortunately, even if we consider concepts as simple as path or tree decompositions, such dynamic program... | [
30984,
34454
] | Test |
44,243 | 2 | Title: 'Put the Car on the Stand': SMT-based Oracles for Investigating Decisions
Abstract: Principled accountability in the aftermath of harms is essential to the trustworthy design and governance of algorithmic decision making. Legal philosophy offers a paramount method for assessing culpability: putting the agent 'on... | [
35460
] | Validation |
44,244 | 24 | Title: Neuro Symbolic Continual Learning: Knowledge, Reasoning Shortcuts and Concept Rehearsal
Abstract: We introduce Neuro-Symbolic Continual Learning, where a model has to solve a sequence of neuro-symbolic tasks, that is, it has to map sub-symbolic inputs to high-level concepts and compute predictions by reasoning c... | [
15496,
8613
] | Validation |
44,245 | 25 | Title: Heterogeneous Graph Learning for Acoustic Event Classification
Abstract: Heterogeneous graphs provide a compact, efficient, and scalable way to model data involving multiple disparate modalities. This makes modeling audiovisual data using heterogeneous graphs an attractive option. However, graph structure does n... | [] | Train |
44,246 | 24 | Title: Mathematical Capabilities of ChatGPT
Abstract: We investigate the mathematical capabilities of two iterations of ChatGPT (released 9-January-2023 and 30-January-2023) and of GPT-4 by testing them on publicly available datasets, as well as hand-crafted ones, using a novel methodology. In contrast to formal mathem... | [
39170,
20739,
39554,
44419,
6535,
3977,
11273,
5643,
18059,
35465,
14606,
19727,
38543,
38162,
24467,
10262,
22042,
7964,
45342,
16032,
7585,
19232,
44323,
28580,
16166,
6061,
1326,
43566,
31924,
36025,
12602,
1595,
16827,
21820,
8894,
3518,
23... | Train |
44,247 | 16 | Title: Cross-modal Orthogonal High-rank Augmentation for RGB-Event Transformer-trackers
Abstract: This paper addresses the problem of cross-modal object tracking from RGB videos and event data. Rather than constructing a complex cross-modal fusion network, we explore the great potential of a pre-trained vision Transfor... | [
21962
] | Validation |
44,248 | 16 | Title: Deep Learning-Based UAV Aerial Triangulation without Image Control Points
Abstract: : The emerging drone aerial survey has the advantages of low cost, high efficiency, and flexible use. However, UAVs are often equipped with cheap POS systems and non-measurement cameras, and their flight attitudes are easily affe... | [] | Test |
44,249 | 2 | Title: Tackling Universal Properties of Minimal Trap Spaces of Boolean Networks
Abstract: Minimal trap spaces (MTSs) capture subspaces in which the Boolean dynamics is trapped, whatever the update mode. They correspond to the attractors of the most permissive mode. Due to their versatility, the computation of MTSs has ... | [] | Train |
44,250 | 17 | Title: Animating explosions
Abstract: In this paper, we introduce techniques for animating explosions and their effects. The primary effect of an explosion is a disturbance that causes a shock wave to propagate through the surrounding medium. The disturbance determines the behavior of nearly all other secondary effects... | [
29345
] | Validation |
44,251 | 24 | Title: TensorBank: Tensor Lakehouse for Foundation Model Training
Abstract: Storing and streaming high dimensional data for foundation model training became a critical requirement with the rise of foundation models beyond natural language. In this paper we introduce TensorBank, a petabyte scale tensor lakehouse capable... | [] | Test |
44,252 | 27 | Title: CEMSSL: A Unified Framework for Multi-Solution Inverse Kinematic Model Learning of Robot Arms with High-Precision Manipulation
Abstract: Multiple solutions mainly originate from the existence of redundant degrees of freedom in the robot arm, which may cause difficulties in inverse model learning but they can als... | [
34265
] | Train |
44,253 | 30 | Title: Stack Over-Flowing with Results: The Case for Domain-Specific Pre-Training Over One-Size-Fits-All Models
Abstract: Large pre-trained neural language models have brought immense progress to both NLP and software engineering. Models in OpenAI's GPT series now dwarf Google's BERT and Meta's RoBERTa, which previousl... | [] | Test |
44,254 | 6 | Title: On Video Game Balancing: Joining Player- and Data-Driven Analytics
Abstract: Balancing is, especially among players, a highly debated topic of video games. Whether a game is sufficiently balanced greatly influences its reception, player satisfaction, churn rates and success. Yet, conceptions about the definition... | [] | Train |
44,255 | 16 | Title: Using simulation to quantify the performance of automotive perception systems
Abstract: The design and evaluation of complex systems can benefit from a software simulation - sometimes called a digital twin. The simulation can be used to characterize system performance or to test its performance under conditions ... | [] | Validation |
44,256 | 18 | Title: Powering AI at the Edge: A Robust, Memristor-based Binarized Neural Network with Near-Memory Computing and Miniaturized Solar Cell
Abstract: Memristor-based neural networks provide an exceptional energy-efficient platform for artificial intelligence (AI), presenting the possibility of self-powered operation when... | [] | Train |
44,257 | 16 | Title: Contrastive Bi-Projector for Unsupervised Domain Adaption
Abstract: This paper proposes a novel unsupervised domain adaption (UDA) method based on contrastive bi-projector (CBP), which can improve the existing UDA methods. It is called CBPUDA here, which effectively promotes the feature extractors (FEs) to reduc... | [] | Test |
44,258 | 10 | Title: Learning in Factored Domains with Information-Constrained Visual Representations
Abstract: Humans learn quickly even in tasks that contain complex visual information. This is due in part to the efficient formation of compressed representations of visual information, allowing for better generalization and robustn... | [] | Test |
44,259 | 28 | Title: Rate-Splitting with Hybrid Messages: DoF Analysis of the Two-User MIMO Broadcast Channel with Imperfect CSIT
Abstract: Most of the existing research on degrees-of-freedom (DoF) with imperfect channel state information at the transmitter (CSIT) assume the messages are private, which may not reflect reality as the... | [
32194
] | Test |
44,260 | 16 | Title: NORM: Knowledge Distillation via N-to-One Representation Matching
Abstract: Existing feature distillation methods commonly adopt the One-to-one Representation Matching between any pre-selected teacher-student layer pair. In this paper, we present N-to-One Representation (NORM), a new two-stage knowledge distilla... | [
43042,
9251,
35947,
8940,
5748,
44182
] | Validation |
44,261 | 30 | Title: Generalized Multiple Intent Conditioned Slot Filling
Abstract: Natural language understanding includes the tasks of intent detection (identifying a user's objectives) and slot filling (extracting the entities relevant to those objectives). Prior slot filling methods assume that each intent type cannot occur more... | [] | Train |
44,262 | 30 | Title: Using n-aksaras to model Sanskrit and Sanskrit-adjacent texts
Abstract: Despite — or perhaps because of — their simplicity, n-grams, or contiguous sequences of tokens, have been used with great success in computational linguistics since their introduction in the late 20 th century. Recast as k-mers, or contiguou... | [] | Validation |
44,263 | 16 | Title: Structural Multiplane Image: Bridging Neural View Synthesis and 3D Reconstruction
Abstract: The Multiplane Image (MPI), containing a set of fronto-parallel $RGB_{\alpha}$ layers, is an effective and efficient representation for view synthesis from sparse inputs. Yet, its fixed structure limits the performance, e... | [] | Train |
44,264 | 28 | Title: Bit-Interleaved Multiple Access: Improved Fairness, Reliability, and Latency for Massive IoT Networks
Abstract: Internet of Things (IoT) networks require massive connections in dense areas. Therefore, a resource-efficient multiple access scheme seems inevitable to enable immense connectivity where multiple devic... | [] | Test |
44,265 | 27 | Title: Online Monocular Lane Mapping Using Catmull-Rom Spline
Abstract: In this study, we introduce an online monocular lane mapping approach that solely relies on a single camera and odometry for generating spline-based maps. Our proposed technique models the lane association process as an assignment issue utilizing a... | [
33251
] | Train |
44,266 | 24 | Title: Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation
Abstract: Good data augmentation is one of the key factors that lead to the empirical success of self-supervised representation learning such as contrastive learning and masked language modeling, yet theoretical under... | [
17872,
31074,
34413,
12070
] | Train |
44,267 | 27 | Title: RAMP: Reaction-Aware Motion Planning of Multi-Legged Robots for Locomotion in Microgravity
Abstract: Robotic mobility in microgravity is necessary to expand human utilization and exploration of outer space. Bio-inspired multi-legged robots are a possible solution for safe and precise locomotion. However, a dynam... | [
5127
] | Test |
44,268 | 24 | Title: Bayesian Federated Learning: A Survey
Abstract: Federated learning (FL) demonstrates its advantages in integrating distributed infrastructure, communication, computing and learning in a privacy-preserving manner. However, the robustness and capabilities of existing FL methods are challenged by limited and dynami... | [
20708,
44838,
19018,
36889,
28541
] | Train |
44,269 | 30 | Title: Error Detection for Text-to-SQL Semantic Parsing
Abstract: Despite remarkable progress in text-to-SQL semantic parsing in recent years, the performance of existing parsers is still far from perfect. At the same time, modern deep learning based text-to-SQL parsers are often over-confident and thus casting doubt o... | [
9060,
37957
] | Test |
44,270 | 24 | Title: Discounted Thompson Sampling for Non-Stationary Bandit Problems
Abstract: Non-stationary multi-armed bandit (NS-MAB) problems have recently received significant attention. NS-MAB are typically modelled in two scenarios: abruptly changing, where reward distributions remain constant for a certain period and change... | [] | Train |
44,271 | 6 | Title: Drive Right: Promoting Autonomous Vehicle Education Through an Integrated Simulation Platform
Abstract: Autonomous vehicles (AVs) are being rapidly introduced into our lives. However, public misunderstanding and mistrust have become prominent issues hindering the acceptance of these driverless technologies. The ... | [] | Train |
44,272 | 30 | Title: ImpressionGPT: An Iterative Optimizing Framework for Radiology Report Summarization with ChatGPT
Abstract: The 'Impression' section of a radiology report is a critical basis for communication between radiologists and other physicians, and it is typically written by radiologists based on the 'Findings' section. H... | [
45505,
20355,
17349,
45189,
36263,
3624,
11273,
18858,
21928,
31147,
40136,
7057,
16471,
23512,
3034,
7996,
23230,
1151
] | Validation |
44,273 | 16 | Title: GaitEditer: Attribute Editing for Gait Representation Learning
Abstract: Gait pattern is a promising biometric for applications, as it can be captured from a distance without requiring individual cooperation. Nevertheless, existing gait datasets typically suffer from limited diversity, with indoor datasets requi... | [] | Test |
44,274 | 24 | Title: Transferable Energy Storage Bidder
Abstract: Energy storage resources must consider both price uncertainties and their physical operating characteristics when participating in wholesale electricity markets. This is a challenging problem as electricity prices are highly volatile, and energy storage has efficiency... | [] | Train |
44,275 | 11 | Title: A Dynamic Heterogeneous Team-based Non-iterative Approach for Online Pick-up and Just-In-Time Delivery Problems
Abstract: This paper presents a non-iterative approach for finding the assignment of heterogeneous robots to efficiently execute online Pickup and Just-In-Time Delivery (PJITD) tasks with optimal resou... | [
24498
] | Train |
44,276 | 30 | Title: Evaluating end-to-end entity linking on domain-specific knowledge bases: Learning about ancient technologies from museum collections
Abstract: To study social, economic, and historical questions, researchers in the social sciences and humanities have started to use increasingly large unstructured textual dataset... | [] | Validation |
44,277 | 13 | Title: 1D Convolutional neural networks and machine learning algorithms for spectral data classification with a case study for Covid-19
Abstract: Machine and deep learning algorithms have increasingly been applied to solve problems in various areas of knowledge. Among these areas, Chemometrics has been benefited from t... | [] | Train |
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