node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
values |
|---|---|---|---|---|
44,678 | 10 | Title: Enabling A Network AI Gym for Autonomous Cyber Agents
Abstract: This work aims to enable autonomous agents for network cyber operations (CyOps) by applying reinforcement and deep reinforcement learning (RL/DRL). The required RL training environment is particularly challenging, as it must balance the need for hig... | [
36550
] | Train |
44,679 | 30 | Title: Making More of Little Data: Improving Low-Resource Automatic Speech Recognition Using Data Augmentation
Abstract: The performance of automatic speech recognition (ASR) systems has advanced substantially in recent years, particularly for languages for which a large amount of transcribed speech is available. Unfor... | [
39192,
3827,
17182
] | Test |
44,680 | 31 | Title: Counterfactual Editing for Search Result Explanation
Abstract: Recently substantial improvements in neural retrieval methods also bring to light the inherent blackbox nature of these methods, especially when viewed from an explainability perspective. Most of existing works on Search Result Explanation (SeRE) are... | [] | Train |
44,681 | 16 | Title: PanoGRF: Generalizable Spherical Radiance Fields for Wide-baseline Panoramas
Abstract: Achieving an immersive experience enabling users to explore virtual environments with six degrees of freedom (6DoF) is essential for various applications such as virtual reality (VR). Wide-baseline panoramas are commonly used ... | [
29000,
9706,
23014
] | Train |
44,682 | 24 | Title: Meta-prediction Model for Distillation-Aware NAS on Unseen Datasets
Abstract: Distillation-aware Neural Architecture Search (DaNAS) aims to search for an optimal student architecture that obtains the best performance and/or efficiency when distilling the knowledge from a given teacher model. Previous DaNAS metho... | [] | Train |
44,683 | 25 | Title: Exploiting Time-Frequency Conformers for Music Audio Enhancement
Abstract: With the proliferation of video platforms on the internet, recording musical performances by mobile devices has become commonplace. However, these recordings often suffer from degradation such as noise and reverberation, which negatively ... | [] | Train |
44,684 | 27 | Title: ARCOR2: Framework for Collaborative End-User Management of Industrial Robotic Workplaces using Augmented Reality
Abstract: This paper presents a novel framework enabling end-users to perform the management of complex robotic workplaces using a tablet and augmented reality. The framework allows users to commissio... | [] | Train |
44,685 | 30 | Title: Quantifying the perceptual value of lexical and non-lexical channels in speech
Abstract: Speech is a fundamental means of communication that can be seen to provide two channels for transmitting information: the lexical channel of which words are said, and the non-lexical channel of how they are spoken. Both chan... | [] | Train |
44,686 | 2 | Title: Forward LTLf Synthesis: DPLL At Work
Abstract: This paper proposes a new AND-OR graph search framework for synthesis of Linear Temporal Logic on finite traces (\LTLf), that overcomes some limitations of previous approaches. Within such framework, we devise a procedure inspired by the Davis-Putnam-Logemann-Lovela... | [
20817,
26701
] | Train |
44,687 | 30 | Title: EvEval: A Comprehensive Evaluation of Event Semantics for Large Language Models
Abstract: Events serve as fundamental units of occurrence within various contexts. The processing of event semantics in textual information forms the basis of numerous natural language processing (NLP) applications. Recent studies ha... | [
35427,
13700,
35580,
36923,
16556,
23252,
31189,
16598,
12602,
18427,
13564,
44189,
3967
] | Test |
44,688 | 16 | Title: Instance-Level Few-Shot Learning With Class Hierarchy Mining
Abstract: Few-shot learning is proposed to tackle the problem of scarce training data in novel classes. However, prior works in instance-level few-shot learning have paid less attention to effectively utilizing the relationship between categories. In t... | [
28598
] | Train |
44,689 | 11 | Title: Attrition-Aware Adaptation for Multi-Agent Patrolling
Abstract: Multi-agent patrolling is a key problem in a variety of domains such as intrusion detection, area surveillance, and policing which involves repeated visits by a group of agents to specified points in an environment. While the problem is well-studied... | [
7304
] | Validation |
44,690 | 24 | Title: When MiniBatch SGD Meets SplitFed Learning: Convergence Analysis and Performance Evaluation
Abstract: Federated learning (FL) enables collaborative model training across distributed clients (e.g., edge devices) without sharing raw data. Yet, FL can be computationally expensive as the clients need to train the en... | [] | Train |
44,691 | 24 | Title: Multi-modal Graph Learning over UMLS Knowledge Graphs
Abstract: Clinicians are increasingly looking towards machine learning to gain insights about patient evolutions. We propose a novel approach named Multi-Modal UMLS Graph Learning (MMUGL) for learning meaningful representations of medical concepts using graph... | [
42238
] | Train |
44,692 | 16 | Title: AdPE: Adversarial Positional Embeddings for Pretraining Vision Transformers via MAE+
Abstract: Unsupervised learning of vision transformers seeks to pretrain an encoder via pretext tasks without labels. Among them is the Masked Image Modeling (MIM) aligned with pretraining of language transformers by predicting ... | [] | Validation |
44,693 | 16 | Title: Learning Feature Matching via Matchable Keypoint-Assisted Graph Neural Network
Abstract: Accurately matching local features between a pair of images is a challenging computer vision task. Previous studies typically use attention based graph neural networks (GNNs) with fully-connected graphs over keypoints within... | [
3240
] | Validation |
44,694 | 16 | Title: UniDiff: Advancing Vision-Language Models with Generative and Discriminative Learning
Abstract: Recent advances in vision-language pre-training have enabled machines to perform better in multimodal object discrimination (e.g., image-text semantic alignment) and image synthesis (e.g., text-to-image generation). O... | [] | Train |
44,695 | 30 | Title: Dreams Are More "Predictable" Than You Think
Abstract: A consistent body of evidence suggests that dream reports significantly vary from other types of textual transcripts with respect to semantic content. Furthermore, it appears to be a widespread belief in the dream/sleep research community that dream reports ... | [] | Test |
44,696 | 30 | Title: ViDeBERTa: A powerful pre-trained language model for Vietnamese
Abstract: This paper presents ViDeBERTa, a new pre-trained monolingual language model for Vietnamese, with three versions - ViDeBERTa_xsmall, ViDeBERTa_base, and ViDeBERTa_large, which are pre-trained on a large-scale corpus of high-quality and dive... | [] | Test |
44,697 | 3 | Title: Artificial Influence: An Analysis Of AI-Driven Persuasion
Abstract: Persuasion is a key aspect of what it means to be human, and is central to business, politics, and other endeavors. Advancements in artificial intelligence (AI) have produced AI systems that are capable of persuading humans to buy products, watc... | [
17248,
28896,
33220,
18764,
35927,
17980
] | Validation |
44,698 | 34 | Title: The Leafed Induced Subtree in chordal and bounded treewidth graphs
Abstract: In the Fully Leafed Induced Subtrees, one is given a graph $G$ and two integers $a$ and $b$ and the question is to find an induced subtree of $G$ with $a$ vertices and at least $b$ leaves. This problem is known to be NP-complete even wh... | [] | Test |
44,699 | 3 | Title: Towards High-Value Datasets determination for data-driven development: a systematic literature review
Abstract: The OGD is seen as a political and socio-economic phenomenon that promises to promote civic engagement and stimulate public sector innovations in various areas of public life. To bring the expected ben... | [] | Train |
44,700 | 30 | Title: The Gender-GAP Pipeline: A Gender-Aware Polyglot Pipeline for Gender Characterisation in 55 Languages
Abstract: Gender biases in language generation systems are challenging to mitigate. One possible source for these biases is gender representation disparities in the training and evaluation data. Despite recent p... | [
33220,
13700,
45294,
29396,
43641
] | Train |
44,701 | 24 | Title: Fairness-aware Message Passing for Graph Neural Networks
Abstract: Graph Neural Networks (GNNs) have shown great power in various domains. However, their predictions may inherit societal biases on sensitive attributes, limiting their adoption in real-world applications. Although many efforts have been taken for ... | [
35507,
263
] | Validation |
44,702 | 11 | Title: Leveraging Human Feedback to Evolve and Discover Novel Emergent Behaviors in Robot Swarms
Abstract: Robot swarms often exhibit emergent behaviors that are fascinating to observe; however, it is often difficult to predict what swarm behaviors can emerge under a given set of agent capabilities. We seek to efficien... | [] | Test |
44,703 | 1 | Title: Aparecium: Revealing Secrets from Physical Photographs
Abstract: Watermarking is a crucial tool for safeguarding copyrights and can serve as a more aesthetically pleasing alternative to QR codes. In recent years, watermarking methods based on deep learning have proved superior robustness against complex physical... | [] | Train |
44,704 | 16 | Title: Dynamic Token-Pass Transformers for Semantic Segmentation
Abstract: Vision transformers (ViT) usually extract features via forwarding all the tokens in the self-attention layers from top to toe. In this paper, we introduce dynamic token-pass vision transformers (DoViT) for semantic segmentation, which can adapti... | [] | Train |
44,705 | 30 | Title: Incorporating Distributions of Discourse Structure for Long Document Abstractive Summarization
Abstract: For text summarization, the role of discourse structure is pivotal in discerning the core content of a text. Regrettably, prior studies on incorporating Rhetorical Structure Theory (RST) into transformer-base... | [
5346,
631
] | Validation |
44,706 | 16 | Title: Improving neural network representations using human similarity judgments
Abstract: Deep neural networks have reached human-level performance on many computer vision tasks. However, the objectives used to train these networks enforce only that similar images are embedded at similar locations in the representatio... | [
18581
] | Validation |
44,707 | 16 | Title: Segment Anything in 3D with NeRFs
Abstract: Recently, the Segment Anything Model (SAM) emerged as a powerful vision foundation model which is capable to segment anything in 2D images. This paper aims to generalize SAM to segment 3D objects. Rather than replicating the data acquisition and annotation procedure wh... | [
12704,
17633,
11551,
27144,
35263,
13674,
43626,
31345,
13876,
38612,
44854,
41400,
16735
] | Test |
44,708 | 16 | Title: An X3D Neural Network Analysis for Runner’s Performance Assessment in a Wild Sporting Environment
Abstract: We present a transfer learning analysis on a sporting environment of the expanded 3D (X3D) neural networks. Inspired by action quality assessment methods in the literature, our method uses an action recogn... | [] | Train |
44,709 | 24 | Title: Analyzing Impact of Socio-Economic Factors on COVID-19 Mortality Prediction Using SHAP Value
Abstract: This paper applies multiple machine learning (ML) algorithms to a dataset of de-identified COVID-19 patients provided by the COVID-19 Research Database. The dataset consists of 20,878 COVID-positive patients, a... | [] | Test |
44,710 | 30 | Title: Multi-Modality Multi-Loss Fusion Network
Abstract: In this work we investigate the optimal selection and fusion of features across multiple modalities and combine these in a neural network to improve emotion detection. We compare different fusion methods and examine the impact of multi-loss training within the m... | [
16848
] | Train |
44,711 | 16 | Title: MMoT: Mixture-of-Modality-Tokens Transformer for Composed Multimodal Conditional Image Synthesis
Abstract: Existing multimodal conditional image synthesis (MCIS) methods generate images conditioned on any combinations of various modalities that require all of them must be exactly conformed, hindering the synthes... | [
42137,
34074,
11820,
15983
] | Validation |
44,712 | 5 | Title: Efficient Intra-Rack Resource Disaggregation for HPC Using Co-Packaged DWDM Photonics
Abstract: The diversity of workload requirements and increasing hardware heterogeneity in emerging high performance computing (HPC) systems motivate resource disaggregation. Resource disaggregation allows compute and memory res... | [
38227,
45436
] | Train |
44,713 | 34 | Title: List 3-Coloring on Comb-Convex and Caterpillar-Convex Bipartite Graphs
Abstract: Given a graph $G=(V, E)$ and a list of available colors $L(v)$ for each vertex $v\in V$, where $L(v) \subseteq \{1, 2, \ldots, k\}$, List $k$-Coloring refers to the problem of assigning colors to the vertices of $G$ so that each ver... | [] | Train |
44,714 | 24 | Title: Adaptive Policy Learning to Additional Tasks
Abstract: This paper develops a policy learning method for tuning a pre-trained policy to adapt to additional tasks without altering the original task. A method named Adaptive Policy Gradient (APG) is proposed in this paper, which combines Bellman's principle of optim... | [] | Train |
44,715 | 24 | Title: Marginalized Importance Sampling for Off-Environment Policy Evaluation
Abstract: Reinforcement Learning (RL) methods are typically sample-inefficient, making it challenging to train and deploy RL-policies in real world robots. Even a robust policy trained in simulation, requires a real-world deployment to assess... | [
40912
] | Validation |
44,716 | 24 | Title: Learning Sparse Neural Networks with Identity Layers
Abstract: The sparsity of Deep Neural Networks is well investigated to maximize the performance and reduce the size of overparameterized networks as possible. Existing methods focus on pruning parameters in the training process by using thresholds and metrics.... | [] | Train |
44,717 | 24 | Title: A Scale-Invariant Task Balancing Approach for Multi-Task Learning
Abstract: Multi-task learning (MTL), a learning paradigm to learn multiple related tasks simultaneously, has achieved great success in various fields. However, task-balancing remains a significant challenge in MTL, with the disparity in loss/gradi... | [
13280
] | Train |
44,718 | 16 | Title: Salient Sign Detection In Safe Autonomous Driving: AI Which Reasons Over Full Visual Context
Abstract: Detecting road traffic signs and accurately determining how they can affect the driver’s future actions is a critical task for safe autonomous driving systems. However, various traffic signs in a driving scene ... | [
5336,
14146
] | Validation |
44,719 | 24 | Title: Fair Off-Policy Learning from Observational Data
Abstract: Businesses and organizations must ensure that their algorithmic decision-making is fair in order to meet legislative, ethical, and societal demands. For example, decision-making in automated hiring must not discriminate with respect to gender or race. To... | [] | Train |
44,720 | 16 | Title: End-to-end Face-swapping via Adaptive Latent Representation Learning
Abstract: Taking full advantage of the excellent performance of StyleGAN, style transfer-based face swapping methods have been extensively investigated recently. However, these studies require separate face segmentation and blending modules for... | [] | Train |
44,721 | 24 | Title: EEG-based Cognitive Load Classification using Feature Masked Autoencoding and Emotion Transfer Learning
Abstract: Cognitive load, the amount of mental effort required for task completion, plays an important role in performance and decision-making outcomes, making its classification and analysis essential in vari... | [
15481,
6734
] | Validation |
44,722 | 31 | Title: Confidence Ranking for CTR Prediction
Abstract: Model evolution and data updating are two common phenomena in large-scale real-world machine learning applications, e.g. ads and recommendation systems. To adapt, the real-world system typically retrain with all available data and online learn with recently availab... | [] | Validation |
44,723 | 24 | Title: BatMan-CLR: Making Few-shots Meta-Learners Resilient Against Label Noise
Abstract: The negative impact of label noise is well studied in classical supervised learning yet remains an open research question in meta-learning. Meta-learners aim to adapt to unseen learning tasks by learning a good initial model in me... | [] | Train |
44,724 | 5 | Title: Architecting Peer-to-Peer Serverless Distributed Machine Learning Training for Improved Fault Tolerance
Abstract: Distributed Machine Learning refers to the practice of training a model on multiple computers or devices that can be called nodes. Additionally, serverless computing is a new paradigm for cloud compu... | [] | Validation |
44,725 | 16 | Title: SPColor: Semantic Prior Guided Exemplar-based Image Colorization
Abstract: Exemplar-based image colorization aims to colorize a target grayscale image based on a color reference image, and the key is to establish accurate pixel-level semantic correspondence between these two images. Previous methods search for c... | [] | Validation |
44,726 | 16 | Title: Text2Room: Extracting Textured 3D Meshes from 2D Text-to-Image Models
Abstract: We present Text2Room, a method for generating room-scale textured 3D meshes from a given text prompt as input. To this end, we leverage pre-trained 2D text-to-image models to synthesize a sequence of images from different poses. In o... | [
13186,
15886,
34074,
28827,
39340,
19757,
16697,
7993,
37692,
40256,
26825,
5580,
4559,
6488,
40667,
21212,
30566,
38374,
2921,
34167
] | Train |
44,727 | 30 | Title: Gender-specific Machine Translation with Large Language Models
Abstract: Decoder-only Large Language Models (LLMs) have demonstrated potential in machine translation (MT), albeit with performance slightly lagging behind traditional encoder-decoder Neural Machine Translation (NMT) systems. However, LLMs offer a u... | [
14368,
15907,
31493,
32744,
27340,
45294,
3795,
24150,
43641,
1789,
15358,
43327
] | Test |
44,728 | 16 | Title: Improving Visual Question Answering Models through Robustness Analysis and In-Context Learning with a Chain of Basic Questions
Abstract: Deep neural networks have been critical in the task of Visual Question Answering (VQA), with research traditionally focused on improving model accuracy. Recently, however, ther... | [
45242,
40316,
35573,
3263
] | Train |
44,729 | 30 | Title: Instruction Position Matters in Sequence Generation with Large Language Models
Abstract: Large language models (LLMs) are capable of performing conditional sequence generation tasks, such as translation or summarization, through instruction fine-tuning. The fine-tuning data is generally sequentially concatenated... | [
39873,
21956,
13700,
17989,
35545
] | Test |
44,730 | 16 | Title: Challenge Results Are Not Reproducible
Abstract: While clinical trials are the state-of-the-art methods to assess the effect of new medication in a comparative manner, benchmarking in the field of medical image analysis is performed by so-called challenges. Recently, comprehensive analysis of multiple biomedical... | [] | Test |
44,731 | 3 | Title: The Case for Anticipating Undesirable Consequences of Computing Innovations Early, Often, and Across Computer Science
Abstract: From smart sensors that infringe on our privacy to neural nets that portray realistic imposter deepfakes, our society increasingly bears the burden of negative, if unintended, consequen... | [
36904
] | Test |
44,732 | 16 | Title: A novel approach to generate datasets with XAI ground truth to evaluate image models
Abstract: With the increased usage of artificial intelligence (AI), it is imperative to understand how these models work internally. These needs have led to the development of a new field called eXplainable artificial intelligen... | [] | Train |
44,733 | 23 | Title: Assessing the Ability of ChatGPT to Screen Articles for Systematic Reviews
Abstract: By organizing knowledge within a research field, Systematic Reviews (SR) provide valuable leads to steer research. Evidence suggests that SRs have become first-class artifacts in software engineering. However, the tedious manual... | [
29109,
6942
] | Train |
44,734 | 31 | Title: Dimensionality Reduction Using pseudo-Boolean polynomials For Cluster Analysis
Abstract: We introduce usage of a reduction property of penalty-based formulation of pseudo-Boolean polynomials as a mechanism for invariant dimensionality reduction in cluster analysis processes. In our experiments, we show that mult... | [
14895
] | Train |
44,735 | 24 | Title: Modeling human road crossing decisions as reward maximization with visual perception limitations
Abstract: Understanding the interaction between different road users is critical for road safety and automated vehicles (AVs). Existing mathematical models on this topic have been proposed based mostly on either cogn... | [] | Train |
44,736 | 16 | Title: SSMG: Spatial-Semantic Map Guided Diffusion Model for Free-form Layout-to-Image Generation
Abstract: Despite significant progress in Text-to-Image (T2I) generative models, even lengthy and complex text descriptions still struggle to convey detailed controls. In contrast, Layout-to-Image (L2I) generation, aiming ... | [
41146,
44585,
34074,
41108
] | Train |
44,737 | 27 | Title: Exploiting Structure for Optimal Multi-Agent Bayesian Decentralized Estimation
Abstract: A key challenge in Bayesian decentralized data fusion is the `rumor propagation' or `double counting' phenomenon, where previously sent data circulates back to its sender. It is often addressed by approximate methods like co... | [] | Test |
44,738 | 30 | Title: Textual Explanations for Automated Commentary Driving
Abstract: The provision of natural language explanations for the predictions of deep-learning-based vehicle controllers is critical as it enhances transparency and easy audit. In this work, a state-of-the-art (SOTA) prediction and explanation model is thoroug... | [] | Train |
44,739 | 16 | Title: MS-LSTM: Exploring Spatiotemporal Multiscale Representations in Video Prediction Domain
Abstract: The drastic variation of motion in spatial and temporal dimensions makes the video prediction task extremely challenging. Existing RNN models obtain higher performance by deepening or widening the model. They obtain... | [] | Train |
44,740 | 24 | Title: PAC Prediction Sets for Large Language Models of Code
Abstract: Prediction sets have recently been shown to be a promising strategy for quantifying the uncertainty of deep neural networks in a way that provides theoretical guarantees. However, existing techniques have largely targeted settings where the space of... | [
4516
] | Test |
44,741 | 16 | Title: Erasing Concepts from Diffusion Models
Abstract: Motivated by recent advancements in text-to-image diffusion, we study erasure of specific concepts from the model's weights. While Stable Diffusion has shown promise in producing explicit or realistic artwork, it has raised concerns regarding its potential for mis... | [
39813,
10252,
23184,
29200,
44177,
45593,
9244,
36383,
43039,
27301,
1318,
43560,
170,
37290,
27059,
7354,
35524,
20687,
18003,
22995,
28885,
12764,
28513,
22886
] | Train |
44,742 | 8 | Title: A Multi-Agent Deep Reinforcement Learning Approach for RAN Resource Allocation in O-RAN
Abstract: Artificial intelligence (AI) and Machine Learning (ML) are considered as key enablers for realizing the full potential of fifth-generation (5G) and beyond mobile networks, particularly in the context of resource man... | [] | Validation |
44,743 | 24 | Title: Smoothing the Edges: A General Framework for Smooth Optimization in Sparse Regularization using Hadamard Overparametrization
Abstract: This paper presents a framework for smooth optimization of objectives with $\ell_q$ and $\ell_{p,q}$ regularization for (structured) sparsity. Finding solutions to these non-smoo... | [
36560,
24271
] | Test |
44,744 | 24 | Title: STG4Traffic: A Survey and Benchmark of Spatial-Temporal Graph Neural Networks for Traffic Prediction
Abstract: Traffic prediction has been an active research topic in the domain of spatial-temporal data mining. Accurate real-time traffic prediction is essential to improve the safety, stability, and versatility o... | [
7318,
28445,
4062
] | Validation |
44,745 | 23 | Title: On the Need for Artifacts to Support Research on Self-Adaptation Mature for Industrial Adoption
Abstract: Despite the vast body of knowledge developed by the self-adaptive systems community and the wide use of self-adaptation in industry, it is unclear whether or to what extent industry leverages output of acade... | [] | Train |
44,746 | 16 | Title: STAIR: Learning Sparse Text and Image Representation in Grounded Tokens
Abstract: Image and text retrieval is one of the foundational tasks in the vision and language domain with multiple real-world applications. State-of-the-art approaches, e.g. CLIP, ALIGN, represent images and texts as dense embeddings and ca... | [
40843,
7124
] | Train |
44,747 | 27 | Title: Learn to Grasp Via Intention Discovery and Its Application to Challenging Clutter
Abstract: Humans excel in grasping objects through diverse and robust policies, many of which are so probabilistically rare that exploration-based learning methods hardly observe and learn. Inspired by the human learning process, w... | [
26426,
20013
] | Train |
44,748 | 13 | Title: Roulette-Wheel Selection-Based PSO Algorithm for Solving the Vehicle Routing Problem with Time Windows
Abstract: The well-known Vehicle Routing Problem with Time Windows (VRPTW) aims to reduce the cost of moving goods between several destinations while accommodating constraints like set time windows for certain ... | [] | Train |
44,749 | 27 | Title: AutonomROS: A ReconROS-based Autonomonous Driving Unit
Abstract: Autonomous driving has become an important research area in recent years, and the corresponding system creates an enormous demand for computations. Heterogeneous computing platforms such as systems-on-chip that combine CPUs with reprogrammable hard... | [] | Test |
44,750 | 10 | Title: Root Cause Identification for Collective Anomalies in Time Series given an Acyclic Summary Causal Graph with Loops
Abstract: This paper presents an approach for identifying the root causes of collective anomalies given observational time series and an acyclic summary causal graph which depicts an abstraction of ... | [
31792,
37494,
43767
] | Test |
44,751 | 28 | Title: The Optimality of AIFV Codes in the Class of 2-bit Delay Decodable Codes
Abstract: AIFV (almost instantaneous fixed-to-variable length) codes are noiseless source codes that can attain a shorter average codeword length than Huffman codes by allowing a time-variant encoder with two code tables and a decoding dela... | [
5711
] | Train |
44,752 | 16 | Title: Free Lunch for Generating Effective Outlier Supervision
Abstract: When deployed in practical applications, computer vision systems will encounter numerous unexpected images (\emph{{i.e.}}, out-of-distribution data). Due to the potentially raised safety risks, these aforementioned unseen data should be carefully ... | [] | Validation |
44,753 | 16 | Title: SegDA: Maximum Separable Segment Mask with Pseudo Labels for Domain Adaptive Semantic Segmentation
Abstract: Unsupervised Domain Adaptation (UDA) aims to solve the problem of label scarcity of the target domain by transferring the knowledge from the label rich source domain. Usually, the source domain consists o... | [
16082
] | Train |
44,754 | 16 | Title: Real-time Multi-person Eyeblink Detection in the Wild for Untrimmed Video
Abstract: Real-time eyeblink detection in the wild can widely serve for fatigue detection, face anti-spoofing, emotion analysis, etc. The existing research efforts generally focus on single-person cases towards trimmed video. However, mult... | [] | Validation |
44,755 | 24 | Title: Robust Sparse Mean Estimation via Incremental Learning
Abstract: In this paper, we study the problem of robust sparse mean estimation, where the goal is to estimate a $k$-sparse mean from a collection of partially corrupted samples drawn from a heavy-tailed distribution. Existing estimators face two critical cha... | [] | Test |
44,756 | 24 | Title: Clinical Trial Active Learning
Abstract: This paper presents a novel approach to active learning that takes into account the non-independent and identically distributed (non-i.i.d.) structure of a clinical trial setting. There exists two types of clinical trials: retrospective and prospective. Retrospective clin... | [
17884,
2366
] | Validation |
44,757 | 16 | Title: Contrast-augmented Diffusion Model with Fine-grained Sequence Alignment for Markup-to-Image Generation
Abstract: The recently rising markup-to-image generation poses greater challenges as compared to natural image generation, due to its low tolerance for errors as well as the complex sequence and context correla... | [
43867,
37254,
16206
] | Train |
44,758 | 10 | Title: A Wide Evaluation of ChatGPT on Affective Computing Tasks
Abstract: With the rise of foundation models, a new artificial intelligence paradigm has emerged, by simply using general purpose foundation models with prompting to solve problems instead of training a separate machine learning model for each problem. Su... | [
12128,
24931,
20228,
33220,
13510,
6535,
38856,
15049,
45605,
6942,
11280,
31956,
8894
] | Test |
44,759 | 10 | Title: Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition
Abstract: To facilitate research in the direction of fine-tuning foundation models from human feedback, we held the MineRL BASALT Competition on Fine-Tuning from Human Feedback at NeurIPS 2022. The BASALT chall... | [
18459,
30756,
20453
] | Train |
44,760 | 3 | Title: Citizen Perspectives on Necessary Safeguards to the Use of AI by Law Enforcement Agencies
Abstract: In the light of modern technological advances, Artificial Intelligence (AI) is relied upon to enhance performance, increase efficiency, and maximize gains. For Law Enforcement Agencies (LEAs), it can prove valuabl... | [] | Test |
44,761 | 4 | Title: Helix++: A platform for efficiently securing software
Abstract: The open-source Helix++ project improves the security posture of computing platforms by applying cutting-edge cybersecurity techniques to diversify and harden software automatically. A distinguishing feature of Helix++ is that it does not require so... | [] | Train |
44,762 | 16 | Title: High Dynamic Range Imaging via Visual Attention Modules
Abstract: Thanks to High Dynamic Range (HDR) imaging methods, the scope of photography has seen profound changes recently. To be more specific, such methods try to reconstruct the lost luminosity of the real world caused by the limitation of regular cameras... | [] | Test |
44,763 | 30 | Title: Attention-Based Methods For Audio Question Answering
Abstract: Audio question answering (AQA) is the task of producing natural language answers when a system is provided with audio and natural language questions. In this paper, we propose neural network architectures based on self-attention and cross-attention f... | [] | Train |
44,764 | 24 | Title: Flexible Phase Dynamics for Bio-Plausible Contrastive Learning
Abstract: Many learning algorithms used as normative models in neuroscience or as candidate approaches for learning on neuromorphic chips learn by contrasting one set of network states with another. These Contrastive Learning (CL) algorithms are trad... | [
19425,
10762
] | Train |
44,765 | 13 | Title: Continuous Cartesian Genetic Programming based representation for Multi-Objective Neural Architecture Search
Abstract: We propose a novel approach for the challenge of designing less complex yet highly effective convolutional neural networks (CNNs) through the use of cartesian genetic programming (CGP) for neura... | [] | Train |
44,766 | 24 | Title: Measuring Surprise in the Wild
Abstract: The quantitative measurement of how and when we experience surprise has mostly remained limited to laboratory studies, and its extension to naturalistic settings has been challenging. Here we demonstrate, for the first time, how computational models of surprise rooted in ... | [
3146
] | Test |
44,767 | 15 | Title: Efficient Multi-Cycle Folded Integer Multipliers
Abstract: Fast combinational multipliers with large bit widths can occupy significant silicon area. Provided the application allows for a multiplication to last two or more clock cycles, the area can be reduced through resource sharing (i.e., folding). This work i... | [] | Train |
44,768 | 24 | Title: Multivariate Time Series Classification: A Deep Learning Approach
Abstract: This paper investigates different methods and various neural network architectures applicable in the time series classification domain. The data is obtained from a fleet of gas sensors that measure and track quantities such as oxygen and... | [] | Train |
44,769 | 16 | Title: System-Status-Aware Adaptive Network for Online Streaming Video Understanding
Abstract: Recent years have witnessed great progress in deep neural networks for real-time applications. However, most existing works do not explicitly consider the general case where the device's state and the available resources fluc... | [
43248,
13860
] | Train |
44,770 | 30 | Title: Word Embeddings for Banking Industry
Abstract: Applications of Natural Language Processing (NLP) are plentiful, from sentiment analysis to text classification. Practitioners rely on static word embeddings (e.g. Word2Vec or GloVe) or static word representation from contextual models (e.g. BERT or ELMo) to perform... | [] | Train |
44,771 | 6 | Title: NeuroAiR: Deep Learning Framework for Airwriting Recognition from Scalp-recorded Neural Signals
Abstract: Airwriting recognition is a task that involves identifying letters written in free space using finger movement. It is a special case of gesture recognition, where gestures correspond to letters in a specific... | [] | Train |
44,772 | 24 | Title: A physics-informed neural network framework for modeling obstacle-related equations
Abstract: Deep learning has been highly successful in some applications. Nevertheless, its use for solving partial differential equations (PDEs) has only been of recent interest with current state-of-the-art machine learning libr... | [] | Train |
44,773 | 22 | Title: Optimal and Heuristic Min-Reg Scheduling Algorithms for GPU Program
Abstract: Given a basic block of instructions, finding a schedule that requires the minimum number of registers for evaluation is a well-known problem. The problem is NP-complete when the dependences among instructions form a directed-acyclic gr... | [] | Train |
44,774 | 16 | Title: Learning to Predict Navigational Patterns From Partial Observations
Abstract: Human beings cooperatively navigate rule-constrained environments by adhering to mutually known navigational patterns, which may be represented as directional pathways or road lanes. Inferring these navigational patterns from incomplet... | [
26680
] | Train |
44,775 | 16 | Title: Exploring the Mutual Influence Between Self-Supervised Single-Frame and Multi-Frame Depth Estimation
Abstract: Although both self-supervised single-frame and multi-frame depth estimation methods only require unlabeled monocular videos for training, the information they leverage varies because single-frame method... | [] | Validation |
44,776 | 30 | Title: Evaluating GPT-3.5 and GPT-4 Models on Brazilian University Admission Exams
Abstract: The present study aims to explore the capabilities of Language Models (LMs) in tackling high-stakes multiple-choice tests, represented here by the Exame Nacional do Ensino M\'edio (ENEM), a multidisciplinary entrance examinatio... | [
24706,
13700,
15301,
14026,
19083,
39600,
14422,
45659
] | Train |
44,777 | 27 | Title: Autonomy for Ferries and Harbour Buses: a Collision Avoidance Perspective
Abstract: This paper provides a collision avoidance perspective to maritime autonomy, in the shift towards Maritime Autonomous Surface Ships (MASS). In particular, the paper presents the developments related to the Greenhopper, Denmark's f... | [] | Validation |
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