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What field is the article from? | Title: Arbitrarily Scalable Environment Generators via Neural Cellular Automata
Abstract: We study the problem of generating arbitrarily large environments to improve
the throughput of multi-robot systems. Prior work proposes Quality Diversity
(QD) algorithms as an effective method for optimizing the environments of
au... | Robotics |
What field is the article from? | Title: CROP: Conservative Reward for Model-based Offline Policy Optimization
Abstract: Offline reinforcement learning (RL) aims to optimize policy using collected
data without online interactions. Model-based approaches are particularly
appealing for addressing offline RL challenges due to their capability to
mitigate ... | Machine Learning |
What field is the article from? | Title: Bridging the Digital Divide: Performance Variation across Socio-Economic Factors in Vision-Language Models
Abstract: Despite the impressive performance of current AI models reported across
various tasks, performance reports often do not include evaluations of how
these models perform on the specific groups that ... | Computers and Society |
What field is the article from? | Title: ToP-ToM: Trust-aware Robot Policy with Theory of Mind
Abstract: Theory of Mind (ToM) is a fundamental cognitive architecture that endows
humans with the ability to attribute mental states to others. Humans infer the
desires, beliefs, and intentions of others by observing their behavior and, in
turn, adjust their... | Robotics |
What field is the article from? | Title: Evaluating Neural Language Models as Cognitive Models of Language Acquisition
Abstract: The success of neural language models (LMs) on many technological tasks has
brought about their potential relevance as scientific theories of language
despite some clear differences between LM training and child language
acqu... | Computational Linguistics |
What field is the article from? | Title: Testing Language Model Agents Safely in the Wild
Abstract: A prerequisite for safe autonomy-in-the-wild is safe testing-in-the-wild. Yet
real-world autonomous tests face several unique safety challenges, both due to
the possibility of causing harm during a test, as well as the risk of
encountering new unsafe age... | Artificial Intelligence |
What field is the article from? | Title: Don't Make Your LLM an Evaluation Benchmark Cheater
Abstract: Large language models~(LLMs) have greatly advanced the frontiers of
artificial intelligence, attaining remarkable improvement in model capacity. To
assess the model performance, a typical approach is to construct evaluation
benchmarks for measuring th... | Computational Linguistics |
What field is the article from? | Title: Structured Chemistry Reasoning with Large Language Models
Abstract: This paper studies the problem of solving complex chemistry problems with
large language models (LLMs). Despite the extensive general knowledge in LLMs
(such as GPT-4), they struggle with chemistry reasoning that requires faithful
grounded reaso... | Computational Linguistics |
What field is the article from? | Title: TabRepo: A Large Scale Repository of Tabular Model Evaluations and its AutoML Applications
Abstract: We introduce TabRepo, a new dataset of tabular model evaluations and
predictions. TabRepo contains the predictions and metrics of 1206 models
evaluated on 200 regression and classification datasets. We illustrate... | Machine Learning |
What field is the article from? | Title: PARK: Parkinson's Analysis with Remote Kinetic-tasks
Abstract: We present a web-based framework to screen for Parkinson's disease (PD) by
allowing users to perform neurological tests in their homes. Our web framework
guides the users to complete three tasks involving speech, facial expression,
and finger movemen... | Human-Computer Interaction |
What field is the article from? | Title: Fully Quantized Always-on Face Detector Considering Mobile Image Sensors
Abstract: Despite significant research on lightweight deep neural networks (DNNs)
designed for edge devices, the current face detectors do not fully meet the
requirements for "intelligent" CMOS image sensors (iCISs) integrated with
embedded... | Computer Vision |
What field is the article from? | Title: A Review of Hybrid and Ensemble in Deep Learning for Natural Language Processing
Abstract: This review presents a comprehensive exploration of hybrid and ensemble deep
learning models within Natural Language Processing (NLP), shedding light on
their transformative potential across diverse tasks such as Sentiment... | Artificial Intelligence |
What field is the article from? | Title: GCPV: Guided Concept Projection Vectors for the Explainable Inspection of CNN Feature Spaces
Abstract: For debugging and verification of computer vision convolutional deep neural
networks (CNNs) human inspection of the learned latent representations is
imperative. Therefore, state-of-the-art eXplainable Artifici... | Computer Vision |
What field is the article from? | Title: NeuroPrompts: An Adaptive Framework to Optimize Prompts for Text-to-Image Generation
Abstract: Despite impressive recent advances in text-to-image diffusion models,
obtaining high-quality images often requires prompt engineering by humans who
have developed expertise in using them. In this work, we present Neuro... | Artificial Intelligence |
What field is the article from? | Title: PELMS: Pre-training for Effective Low-Shot Multi-Document Summarization
Abstract: We investigate pre-training techniques for abstractive multi-document
summarization (MDS), which is much less studied than summarizing single
documents. Though recent work has demonstrated the effectiveness of
highlighting informat... | Computational Linguistics |
What field is the article from? | Title: Causal-CoG: A Causal-Effect Look at Context Generation for Boosting Multi-modal Language Models
Abstract: While Multi-modal Language Models (MLMs) demonstrate impressive multimodal
ability, they still struggle on providing factual and precise responses for
tasks like visual question answering (VQA). In this pape... | Artificial Intelligence |
What field is the article from? | Title: Transferring Modality-Aware Pedestrian Attentive Learning for Visible-Infrared Person Re-identification
Abstract: Visible-infrared person re-identification (VI-ReID) aims to search the same
pedestrian of interest across visible and infrared modalities. Existing models
mainly focus on compensating for modality-sp... | Computer Vision |
What field is the article from? | Title: D3A-TS: Denoising-Driven Data Augmentation in Time Series
Abstract: It has been demonstrated that the amount of data is crucial in data-driven
machine learning methods. Data is always valuable, but in some tasks, it is
almost like gold. This occurs in engineering areas where data is scarce or very
expensive to o... | Artificial Intelligence |
What field is the article from? | Title: Findings of the WMT 2023 Shared Task on Discourse-Level Literary Translation: A Fresh Orb in the Cosmos of LLMs
Abstract: Translating literary works has perennially stood as an elusive dream in
machine translation (MT), a journey steeped in intricate challenges. To foster
progress in this domain, we hold a new s... | Computational Linguistics |
What field is the article from? | Title: UINav: A maker of UI automation agents
Abstract: An automation system that can execute natural language instructions by
driving the user interface (UI) of an application can benefit users, especially
when situationally or permanently impaired. Traditional automation systems
(manual scripting, programming by demo... | Human-Computer Interaction |
What field is the article from? | Title: Advancing Urban Renewal: An Automated Approach to Generating Historical Arcade Facades with Stable Diffusion Models
Abstract: Urban renewal and transformation processes necessitate the preservation of
the historical urban fabric, particularly in districts known for their
architectural and historical significance... | Computer Vision |
What field is the article from? | Title: Technical Note: Feasibility of translating 3.0T-trained Deep-Learning Segmentation Models Out-of-the-Box on Low-Field MRI 0.55T Knee-MRI of Healthy Controls
Abstract: In the current study, our purpose is to evaluate the feasibility of applying
deep learning (DL) enabled algorithms to quantify bilateral knee biom... | Computer Vision |
What field is the article from? | Title: Context Matter: Data-Efficient Augmentation of Large Language Models for Scientific Applications
Abstract: In this paper, we explore the challenges inherent to Large Language Models
(LLMs) like GPT-4, particularly their propensity for hallucinations, logic
mistakes, and incorrect conclusions when tasked with ans... | Computational Linguistics |
What field is the article from? | Title: A Survey of Language Model Confidence Estimation and Calibration
Abstract: Language models (LMs) have demonstrated remarkable capabilities across a wide
range of tasks in various domains. Despite their impressive performance, the
reliability of their output is concerning and questionable regarding the demand
for... | Computational Linguistics |
What field is the article from? | Title: Aligner: One Global Token is Worth Millions of Parameters When Aligning Large Language Models
Abstract: We introduce Aligner, a novel Parameter-Efficient Fine-Tuning (PEFT) method
for aligning multi-billion-parameter-sized Large Language Models (LLMs).
Aligner employs a unique design that constructs a globally s... | Computational Linguistics |
What field is the article from? | Title: Augmentation-Free Dense Contrastive Knowledge Distillation for Efficient Semantic Segmentation
Abstract: In recent years, knowledge distillation methods based on contrastive learning
have achieved promising results on image classification and object detection
tasks. However, in this line of research, we note tha... | Computer Vision |
What field is the article from? | Title: Newvision: application for helping blind people using deep learning
Abstract: As able-bodied people, we often take our vision for granted. For people who
are visually impaired, however, their disability can have a significant impact
on their daily lives. We are developing proprietary headgear that will help
visu... | Human-Computer Interaction |
What field is the article from? | Title: NeuSD: Surface Completion with Multi-View Text-to-Image Diffusion
Abstract: We present a novel method for 3D surface reconstruction from multiple images
where only a part of the object of interest is captured. Our approach builds on
two recent developments: surface reconstruction using neural radiance fields
for... | Computer Vision |
What field is the article from? | Title: Intriguing Properties of Data Attribution on Diffusion Models
Abstract: Data attribution seeks to trace model outputs back to training data. With the
recent development of diffusion models, data attribution has become a desired
module to properly assign valuations for high-quality or copyrighted training
samples... | Machine Learning |
What field is the article from? | Title: LoRA Fine-tuning Efficiently Undoes Safety Training in Llama 2-Chat 70B
Abstract: AI developers often apply safety alignment procedures to prevent the misuse
of their AI systems. For example, before Meta released Llama 2-Chat, a
collection of instruction fine-tuned large language models, they invested
heavily in... | Machine Learning |
What field is the article from? | Title: DiT-Head: High-Resolution Talking Head Synthesis using Diffusion Transformers
Abstract: We propose a novel talking head synthesis pipeline called "DiT-Head", which
is based on diffusion transformers and uses audio as a condition to drive the
denoising process of a diffusion model. Our method is scalable and can
... | Artificial Intelligence |
What field is the article from? | Title: TransNeXt: Robust Foveal Visual Perception for Vision Transformers
Abstract: Due to the depth degradation effect in residual connections, many efficient
Vision Transformers models that rely on stacking layers for information
exchange often fail to form sufficient information mixing, leading to unnatural
visual p... | Computer Vision |
What field is the article from? | Title: TransCORALNet: A Two-Stream Transformer CORAL Networks for Supply Chain Credit Assessment Cold Start
Abstract: This paper proposes an interpretable two-stream transformer CORAL networks
(TransCORALNet) for supply chain credit assessment under the segment industry
and cold start problem. The model aims to provide... | Machine Learning |
What field is the article from? | Title: Federated Learning for Clinical Structured Data: A Benchmark Comparison of Engineering and Statistical Approaches
Abstract: Federated learning (FL) has shown promising potential in safeguarding data
privacy in healthcare collaborations. While the term "FL" was originally coined
by the engineering community, the ... | Machine Learning |
What field is the article from? | Title: Towards Goal-oriented Intelligent Tutoring Systems in Online Education
Abstract: Interactive Intelligent Tutoring Systems (ITSs) enhance traditional ITSs by
promoting effective learning through interactions and problem resolution in
online education. Yet, proactive engagement, prioritizing resource optimization
... | Computers and Society |
What field is the article from? | Title: TimeBench: A Comprehensive Evaluation of Temporal Reasoning Abilities in Large Language Models
Abstract: Understanding time is a pivotal aspect of human cognition, crucial in the
broader framework of grasping the intricacies of the world. Previous studies
typically focus on specific aspects of time, lacking a co... | Computational Linguistics |
What field is the article from? | Title: Unsupervised Extractive Summarization with Learnable Length Control Strategies
Abstract: Unsupervised extractive summarization is an important technique in
information extraction and retrieval. Compared with supervised method, it does
not require high-quality human-labelled summaries for training and thus can be... | Artificial Intelligence |
What field is the article from? | Title: Responsible AI (RAI) Games and Ensembles
Abstract: Several recent works have studied the societal effects of AI; these include
issues such as fairness, robustness, and safety. In many of these objectives, a
learner seeks to minimize its worst-case loss over a set of predefined
distributions (known as uncertainty... | Artificial Intelligence |
What field is the article from? | Title: Evaluating Uncertainty Quantification approaches for Neural PDEs in scientific applications
Abstract: The accessibility of spatially distributed data, enabled by affordable
sensors, field, and numerical experiments, has facilitated the development of
data-driven solutions for scientific problems, including clima... | Machine Learning |
What field is the article from? | Title: Artificial Intelligence in the Service of Entrepreneurial Finance: Knowledge Structure and the Foundational Algorithmic Paradigm
Abstract: While the application of Artificial Intelligence in Finance has a long
tradition, its potential in Entrepreneurship has been intensively explored only
recently. In this conte... | Artificial Intelligence |
What field is the article from? | Title: When is Off-Policy Evaluation Useful? A Data-Centric Perspective
Abstract: Evaluating the value of a hypothetical target policy with only a logged
dataset is important but challenging. On the one hand, it brings opportunities
for safe policy improvement under high-stakes scenarios like clinical
guidelines. On th... | Machine Learning |
What field is the article from? | Title: Benchmark Generation Framework with Customizable Distortions for Image Classifier Robustness
Abstract: We present a novel framework for generating adversarial benchmarks to
evaluate the robustness of image classification models. Our framework allows
users to customize the types of distortions to be optimally app... | Computer Vision |
What field is the article from? | Title: Accurate and Fast Fischer-Tropsch Reaction Microkinetics using PINNs
Abstract: Microkinetics allows detailed modelling of chemical transformations occurring
in many industrially relevant reactions. Traditional way of solving the
microkinetics model for Fischer-Tropsch synthesis (FTS) becomes inefficient
when it ... | Machine Learning |
What field is the article from? | Title: Knowledge-Aware Artifact Image Synthesis with LLM-Enhanced Prompting and Multi-Source Supervision
Abstract: Ancient artifacts are an important medium for cultural preservation and
restoration. However, many physical copies of artifacts are either damaged or
lost, leaving a blank space in archaeological and histo... | Computer Vision |
What field is the article from? | Title: FedGeo: Privacy-Preserving User Next Location Prediction with Federated Learning
Abstract: A User Next Location Prediction (UNLP) task, which predicts the next location
that a user will move to given his/her trajectory, is an indispensable task for
a wide range of applications. Previous studies using large-scale... | Cryptography and Security |
What field is the article from? | Title: Parameter-Efficient Multilingual Summarisation: An Empirical Study
Abstract: With the increasing prevalence of Large Language Models, traditional full
fine-tuning approaches face growing challenges, especially in memory-intensive
tasks. This paper investigates the potential of Parameter-Efficient
Fine-Tuning, fo... | Computational Linguistics |
What field is the article from? | Title: Safety, Trust, and Ethics Considerations for Human-AI Teaming in Aerospace Control
Abstract: Designing a safe, trusted, and ethical AI may be practically impossible;
however, designing AI with safe, trusted, and ethical use in mind is possible
and necessary in safety and mission-critical domains like aerospace. ... | Computers and Society |
What field is the article from? | Title: Collaborating Foundation models for Domain Generalized Semantic Segmentation
Abstract: Domain Generalized Semantic Segmentation (DGSS) deals with training a model
on a labeled source domain with the aim of generalizing to unseen domains
during inference. Existing DGSS methods typically effectuate robust features... | Computer Vision |
What field is the article from? | Title: An Embodied Generalist Agent in 3D World
Abstract: Leveraging massive knowledge and learning schemes from large language models
(LLMs), recent machine learning models show notable successes in building
generalist agents that exhibit the capability of general-purpose task solving
in diverse domains, including nat... | Computer Vision |
What field is the article from? | Title: From Classification to Clinical Insights: Towards Analyzing and Reasoning About Mobile and Behavioral Health Data With Large Language Models
Abstract: Passively collected behavioral health data from ubiquitous sensors holds
significant promise to provide mental health professionals insights from
patient's daily ... | Artificial Intelligence |
What field is the article from? | Title: Learning Curricula in Open-Ended Worlds
Abstract: Deep reinforcement learning (RL) provides powerful methods for training
optimal sequential decision-making agents. As collecting real-world
interactions can entail additional costs and safety risks, the common paradigm
of sim2real conducts training in a simulator... | Artificial Intelligence |
What field is the article from? | Title: Language Models can be Logical Solvers
Abstract: Logical reasoning is a fundamental aspect of human intelligence and a key
component of tasks like problem-solving and decision-making. Recent
advancements have enabled Large Language Models (LLMs) to potentially exhibit
reasoning capabilities, but complex logical ... | Computational Linguistics |
What field is the article from? | Title: MIMo: A Multi-Modal Infant Model for Studying Cognitive Development
Abstract: Human intelligence and human consciousness emerge gradually during the
process of cognitive development. Understanding this development is an
essential aspect of understanding the human mind and may facilitate the
construction of artif... | Artificial Intelligence |
What field is the article from? | Title: Stochastic Bayesian Optimization with Unknown Continuous Context Distribution via Kernel Density Estimation
Abstract: Bayesian optimization (BO) is a sample-efficient method and has been widely
used for optimizing expensive black-box functions. Recently, there has been a
considerable interest in BO literature in... | Machine Learning |
What field is the article from? | Title: Instance-wise Linearization of Neural Network for Model Interpretation
Abstract: Neural network have achieved remarkable successes in many scientific fields.
However, the interpretability of the neural network model is still a major
bottlenecks to deploy such technique into our daily life. The challenge can
dive... | Machine Learning |
What field is the article from? | Title: Adaptive Compression of the Latent Space in Variational Autoencoders
Abstract: Variational Autoencoders (VAEs) are powerful generative models that have been
widely used in various fields, including image and text generation. However,
one of the known challenges in using VAEs is the model's sensitivity to its
hyp... | Machine Learning |
What field is the article from? | Title: Matching Weak Informative Ontologies
Abstract: Most existing ontology matching methods utilize the literal information to
discover alignments. However, some literal information in ontologies may be
opaque and some ontologies may not have sufficient literal information. In this
paper, these ontologies are named a... | Artificial Intelligence |
What field is the article from? | Title: Arabic Mini-ClimateGPT : A Climate Change and Sustainability Tailored Arabic LLM
Abstract: Climate change is one of the most significant challenges we face together as
a society. Creating awareness and educating policy makers the wide-ranging
impact of climate change is an essential step towards a sustainable fu... | Computational Linguistics |
What field is the article from? | Title: Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning
Abstract: Neural MMO 2.0 is a massively multi-agent environment for reinforcement
learning research. The key feature of this new version is a flexible task
system that allows users to define a broad range of objectives and reward
s... | Artificial Intelligence |
What field is the article from? | Title: Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals
Abstract: Transformers have achieved remarkable success in a wide range of natural
language processing and computer vision applications. However, the
representation capacity of a deep transformer model is degraded due to the
over-smoo... | Computational Linguistics |
What field is the article from? | Title: Rethinking Dimensional Rationale in Graph Contrastive Learning from Causal Perspective
Abstract: Graph contrastive learning is a general learning paradigm excelling at
capturing invariant information from diverse perturbations in graphs. Recent
works focus on exploring the structural rationale from graphs, there... | Machine Learning |
What field is the article from? | Title: Plum: Prompt Learning using Metaheuristic
Abstract: Since the emergence of large language models, prompt learning has become a
popular method for optimizing and customizing these models. Special prompts,
such as Chain-of-Thought, have even revealed previously unknown reasoning
capabilities within these models. H... | Machine Learning |
What field is the article from? | Title: Similarity-based Knowledge Transfer for Cross-Domain Reinforcement Learning
Abstract: Transferring knowledge in cross-domain reinforcement learning is a
challenging setting in which learning is accelerated by reusing knowledge from
a task with different observation and/or action space. However, it is often
neces... | Machine Learning |
What field is the article from? | Title: Evaluating AI Vocational Skills Through Professional Testing
Abstract: Using a novel professional certification survey, the study focuses on
assessing the vocational skills of two highly cited AI models, GPT-3 and
Turbo-GPT3.5. The approach emphasizes the importance of practical readiness
over academic performan... | Machine Learning |
What field is the article from? | Title: VisPercep: A Vision-Language Approach to Enhance Visual Perception for People with Blindness and Low Vision
Abstract: People with blindness and low vision (pBLV) encounter substantial challenges
when it comes to comprehensive scene recognition and precise object
identification in unfamiliar environments. Additio... | Computer Vision |
What field is the article from? | Title: nach0: Multimodal Natural and Chemical Languages Foundation Model
Abstract: Large Language Models (LLMs) have substantially driven scientific progress in
various domains, and many papers have demonstrated their ability to tackle
complex problems with creative solutions. Our paper introduces a new foundation
mode... | Computational Linguistics |
What field is the article from? | Title: Conceptual Engineering Using Large Language Models
Abstract: We describe a method, based on Jennifer Nado's definition of classification
procedures as targets of conceptual engineering, that implements such
procedures using a large language model. We then apply this method using data
from the Wikidata knowledge ... | Computational Linguistics |
What field is the article from? | Title: Patch-MI: Enhancing Model Inversion Attacks via Patch-Based Reconstruction
Abstract: Model inversion (MI) attacks aim to reveal sensitive information in training
datasets by solely accessing model weights. Generative MI attacks, a prominent
strand in this field, utilize auxiliary datasets to recreate target data... | Artificial Intelligence |
What field is the article from? | Title: TrustMark: Universal Watermarking for Arbitrary Resolution Images
Abstract: Imperceptible digital watermarking is important in copyright protection,
misinformation prevention, and responsible generative AI. We propose TrustMark
- a GAN-based watermarking method with novel design in architecture and
spatio-spectr... | Computer Vision |
What field is the article from? | Title: UI Layout Generation with LLMs Guided by UI Grammar
Abstract: The recent advances in Large Language Models (LLMs) have stimulated interest
among researchers and industry professionals, particularly in their application
to tasks concerning mobile user interfaces (UIs). This position paper
investigates the use of ... | Human-Computer Interaction |
What field is the article from? | Title: Context Tuning for Retrieval Augmented Generation
Abstract: Large language models (LLMs) have the remarkable ability to solve new tasks
with just a few examples, but they need access to the right tools. Retrieval
Augmented Generation (RAG) addresses this problem by retrieving a list of
relevant tools for a given... | Information Retrieval |
What field is the article from? | Title: Universal Self-Consistency for Large Language Model Generation
Abstract: Self-consistency with chain-of-thought prompting (CoT) has demonstrated
remarkable performance gains on various challenging tasks, by utilizing
multiple reasoning paths sampled from large language models (LLMs). However,
self-consistency re... | Computational Linguistics |
What field is the article from? | Title: The Behavior of Large Language Models When Prompted to Generate Code Explanations
Abstract: This paper systematically investigates the generation of code explanations by
Large Language Models (LLMs) for code examples commonly encountered in
introductory programming courses. Our findings reveal significant variat... | Software Engineering |
What field is the article from? | Title: Multi-perspective Feedback-attention Coupling Model for Continuous-time Dynamic Graphs
Abstract: Recently, representation learning over graph networks has gained popularity,
with various models showing promising results. Despite this, several challenges
persist: 1) most methods are designed for static or discret... | Machine Learning |
What field is the article from? | Title: Conditions for Length Generalization in Learning Reasoning Skills
Abstract: Reasoning is a fundamental capability of AI agents. Recently, large language
models (LLMs) have shown remarkable abilities to perform reasoning tasks.
However, numerous evaluations of the reasoning capabilities of LLMs have also
showed s... | Artificial Intelligence |
What field is the article from? | Title: Probabilistic Forecast Reconciliation with Kullback-Leibler Divergence Regularization
Abstract: As the popularity of hierarchical point forecast reconciliation methods
increases, there is a growing interest in probabilistic forecast
reconciliation. Many studies have utilized machine learning or deep learning
tec... | Artificial Intelligence |
What field is the article from? | Title: How Trustworthy are Open-Source LLMs? An Assessment under Malicious Demonstrations Shows their Vulnerabilities
Abstract: The rapid progress in open-source Large Language Models (LLMs) is
significantly driving AI development forward. However, there is still a limited
understanding of their trustworthiness. Deploy... | Computational Linguistics |
What field is the article from? | Title: HypUC: Hyperfine Uncertainty Calibration with Gradient-boosted Corrections for Reliable Regression on Imbalanced Electrocardiograms
Abstract: The automated analysis of medical time series, such as the electrocardiogram
(ECG), electroencephalogram (EEG), pulse oximetry, etc, has the potential to
serve as a valuab... | Machine Learning |
What field is the article from? | Title: The theoretical limits of biometry
Abstract: Biometry has proved its capability in terms of recognition accuracy. Now, it
is widely used for automated border control with the biometric passport, to
unlock a smartphone or a computer with a fingerprint or a face recognition
algorithm. While identity verification i... | Cryptography and Security |
What field is the article from? | Title: Federated Natural Policy Gradient Methods for Multi-task Reinforcement Learning
Abstract: Federated reinforcement learning (RL) enables collaborative decision making
of multiple distributed agents without sharing local data trajectories. In this
work, we consider a multi-task setting, in which each agent has its... | Machine Learning |
What field is the article from? | Title: Dynamic V2X Autonomous Perception from Road-to-Vehicle Vision
Abstract: Vehicle-to-everything (V2X) perception is an innovative technology that
enhances vehicle perception accuracy, thereby elevating the security and
reliability of autonomous systems. However, existing V2X perception methods
focus on static scen... | Computer Vision |
What field is the article from? | Title: Exploring Large Language Models to Facilitate Variable Autonomy for Human-Robot Teaming
Abstract: In a rapidly evolving digital landscape autonomous tools and robots are
becoming commonplace. Recognizing the significance of this development, this
paper explores the integration of Large Language Models (LLMs) lik... | Human-Computer Interaction |
What field is the article from? | Title: Homogeneous Artificial Neural Network
Abstract: The paper proposes an artificial neural network (ANN) being a global
approximator for a special class of functions, which are known as generalized
homogeneous. The homogeneity means a symmetry of a function with respect to a
group of transformations having topologi... | Machine Learning |
What field is the article from? | Title: Physics simulation capabilities of LLMs
Abstract: [Abridged abstract] Large Language Models (LLMs) can solve some
undergraduate-level to graduate-level physics textbook problems and are
proficient at coding. Combining these two capabilities could one day enable AI
systems to simulate and predict the physical wor... | Artificial Intelligence |
What field is the article from? | Title: Scaling #DNN-Verification Tools with Efficient Bound Propagation and Parallel Computing
Abstract: Deep Neural Networks (DNNs) are powerful tools that have shown extraordinary
results in many scenarios, ranging from pattern recognition to complex robotic
problems. However, their intricate designs and lack of tran... | Artificial Intelligence |
What field is the article from? | Title: KBFormer: A Diffusion Model for Structured Entity Completion
Abstract: We develop a generative attention-based approach to modeling structured
entities comprising different property types, such as numerical, categorical,
string, and composite. This approach handles such heterogeneous data through a
mixed continu... | Machine Learning |
What field is the article from? | Title: Model-Based Runtime Monitoring with Interactive Imitation Learning
Abstract: Robot learning methods have recently made great strides, but generalization
and robustness challenges still hinder their widespread deployment. Failing to
detect and address potential failures renders state-of-the-art learning systems
n... | Robotics |
What field is the article from? | Title: Towards Conceptualization of "Fair Explanation": Disparate Impacts of anti-Asian Hate Speech Explanations on Content Moderators
Abstract: Recent research at the intersection of AI explainability and fairness has
focused on how explanations can improve human-plus-AI task performance as
assessed by fairness measur... | Computational Linguistics |
What field is the article from? | Title: ExPT: Synthetic Pretraining for Few-Shot Experimental Design
Abstract: Experimental design is a fundamental problem in many science and engineering
fields. In this problem, sample efficiency is crucial due to the time, money,
and safety costs of real-world design evaluations. Existing approaches either
rely on a... | Machine Learning |
What field is the article from? | Title: How Generative-AI can be Effectively used in Government Chatbots
Abstract: With the rapid development of artificial intelligence and breakthroughs in
machine learning and natural language processing, intelligent
question-answering robots have become widely used in government affairs. This
paper conducts a horizo... | Computational Linguistics |
What field is the article from? | Title: Synergizing Human-AI Agency: A Guide of 23 Heuristics for Service Co-Creation with LLM-Based Agents
Abstract: This empirical study serves as a primer for interested service providers to
determine if and how Large Language Models (LLMs) technology will be integrated
for their practitioners and the broader communi... | Human-Computer Interaction |
What field is the article from? | Title: Heterogeneous Graph Neural Architecture Search with GPT-4
Abstract: Heterogeneous graph neural architecture search (HGNAS) represents a powerful
tool for automatically designing effective heterogeneous graph neural networks.
However, existing HGNAS algorithms suffer from inefficient searches and
unstable results... | Artificial Intelligence |
What field is the article from? | Title: The Alignment Problem in Context
Abstract: A core challenge in the development of increasingly capable AI systems is to
make them safe and reliable by ensuring their behaviour is consistent with
human values. This challenge, known as the alignment problem, does not merely
apply to hypothetical future AI systems ... | Machine Learning |
What field is the article from? | Title: Sample Efficient Reinforcement Learning from Human Feedback via Active Exploration
Abstract: Preference-based feedback is important for many applications in reinforcement
learning where direct evaluation of a reward function is not feasible. A
notable recent example arises in reinforcement learning from human fe... | Machine Learning |
What field is the article from? | Title: Operator-learning-inspired Modeling of Neural Ordinary Differential Equations
Abstract: Neural ordinary differential equations (NODEs), one of the most influential
works of the differential equation-based deep learning, are to continuously
generalize residual networks and opened a new field. They are currently
u... | Machine Learning |
What field is the article from? | Title: SCPO: Safe Reinforcement Learning with Safety Critic Policy Optimization
Abstract: Incorporating safety is an essential prerequisite for broadening the
practical applications of reinforcement learning in real-world scenarios. To
tackle this challenge, Constrained Markov Decision Processes (CMDPs) are
leveraged, ... | Machine Learning |
What field is the article from? | Title: MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI
Abstract: We introduce MMMU: a new benchmark designed to evaluate multimodal models on
massive multi-discipline tasks demanding college-level subject knowledge and
deliberate reasoning. MMMU includes 11.5K meticulous... | Computational Linguistics |
What field is the article from? | Title: Learning from One Continuous Video Stream
Abstract: We introduce a framework for online learning from a single continuous video
stream -- the way people and animals learn, without mini-batches, data
augmentation or shuffling. This poses great challenges given the high
correlation between consecutive video frames... | Computer Vision |
What field is the article from? | Title: Stochastic Configuration Machines: FPGA Implementation
Abstract: Neural networks for industrial applications generally have additional
constraints such as response speed, memory size and power usage. Randomized
learners can address some of these issues. However, hardware solutions can
provide better resource red... | Machine Learning |
What field is the article from? | Title: Concept-centric Personalization with Large-scale Diffusion Priors
Abstract: Despite large-scale diffusion models being highly capable of generating
diverse open-world content, they still struggle to match the photorealism and
fidelity of concept-specific generators. In this work, we present the task of
customizi... | Computer Vision |
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