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What field is the article from? | Title: Multimodal Stress Detection Using Facial Landmarks and Biometric Signals
Abstract: The development of various sensing technologies is improving measurements of
stress and the well-being of individuals. Although progress has been made with
single signal modalities like wearables and facial emotion recognition,
in... | Computer Vision |
What field is the article from? | Title: 3D Hand Pose Estimation in Egocentric Images in the Wild
Abstract: We present WildHands, a method for 3D hand pose estimation in egocentric
images in the wild. This is challenging due to (a) lack of 3D hand pose
annotations for images in the wild, and (b) a form of perspective
distortion-induced shape ambiguity ... | Computer Vision |
What field is the article from? | Title: Domain-Specific Deep Learning Feature Extractor for Diabetic Foot Ulcer Detection
Abstract: Diabetic Foot Ulcer (DFU) is a condition requiring constant monitoring and
evaluations for treatment. DFU patient population is on the rise and will soon
outpace the available health resources. Autonomous monitoring and e... | Computer Vision |
What field is the article from? | Title: Improving Source-Free Target Adaptation with Vision Transformers Leveraging Domain Representation Images
Abstract: Unsupervised Domain Adaptation (UDA) methods facilitate knowledge transfer
from a labeled source domain to an unlabeled target domain, navigating the
obstacle of domain shift. While Convolutional Ne... | Computer Vision |
What field is the article from? | Title: Exploring Post-Training Quantization of Protein Language Models
Abstract: Recent advancements in unsupervised protein language models (ProteinLMs),
like ESM-1b and ESM-2, have shown promise in different protein prediction
tasks. However, these models face challenges due to their high computational
demands, signi... | Machine Learning |
What field is the article from? | Title: Toward Reinforcement Learning-based Rectilinear Macro Placement Under Human Constraints
Abstract: Macro placement is a critical phase in chip design, which becomes more
intricate when involving general rectilinear macros and layout areas.
Furthermore, macro placement that incorporates human-like constraints, suc... | Machine Learning |
What field is the article from? | Title: A Multi-Center Study on the Adaptability of a Shared Foundation Model for Electronic Health Records
Abstract: Foundation models hold promise for transforming AI in healthcare by providing
modular components that are easily adaptable to downstream healthcare tasks,
making AI development more scalable and cost-eff... | Machine Learning |
What field is the article from? | Title: Enabling Decision-Support Systems through Automated Cell Tower Detection
Abstract: Cell phone coverage and high-speed service gaps persist in rural areas in
sub-Saharan Africa, impacting public access to mobile-based financial,
educational, and humanitarian services. Improving maps of telecommunications
infrastr... | Computer Vision |
What field is the article from? | Title: REST: Retrieval-Based Speculative Decoding
Abstract: We introduce Retrieval-Based Speculative Decoding (REST), a novel algorithm
designed to speed up language model generation. The key insight driving the
development of REST is the observation that the process of text generation
often includes certain common pha... | Computational Linguistics |
What field is the article from? | Title: GTP-ViT: Efficient Vision Transformers via Graph-based Token Propagation
Abstract: Vision Transformers (ViTs) have revolutionized the field of computer vision,
yet their deployments on resource-constrained devices remain challenging due to
high computational demands. To expedite pre-trained ViTs, token pruning a... | Computer Vision |
What field is the article from? | Title: Differentially Private Pre-Trained Model Fusion using Decentralized Federated Graph Matching
Abstract: Model fusion is becoming a crucial component in the context of
model-as-a-service scenarios, enabling the delivery of high-quality model
services to local users. However, this approach introduces privacy risks ... | Machine Learning |
What field is the article from? | Title: Large-scale Training of Foundation Models for Wearable Biosignals
Abstract: Tracking biosignals is crucial for monitoring wellness and preempting the
development of severe medical conditions. Today, wearable devices can
conveniently record various biosignals, creating the opportunity to monitor
health status wit... | Machine Learning |
What field is the article from? | Title: Universal Knowledge Graph Embeddings
Abstract: A variety of knowledge graph embedding approaches have been developed. Most
of them obtain embeddings by learning the structure of the knowledge graph
within a link prediction setting. As a result, the embeddings reflect only the
semantics of a single knowledge grap... | Artificial Intelligence |
What field is the article from? | Title: Empowering Distributed Solutions in Renewable Energy Systems and Grid Optimization
Abstract: This study delves into the shift from centralized to decentralized approaches
in the electricity industry, with a particular focus on how machine learning
(ML) advancements play a crucial role in empowering renewable ene... | Machine Learning |
What field is the article from? | Title: SortNet: Learning To Rank By a Neural-Based Sorting Algorithm
Abstract: The problem of relevance ranking consists of sorting a set of objects with
respect to a given criterion. Since users may prefer different relevance
criteria, the ranking algorithms should be adaptable to the user needs. Two
main approaches e... | Machine Learning |
What field is the article from? | Title: Establishing Performance Baselines in Fine-Tuning, Retrieval-Augmented Generation and Soft-Prompting for Non-Specialist LLM Users
Abstract: Research into methods for improving the performance of large language models
(LLMs) through fine-tuning, retrieval-augmented generation (RAG) and
soft-prompting has tended t... | Information Retrieval |
What field is the article from? | Title: Detrimental Contexts in Open-Domain Question Answering
Abstract: For knowledge intensive NLP tasks, it has been widely accepted that accessing
more information is a contributing factor to improvements in the model's
end-to-end performance. However, counter-intuitively, too much context can have
a negative impact... | Computational Linguistics |
What field is the article from? | Title: MAIRA-1: A specialised large multimodal model for radiology report generation
Abstract: We present a radiology-specific multimodal model for the task for generating
radiological reports from chest X-rays (CXRs). Our work builds on the idea that
large language model(s) can be equipped with multimodal capabilities... | Computational Linguistics |
What field is the article from? | Title: Gen2Sim: Scaling up Robot Learning in Simulation with Generative Models
Abstract: Generalist robot manipulators need to learn a wide variety of manipulation
skills across diverse environments. Current robot training pipelines rely on
humans to provide kinesthetic demonstrations or to program simulation
environme... | Robotics |
What field is the article from? | Title: Efficient Temporally-Aware DeepFake Detection using H.264 Motion Vectors
Abstract: Video DeepFakes are fake media created with Deep Learning (DL) that
manipulate a person's expression or identity. Most current DeepFake detection
methods analyze each frame independently, ignoring inconsistencies and
unnatural mov... | Computer Vision |
What field is the article from? | Title: Taking it further: leveraging pseudo labels for field delineation across label-scarce smallholder regions
Abstract: Transfer learning allows for resource-efficient geographic transfer of
pre-trained field delineation models. However, the scarcity of labeled data for
complex and dynamic smallholder landscapes, pa... | Computer Vision |
What field is the article from? | Title: KwaiAgents: Generalized Information-seeking Agent System with Large Language Models
Abstract: Driven by curiosity, humans have continually sought to explore and understand
the world around them, leading to the invention of various tools to satiate
this inquisitiveness. Despite not having the capacity to process ... | Artificial Intelligence |
What field is the article from? | Title: Efficient Toxic Content Detection by Bootstrapping and Distilling Large Language Models
Abstract: Toxic content detection is crucial for online services to remove
inappropriate content that violates community standards. To automate the
detection process, prior works have proposed varieties of machine learning (M... | Computational Linguistics |
What field is the article from? | Title: Representation Learning with Large Language Models for Recommendation
Abstract: Recommender systems have seen significant advancements with the influence of
deep learning and graph neural networks, particularly in capturing complex
user-item relationships. However, these graph-based recommenders heavily depend
o... | Information Retrieval |
What field is the article from? | Title: Generating Continuations in Multilingual Idiomatic Contexts
Abstract: The ability to process idiomatic or literal multiword expressions is a
crucial aspect of understanding and generating any language. The task of
generating contextually relevant continuations for narratives containing
idiomatic (or literal) exp... | Computational Linguistics |
What field is the article from? | Title: On Measuring Faithfulness of Natural Language Explanations
Abstract: Large language models (LLMs) can explain their own predictions, through
post-hoc or Chain-of-Thought (CoT) explanations. However the LLM could make up
reasonably sounding explanations that are unfaithful to its underlying
reasoning. Recent work... | Computational Linguistics |
What field is the article from? | Title: Contrastive Deep Nonnegative Matrix Factorization for Community Detection
Abstract: Recently, nonnegative matrix factorization (NMF) has been widely adopted for
community detection, because of its better interpretability. However, the
existing NMF-based methods have the following three problems: 1) they directly... | Machine Learning |
What field is the article from? | Title: Cognitive bias in large language models: Cautious optimism meets anti-Panglossian meliorism
Abstract: Traditional discussions of bias in large language models focus on a
conception of bias closely tied to unfairness, especially as affecting
marginalized groups. Recent work raises the novel possibility of assessi... | Artificial Intelligence |
What field is the article from? | Title: Improving age prediction: Utilizing LSTM-based dynamic forecasting for data augmentation in multivariate time series analysis
Abstract: The high dimensionality and complexity of neuroimaging data necessitate large
datasets to develop robust and high-performing deep learning models. However,
the neuroimaging fiel... | Machine Learning |
What field is the article from? | Title: RDBench: ML Benchmark for Relational Databases
Abstract: Benefiting from high-quality datasets and standardized evaluation metrics,
machine learning (ML) has achieved sustained progress and widespread
applications. However, while applying machine learning to relational databases
(RDBs), the absence of a well-est... | Machine Learning |
What field is the article from? | Title: On the Exploitability of Reinforcement Learning with Human Feedback for Large Language Models
Abstract: Reinforcement Learning with Human Feedback (RLHF) is a methodology designed
to align Large Language Models (LLMs) with human preferences, playing an
important role in LLMs alignment. Despite its advantages, RL... | Artificial Intelligence |
What field is the article from? | Title: Addressing Long-Horizon Tasks by Integrating Program Synthesis and State Machines
Abstract: Deep reinforcement learning excels in various domains but lacks
generalizability and interoperability. Programmatic RL methods (Trivedi et al.,
2021; Liu et al., 2023) reformulate solving RL tasks as synthesizing
interpre... | Machine Learning |
What field is the article from? | Title: Non-Cross Diffusion for Semantic Consistency
Abstract: In diffusion models, deviations from a straight generative flow are a common
issue, resulting in semantic inconsistencies and suboptimal generations. To
address this challenge, we introduce `Non-Cross Diffusion', an innovative
approach in generative modeling... | Machine Learning |
What field is the article from? | Title: Open Visual Knowledge Extraction via Relation-Oriented Multimodality Model Prompting
Abstract: Images contain rich relational knowledge that can help machines understand
the world. Existing methods on visual knowledge extraction often rely on the
pre-defined format (e.g., sub-verb-obj tuples) or vocabulary (e.g.... | Computational Linguistics |
What field is the article from? | Title: A Survey of Blockchain, Artificial Intelligence, and Edge Computing for Web 3.0
Abstract: Web 3.0, as the third generation of the World Wide Web, aims to solve
contemporary problems of trust, centralization, and data ownership. Driven by
the latest advances in cutting-edge technologies, Web 3.0 is moving towards... | Cryptography and Security |
What field is the article from? | Title: RAEDiff: Denoising Diffusion Probabilistic Models Based Reversible Adversarial Examples Self-Generation and Self-Recovery
Abstract: Collected and annotated datasets, which are obtained through extensive
efforts, are effective for training Deep Neural Network (DNN) models. However,
these datasets are susceptible ... | Cryptography and Security |
What field is the article from? | Title: A Bi-level Framework for Traffic Accident Duration Prediction: Leveraging Weather and Road Condition Data within a Practical Optimum Pipeline
Abstract: Due to the stochastic nature of events, predicting the duration of a traffic
incident presents a formidable challenge. Accurate duration estimation can
result in... | Artificial Intelligence |
What field is the article from? | Title: Not All Large Language Models (LLMs) Succumb to the "Reversal Curse": A Comparative Study of Deductive Logical Reasoning in BERT and GPT Models
Abstract: The "Reversal Curse" refers to the scenario where auto-regressive decoder
large language models (LLMs), such as ChatGPT, trained on "A is B" fail to
learn "B i... | Computational Linguistics |
What field is the article from? | Title: A comparative analysis between Conformer-Transducer, Whisper, and wav2vec2 for improving the child speech recognition
Abstract: Automatic Speech Recognition (ASR) systems have progressed significantly in
their performance on adult speech data; however, transcribing child speech
remains challenging due to the aco... | Computational Linguistics |
What field is the article from? | Title: Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation
Abstract: Recent advancements in Large Language Models (LLMs) have revolutionized
decision-making by breaking down complex problems into more manageable language
sequences referred to as ``thoughts''. An effective thought design s... | Artificial Intelligence |
What field is the article from? | Title: Lightweight Face Recognition: An Improved MobileFaceNet Model
Abstract: This paper presents an extensive exploration and comparative analysis of
lightweight face recognition (FR) models, specifically focusing on
MobileFaceNet and its modified variant, MMobileFaceNet. The need for efficient
FR models on devices w... | Computer Vision |
What field is the article from? | Title: One-shot Localization and Segmentation of Medical Images with Foundation Models
Abstract: Recent advances in Vision Transformers (ViT) and Stable Diffusion (SD) models
with their ability to capture rich semantic features of the image have been
used for image correspondence tasks on natural images. In this paper,... | Computer Vision |
What field is the article from? | Title: IA-LSTM: Interaction-Aware LSTM for Pedestrian Trajectory Prediction
Abstract: Predicting the trajectory of pedestrians in crowd scenarios is indispensable
in self-driving or autonomous mobile robot field because estimating the future
locations of pedestrians around is beneficial for policy decision to avoid
col... | Computer Vision |
What field is the article from? | Title: A Comprehensive and Reliable Feature Attribution Method: Double-sided Remove and Reconstruct (DoRaR)
Abstract: The limited transparency of the inner decision-making mechanism in deep
neural networks (DNN) and other machine learning (ML) models has hindered their
application in several domains. In order to tackle... | Machine Learning |
What field is the article from? | Title: Knowledgeable Preference Alignment for LLMs in Domain-specific Question Answering
Abstract: Recently, the development of large language models (LLMs) has attracted wide
attention in academia and industry. Deploying LLMs to real scenarios is one of
the key directions in the current Internet industry. In this pape... | Computational Linguistics |
What field is the article from? | Title: Mixture-of-Linear-Experts for Long-term Time Series Forecasting
Abstract: Long-term time series forecasting (LTSF) aims to predict future values of a
time series given the past values. The current state-of-the-art (SOTA) on this
problem is attained in some cases by linear-centric models, which primarily
feature ... | Machine Learning |
What field is the article from? | Title: Cross-Modal Information-Guided Network using Contrastive Learning for Point Cloud Registration
Abstract: The majority of point cloud registration methods currently rely on extracting
features from points. However, these methods are limited by their dependence on
information obtained from a single modality of poi... | Computer Vision |
What field is the article from? | Title: Retrieval-Augmented Code Generation for Universal Information Extraction
Abstract: Information Extraction (IE) aims to extract structural knowledge (e.g.,
entities, relations, events) from natural language texts, which brings
challenges to existing methods due to task-specific schemas and complex text
expression... | Artificial Intelligence |
What field is the article from? | Title: Probabilistic Tree-of-thought Reasoning for Answering Knowledge-intensive Complex Questions
Abstract: Large language models (LLMs) are capable of answering knowledge-intensive
complex questions with chain-of-thought (CoT) reasoning. However, they tend to
generate factually incorrect reasoning steps when the requ... | Computational Linguistics |
What field is the article from? | Title: AI-assisted Learning for Electronic Engineering Courses in High Education
Abstract: This study evaluates the efficacy of ChatGPT as an AI teaching and learning
support tool in an integrated circuit systems course at a higher education
institution in an Asian country. Various question types were completed, and
Ch... | Computers and Society |
What field is the article from? | Title: Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game
Abstract: Agents built with large language models (LLMs) have recently achieved great
advancements. However, most of the efforts focus on single-agent or cooperative
settings, leaving more general multi-agent environments underex... | Artificial Intelligence |
What field is the article from? | Title: Efficient Pre-training for Localized Instruction Generation of Videos
Abstract: Procedural videos show step-by-step demonstrations of tasks like recipe
preparation. Understanding such videos is challenging, involving the precise
localization of steps and the generation of textual instructions. Manually
annotatin... | Computer Vision |
What field is the article from? | Title: Decision-Making for Autonomous Vehicles with Interaction-Aware Behavioral Prediction and Social-Attention Neural Network
Abstract: Autonomous vehicles need to accomplish their tasks while interacting with
human drivers in traffic. It is thus crucial to equip autonomous vehicles with
artificial reasoning to bette... | Artificial Intelligence |
What field is the article from? | Title: Debiasing Multimodal Models via Causal Information Minimization
Abstract: Most existing debiasing methods for multimodal models, including causal
intervention and inference methods, utilize approximate heuristics to represent
the biases, such as shallow features from early stages of training or unimodal
features... | Machine Learning |
What field is the article from? | Title: Federated Learning for Generalization, Robustness, Fairness: A Survey and Benchmark
Abstract: Federated learning has emerged as a promising paradigm for privacy-preserving
collaboration among different parties. Recently, with the popularity of
federated learning, an influx of approaches have delivered towards di... | Machine Learning |
What field is the article from? | Title: Towards Concept-Aware Large Language Models
Abstract: Concepts play a pivotal role in various human cognitive functions, including
learning, reasoning and communication. However, there is very little work on
endowing machines with the ability to form and reason with concepts. In
particular, state-of-the-art larg... | Computational Linguistics |
What field is the article from? | Title: nerblackbox: A High-level Library for Named Entity Recognition in Python
Abstract: We present nerblackbox, a python library to facilitate the use of
state-of-the-art transformer-based models for named entity recognition. It
provides simple-to-use yet powerful methods to access data and models from a
wide range o... | Computational Linguistics |
What field is the article from? | Title: More Robots are Coming: Large Multimodal Models (ChatGPT) can Solve Visually Diverse Images of Parsons Problems
Abstract: The advent of large language models is reshaping computing education. Recent
research has demonstrated that these models can produce better explanations
than students, answer multiple-choice ... | Computational Linguistics |
What field is the article from? | Title: Methods to Estimate Large Language Model Confidence
Abstract: Large Language Models have difficulty communicating uncertainty, which is a
significant obstacle to applying LLMs to complex medical tasks. This study
evaluates methods to measure LLM confidence when suggesting a diagnosis for
challenging clinical vig... | Computational Linguistics |
What field is the article from? | Title: Green Resilience of Cyber-Physical Systems
Abstract: Cyber-Physical System (CPS) represents systems that join both hardware and
software components to perform real-time services. Maintaining the system's
reliability is critical to the continuous delivery of these services. However,
the CPS running environment is... | Software Engineering |
What field is the article from? | Title: Quilt: Robust Data Segment Selection against Concept Drifts
Abstract: Continuous machine learning pipelines are common in industrial settings where
models are periodically trained on data streams. Unfortunately, concept drifts
may occur in data streams where the joint distribution of the data X and label
y, P(X,... | Machine Learning |
What field is the article from? | Title: Coordination-free Decentralised Federated Learning on Complex Networks: Overcoming Heterogeneity
Abstract: Federated Learning (FL) is a well-known framework for successfully performing
a learning task in an edge computing scenario where the devices involved have
limited resources and incomplete data representati... | Machine Learning |
What field is the article from? | Title: Kuro Siwo: 12.1 billion $m^2$ under the water. A global multi-temporal satellite dataset for rapid flood mapping
Abstract: Global floods, exacerbated by climate change, pose severe threats to human
life, infrastructure, and the environment. This urgency is highlighted by
recent catastrophic events in Pakistan an... | Computer Vision |
What field is the article from? | Title: Masking Hyperspectral Imaging Data with Pretrained Models
Abstract: The presence of undesired background areas associated with potential noise
and unknown spectral characteristics degrades the performance of hyperspectral
data processing. Masking out unwanted regions is key to addressing this issue.
Processing o... | Computer Vision |
What field is the article from? | Title: How to Bridge the Gap between Modalities: A Comprehensive Survey on Multimodal Large Language Model
Abstract: This review paper explores Multimodal Large Language Models (MLLMs), which
integrate Large Language Models (LLMs) like GPT-4 to handle multimodal data
such as text and vision. MLLMs demonstrate capabilit... | Computational Linguistics |
What field is the article from? | Title: Adaptive Interventions with User-Defined Goals for Health Behavior Change
Abstract: Physical inactivity remains a major public health concern, having
associations with adverse health outcomes such as cardiovascular disease and
type-2 diabetes. Mobile health applications present a promising avenue for
low-cost, s... | Machine Learning |
What field is the article from? | Title: Roles of Scaling and Instruction Tuning in Language Perception: Model vs. Human Attention
Abstract: Recent large language models (LLMs) have revealed strong abilities to
understand natural language. Since most of them share the same basic structure,
i.e. the transformer block, possible contributors to their succ... | Computational Linguistics |
What field is the article from? | Title: Culturally Responsive Artificial Intelligence -- Problems, Challenges and Solutions
Abstract: In the contemporary interconnected world, the concept of cultural
responsibility occupies paramount importance. As the lines between nations
become less distinct, it is incumbent upon individuals, communities, and
insti... | Computers and Society |
What field is the article from? | Title: Deep Reinforcement Learning for Community Battery Scheduling under Uncertainties of Load, PV Generation, and Energy Prices
Abstract: In response to the growing uptake of distributed energy resources (DERs),
community batteries have emerged as a promising solution to support renewable
energy integration, reduce p... | Machine Learning |
What field is the article from? | Title: Artificial Intelligence Ethics Education in Cybersecurity: Challenges and Opportunities: a focus group report
Abstract: The emergence of AI tools in cybersecurity creates many opportunities and
uncertainties. A focus group with advanced graduate students in cybersecurity
revealed the potential depth and breadth ... | Cryptography and Security |
What field is the article from? | Title: Customizable Combination of Parameter-Efficient Modules for Multi-Task Learning
Abstract: Modular and composable transfer learning is an emerging direction in the
field of Parameter Efficient Fine-Tuning, as it enables neural networks to
better organize various aspects of knowledge, leading to improved cross-tas... | Machine Learning |
What field is the article from? | Title: Dual Conditioned Diffusion Models for Out-Of-Distribution Detection: Application to Fetal Ultrasound Videos
Abstract: Out-of-distribution (OOD) detection is essential to improve the reliability
of machine learning models by detecting samples that do not belong to the
training distribution. Detecting OOD samples ... | Computer Vision |
What field is the article from? | Title: Unsupervised Lexical Simplification with Context Augmentation
Abstract: We propose a new unsupervised lexical simplification method that uses only
monolingual data and pre-trained language models. Given a target word and its
context, our method generates substitutes based on the target context and also
additiona... | Computational Linguistics |
What field is the article from? | Title: RankAug: Augmented data ranking for text classification
Abstract: Research on data generation and augmentation has been focused majorly on
enhancing generation models, leaving a notable gap in the exploration and
refinement of methods for evaluating synthetic data. There are several text
similarity metrics withi... | Computational Linguistics |
What field is the article from? | Title: Unleashing the Creative Mind: Language Model As Hierarchical Policy For Improved Exploration on Challenging Problem Solving
Abstract: Large Language Models (LLMs) have achieved tremendous progress, yet they
still often struggle with challenging reasoning problems. Current approaches
address this challenge by sam... | Artificial Intelligence |
What field is the article from? | Title: Empowering remittance management in the digitised landscape: A real-time Data-Driven Decision Support with predictive abilities for financial transactions
Abstract: The advent of Blockchain technology (BT) revolutionised the way remittance
transactions are recorded. Banks and remittance organisations have shown ... | Artificial Intelligence |
What field is the article from? | Title: Dexterous Functional Grasping
Abstract: While there have been significant strides in dexterous manipulation, most of
it is limited to benchmark tasks like in-hand reorientation which are of
limited utility in the real world. The main benefit of dexterous hands over
two-fingered ones is their ability to pickup to... | Robotics |
What field is the article from? | Title: Histopathologic Cancer Detection
Abstract: Early diagnosis of the cancer cells is necessary for making an effective
treatment plan and for the health and safety of a patient. Nowadays, doctors
usually use a histological grade that pathologists determine by performing a
semi-quantitative analysis of the histopath... | Computer Vision |
What field is the article from? | Title: Ever Evolving Evaluator (EV3): Towards Flexible and Reliable Meta-Optimization for Knowledge Distillation
Abstract: We introduce EV3, a novel meta-optimization framework designed to efficiently
train scalable machine learning models through an intuitive
explore-assess-adapt protocol. In each iteration of EV3, we... | Machine Learning |
What field is the article from? | Title: VIGraph: Self-supervised Learning for Class-Imbalanced Node Classification
Abstract: Class imbalance in graph data poses significant challenges for node
classification. Existing methods, represented by SMOTE-based approaches,
partially alleviate this issue but still exhibit limitations during imbalanced
scenario... | Machine Learning |
What field is the article from? | Title: NVFi: Neural Velocity Fields for 3D Physics Learning from Dynamic Videos
Abstract: In this paper, we aim to model 3D scene dynamics from multi-view videos.
Unlike the majority of existing works which usually focus on the common task of
novel view synthesis within the training time period, we propose to
simultane... | Computer Vision |
What field is the article from? | Title: Large-Scale Multi-Robot Assembly Planning for Autonomous Manufacturing
Abstract: Mobile autonomous robots have the potential to revolutionize manufacturing
processes. However, employing large robot fleets in manufacturing requires
addressing challenges including collision-free movement in a shared workspace,
eff... | Robotics |
What field is the article from? | Title: Surprisal Driven $k$-NN for Robust and Interpretable Nonparametric Learning
Abstract: Nonparametric learning is a fundamental concept in machine learning that aims
to capture complex patterns and relationships in data without making strong
assumptions about the underlying data distribution. Owing to simplicity a... | Machine Learning |
What field is the article from? | Title: Rule Learning as Machine Translation using the Atomic Knowledge Bank
Abstract: Machine learning models, and in particular language models, are being applied
to various tasks that require reasoning. While such models are good at
capturing patterns their ability to reason in a trustable and controlled manner
is fr... | Computational Linguistics |
What field is the article from? | Title: Towards Possibilities & Impossibilities of AI-generated Text Detection: A Survey
Abstract: Large Language Models (LLMs) have revolutionized the domain of natural
language processing (NLP) with remarkable capabilities of generating human-like
text responses. However, despite these advancements, several works in t... | Computational Linguistics |
What field is the article from? | Title: A Central Motor System Inspired Pre-training Reinforcement Learning for Robotic Control
Abstract: Designing controllers to achieve natural motor capabilities for multi-joint
robots is a significant challenge. However, animals in nature are naturally
with basic motor abilities and can master various complex motor... | Robotics |
What field is the article from? | Title: Are Vision Transformers More Data Hungry Than Newborn Visual Systems?
Abstract: Vision transformers (ViTs) are top performing models on many computer vision
benchmarks and can accurately predict human behavior on object recognition
tasks. However, researchers question the value of using ViTs as models of
biologi... | Computer Vision |
What field is the article from? | Title: Physics-Enhanced Multi-fidelity Learning for Optical Surface Imprint
Abstract: Human fingerprints serve as one unique and powerful characteristic for each
person, from which policemen can recognize the identity. Similar to humans,
many natural bodies and intrinsic mechanical qualities can also be uniquely
identi... | Machine Learning |
What field is the article from? | Title: Assessing Knowledge Editing in Language Models via Relation Perspective
Abstract: Knowledge Editing (KE) for modifying factual knowledge in Large Language
Models (LLMs) has been receiving increasing attention. However, existing
knowledge editing methods are entity-centric, and it is unclear whether this
approach... | Computational Linguistics |
What field is the article from? | Title: Nexus at ArAIEval Shared Task: Fine-Tuning Arabic Language Models for Propaganda and Disinformation Detection
Abstract: The spread of disinformation and propagandistic content poses a threat to
societal harmony, undermining informed decision-making and trust in reliable
sources. Online platforms often serve as b... | Computational Linguistics |
What field is the article from? | Title: Fine-Tuning InstructPix2Pix for Advanced Image Colorization
Abstract: This paper presents a novel approach to human image colorization by
fine-tuning the InstructPix2Pix model, which integrates a language model
(GPT-3) with a text-to-image model (Stable Diffusion). Despite the original
InstructPix2Pix model's pr... | Computer Vision |
What field is the article from? | Title: Investigating YOLO Models Towards Outdoor Obstacle Detection For Visually Impaired People
Abstract: The utilization of deep learning-based object detection is an effective
approach to assist visually impaired individuals in avoiding obstacles. In this
paper, we implemented seven different YOLO object detection m... | Computer Vision |
What field is the article from? | Title: Modeling subjectivity (by Mimicking Annotator Annotation) in toxic comment identification across diverse communities
Abstract: The prevalence and impact of toxic discussions online have made content
moderation crucial.Automated systems can play a vital role in identifying
toxicity, and reducing the reliance on h... | Artificial Intelligence |
What field is the article from? | Title: Content Augmented Graph Neural Networks
Abstract: In recent years, graph neural networks (GNNs) have become a popular tool for
solving various problems over graphs. In these models, the link structure of
the graph is typically exploited and nodes' embeddings are iteratively updated
based on adjacent nodes. Nodes... | Machine Learning |
What field is the article from? | Title: Best uses of ChatGPT and Generative AI for computer science research
Abstract: Generative Artificial Intelligence (AI), particularly tools like OpenAI's
popular ChatGPT, is reshaping the landscape of computer science research. Used
wisely, these tools can boost the productivity of a computer research
scientist. ... | Artificial Intelligence |
What field is the article from? | Title: Towards the Law of Capacity Gap in Distilling Language Models
Abstract: Language model (LM) distillation is a trending area that aims to distil the
knowledge resided in a large teacher LM to a small student one. While various
methods have been proposed to push the distillation to its limits, it is still
a pain d... | Computational Linguistics |
What field is the article from? | Title: Learning interactions to boost human creativity with bandits and GPT-4
Abstract: This paper considers how interactions with AI algorithms can boost human
creative thought. We employ a psychological task that demonstrates limits on
human creativity, namely semantic feature generation: given a concept name,
respon... | Artificial Intelligence |
What field is the article from? | Title: Classification for everyone : Building geography agnostic models for fairer recognition
Abstract: In this paper, we analyze different methods to mitigate inherent geographical
biases present in state of the art image classification models. We first
quantitatively present this bias in two datasets - The Dollar St... | Computer Vision |
What field is the article from? | Title: Learning Reusable Manipulation Strategies
Abstract: Humans demonstrate an impressive ability to acquire and generalize
manipulation "tricks." Even from a single demonstration, such as using soup
ladles to reach for distant objects, we can apply this skill to new scenarios
involving different object positions, si... | Robotics |
What field is the article from? | Title: Modeling the Telemarketing Process using Genetic Algorithms and Extreme Boosting: Feature Selection and Cost-Sensitive Analytical Approach
Abstract: Currently, almost all direct marketing activities take place virtually rather
than in person, weakening interpersonal skills at an alarming pace.
Furthermore, busin... | Machine Learning |
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