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What field is the article from? | Title: Latent Lab: Large Language Models for Knowledge Exploration
Abstract: This paper investigates the potential of AI models, particularly large
language models (LLMs), to support knowledge exploration and augment human
creativity during ideation. We present "Latent Lab" an interactive tool for
discovering connectio... | Artificial Intelligence |
What field is the article from? | Title: Taming Gradient Variance in Federated Learning with Networked Control Variates
Abstract: Federated learning, a decentralized approach to machine learning, faces
significant challenges such as extensive communication overheads, slow
convergence, and unstable improvements. These challenges primarily stem from
the ... | Machine Learning |
What field is the article from? | Title: Direct Preference-Based Evolutionary Multi-Objective Optimization with Dueling Bandit
Abstract: Optimization problems find widespread use in both single-objective and
multi-objective scenarios. In practical applications, users aspire for
solutions that converge to the region of interest (ROI) along the Pareto fr... | Artificial Intelligence |
What field is the article from? | Title: MAFALDA: A Benchmark and Comprehensive Study of Fallacy Detection and Classification
Abstract: Fallacies can be used to spread disinformation, fake news, and propaganda,
underlining the importance of their detection. Automated detection and
classification of fallacies, however, remain challenging, mainly because... | Computational Linguistics |
What field is the article from? | Title: LSTM Network Analysis of Vehicle-Type Fatalities on Great Britain's Roads
Abstract: This study harnesses the predictive capabilities of Long Short-Term Memory
(LSTM) networks to analyse and predict road traffic accidents in Great Britain.
It addresses the challenge of traffic accident forecasting, which is param... | Machine Learning |
What field is the article from? | Title: The Energy Prediction Smart-Meter Dataset: Analysis of Previous Competitions and Beyond
Abstract: This paper presents the real-world smart-meter dataset and offers an analysis
of solutions derived from the Energy Prediction Technical Challenges, focusing
primarily on two key competitions: the IEEE Computational ... | Machine Learning |
What field is the article from? | Title: Linear time Evidence Accumulation Clustering with KMeans
Abstract: Among ensemble clustering methods, Evidence Accumulation Clustering is one of
the simplest technics. In this approach, a co-association (CA) matrix
representing the co-clustering frequency is built and then clustered to extract
consensus clusters... | Machine Learning |
What field is the article from? | Title: Navigating the Ocean of Biases: Political Bias Attribution in Language Models via Causal Structures
Abstract: The rapid advancement of Large Language Models (LLMs) has sparked intense
debate regarding their ability to perceive and interpret complex
socio-political landscapes. In this study, we undertake an explo... | Computational Linguistics |
What field is the article from? | Title: Improving Pacing in Long-Form Story Planning
Abstract: Existing LLM-based systems for writing long-form stories or story outlines
frequently suffer from unnatural pacing, whether glossing over important events
or over-elaborating on insignificant details, resulting in a jarring experience
for the reader. We prop... | Computational Linguistics |
What field is the article from? | Title: From Concept to Manufacturing: Evaluating Vision-Language Models for Engineering Design
Abstract: Engineering Design is undergoing a transformative shift with the advent of
AI, marking a new era in how we approach product, system, and service planning.
Large language models have demonstrated impressive capabilit... | Artificial Intelligence |
What field is the article from? | Title: Learning From Mistakes Makes LLM Better Reasoner
Abstract: Large language models (LLMs) recently exhibited remarkable reasoning
capabilities on solving math problems. To further improve this capability, this
work proposes Learning from Mistakes (LeMa), akin to human learning processes.
Consider a human student w... | Computational Linguistics |
What field is the article from? | Title: Which way is `right'?: Uncovering limitations of Vision-and-Language Navigation model
Abstract: The challenging task of Vision-and-Language Navigation (VLN) requires
embodied agents to follow natural language instructions to reach a goal
location or object (e.g. `walk down the hallway and turn left at the piano'... | Computer Vision |
What field is the article from? | Title: Sub-Sentence Encoder: Contrastive Learning of Propositional Semantic Representations
Abstract: We introduce sub-sentence encoder, a contrastively-learned contextual
embedding model for fine-grained semantic representation of text. In contrast
to the standard practice with sentence embeddings, where the meaning o... | Computational Linguistics |
What field is the article from? | Title: Replicable Benchmarking of Neural Machine Translation (NMT) on Low-Resource Local Languages in Indonesia
Abstract: Neural machine translation (NMT) for low-resource local languages in
Indonesia faces significant challenges, including the need for a representative
benchmark and limited data availability. This wor... | Computational Linguistics |
What field is the article from? | Title: Morphology-Enhanced CAM-Guided SAM for weakly supervised Breast Lesion Segmentation
Abstract: Breast cancer diagnosis challenges both patients and clinicians, with early
detection being crucial for effective treatment. Ultrasound imaging plays a key
role in this, but its utility is hampered by the need for preci... | Computer Vision |
What field is the article from? | Title: A Survey on Large Language Models for Personalized and Explainable Recommendations
Abstract: In recent years, Recommender Systems(RS) have witnessed a transformative
shift with the advent of Large Language Models(LLMs) in the field of Natural
Language Processing(NLP). These models such as OpenAI's GPT-3.5/4, Lla... | Information Retrieval |
What field is the article from? | Title: An Evaluation of GPT-4V and Gemini in Online VQA
Abstract: A comprehensive evaluation is critical to assess the capabilities of large
multimodal models (LMM). In this study, we evaluate the state-of-the-art LMMs,
namely GPT-4V and Gemini, utilizing the VQAonline dataset. VQAonline is an
end-to-end authentic VQA ... | Computer Vision |
What field is the article from? | Title: Designing AI Support for Human Involvement in AI-assisted Decision Making: A Taxonomy of Human-AI Interactions from a Systematic Review
Abstract: Efforts in levering Artificial Intelligence (AI) in decision support systems
have disproportionately focused on technological advancements, often
overlooking the align... | Human-Computer Interaction |
What field is the article from? | Title: Perceptual Group Tokenizer: Building Perception with Iterative Grouping
Abstract: Human visual recognition system shows astonishing capability of compressing
visual information into a set of tokens containing rich representations without
label supervision. One critical driving principle behind it is perceptual
g... | Computer Vision |
What field is the article from? | Title: Brain Networks and Intelligence: A Graph Neural Network Based Approach to Resting State fMRI Data
Abstract: Resting-state functional magnetic resonance imaging (rsfMRI) is a powerful
tool for investigating the relationship between brain function and cognitive
processes as it allows for the functional organizatio... | Machine Learning |
What field is the article from? | Title: Interpretable Long Term Waypoint-Based Trajectory Prediction Model
Abstract: Predicting the future trajectories of dynamic agents in complex environments
is crucial for a variety of applications, including autonomous driving,
robotics, and human-computer interaction. It is a challenging task as the
behavior of t... | Artificial Intelligence |
What field is the article from? | Title: Integrating Pre-trained Language Model into Neural Machine Translation
Abstract: Neural Machine Translation (NMT) has become a significant technology in
natural language processing through extensive research and development.
However, the deficiency of high-quality bilingual language pair data still
poses a major... | Computational Linguistics |
What field is the article from? | Title: A Vision for Operationalising Diversity and Inclusion in AI
Abstract: The growing presence of Artificial Intelligence (AI) in various sectors
necessitates systems that accurately reflect societal diversity. This study
seeks to envision the operationalization of the ethical imperatives of
diversity and inclusion ... | Artificial Intelligence |
What field is the article from? | Title: Active teacher selection for reinforcement learning from human feedback
Abstract: Reinforcement learning from human feedback (RLHF) enables machine learning
systems to learn objectives from human feedback. A core limitation of these
systems is their assumption that all feedback comes from a single human
teacher,... | Artificial Intelligence |
What field is the article from? | Title: Rethinking and Benchmarking Predict-then-Optimize Paradigm for Combinatorial Optimization Problems
Abstract: Numerous web applications rely on solving combinatorial optimization
problems, such as energy cost-aware scheduling, budget allocation on web
advertising, and graph matching on social networks. However, m... | Machine Learning |
What field is the article from? | Title: BrainWash: A Poisoning Attack to Forget in Continual Learning
Abstract: Continual learning has gained substantial attention within the deep learning
community, offering promising solutions to the challenging problem of
sequential learning. Yet, a largely unexplored facet of this paradigm is its
susceptibility to... | Machine Learning |
What field is the article from? | Title: Tamil-Llama: A New Tamil Language Model Based on Llama 2
Abstract: Language modeling has witnessed remarkable advancements in recent years, with
Large Language Models (LLMs) like ChatGPT setting unparalleled benchmarks in
human-like text generation. However, a prevailing limitation is the
underrepresentation of ... | Computational Linguistics |
What field is the article from? | Title: RecExplainer: Aligning Large Language Models for Recommendation Model Interpretability
Abstract: Recommender systems are widely used in various online services, with
embedding-based models being particularly popular due to their expressiveness
in representing complex signals. However, these models often lack
int... | Information Retrieval |
What field is the article from? | Title: Code Models are Zero-shot Precondition Reasoners
Abstract: One of the fundamental skills required for an agent acting in an environment
to complete tasks is the ability to understand what actions are plausible at
any given point. This work explores a novel use of code representations to
reason about action preco... | Artificial Intelligence |
What field is the article from? | Title: On the Multiple Roles of Ontologies in Explainable AI
Abstract: This paper discusses the different roles that explicit knowledge, in
particular ontologies, can play in Explainable AI and in the development of
human-centric explainable systems and intelligible explanations. We consider
three main perspectives in ... | Artificial Intelligence |
What field is the article from? | Title: A Survey of Generative AI for Intelligent Transportation Systems
Abstract: Intelligent transportation systems play a crucial role in modern traffic
management and optimization, greatly improving traffic efficiency and safety.
With the rapid development of generative artificial intelligence (Generative
AI) techno... | Artificial Intelligence |
What field is the article from? | Title: Age-Friendly Route Planner: Calculating Comfortable Routes for Senior Citizens
Abstract: The application of routing algorithms to real-world situations is a widely
studied research topic. Despite this, routing algorithms and applications are
usually developed for a general purpose, meaning that certain groups, s... | Artificial Intelligence |
What field is the article from? | Title: On Meta-Prompting
Abstract: Certain statistical models are capable of interpreting input strings as
instructions, or prompts, and carry out tasks based on them. Many approaches to
prompting and pre-training these models involve the automated generation of
these prompts. We call these approaches meta-prompting, o... | Computational Linguistics |
What field is the article from? | Title: Frequency Domain-based Dataset Distillation
Abstract: This paper presents FreD, a novel parameterization method for dataset
distillation, which utilizes the frequency domain to distill a small-sized
synthetic dataset from a large-sized original dataset. Unlike conventional
approaches that focus on the spatial do... | Machine Learning |
What field is the article from? | Title: Divergences between Language Models and Human Brains
Abstract: Do machines and humans process language in similar ways? A recent line of
research has hinted in the affirmative, demonstrating that human brain signals
can be effectively predicted using the internal representations of language
models (LMs). This is... | Computational Linguistics |
What field is the article from? | Title: Irreducible Curriculum for Language Model Pretraining
Abstract: Automatic data selection and curriculum design for training large language
models is challenging, with only a few existing methods showing improvements
over standard training. Furthermore, current schemes focus on domain-level
selection, overlooking... | Computational Linguistics |
What field is the article from? | Title: Why "classic" Transformers are shallow and how to make them go deep
Abstract: Since its introduction in 2017, Transformer has emerged as the leading neural
network architecture, catalyzing revolutionary advancements in many AI
disciplines. The key innovation in Transformer is a Self-Attention (SA)
mechanism desi... | Machine Learning |
What field is the article from? | Title: Deployment of a Robust and Explainable Mortality Prediction Model: The COVID-19 Pandemic and Beyond
Abstract: This study investigated the performance, explainability, and robustness of
deployed artificial intelligence (AI) models in predicting mortality during the
COVID-19 pandemic and beyond. The first study of... | Machine Learning |
What field is the article from? | Title: UniFolding: Towards Sample-efficient, Scalable, and Generalizable Robotic Garment Folding
Abstract: This paper explores the development of UniFolding, a sample-efficient,
scalable, and generalizable robotic system for unfolding and folding various
garments. UniFolding employs the proposed UFONet neural network t... | Robotics |
What field is the article from? | Title: DRNet: A Decision-Making Method for Autonomous Lane Changingwith Deep Reinforcement Learning
Abstract: Machine learning techniques have outperformed numerous rule-based methods for
decision-making in autonomous vehicles. Despite recent efforts, lane changing
remains a major challenge, due to the complex driving ... | Robotics |
What field is the article from? | Title: LLM Augmented Hierarchical Agents
Abstract: Solving long-horizon, temporally-extended tasks using Reinforcement Learning
(RL) is challenging, compounded by the common practice of learning without
prior knowledge (or tabula rasa learning). Humans can generate and execute
plans with temporally-extended actions and... | Machine Learning |
What field is the article from? | Title: Privacy Issues in Large Language Models: A Survey
Abstract: This is the first survey of the active area of AI research that focuses on
privacy issues in Large Language Models (LLMs). Specifically, we focus on work
that red-teams models to highlight privacy risks, attempts to build privacy
into the training or in... | Artificial Intelligence |
What field is the article from? | Title: Mini Minds: Exploring Bebeshka and Zlata Baby Models
Abstract: In this paper, we describe the University of Lyon 2 submission to the
Strict-Small track of the BabyLM competition. The shared task is created with
an emphasis on small-scale language modelling from scratch on limited-size data
and human language acq... | Computational Linguistics |
What field is the article from? | Title: Large language models for aspect-based sentiment analysis
Abstract: Large language models (LLMs) offer unprecedented text completion
capabilities. As general models, they can fulfill a wide range of roles,
including those of more specialized models. We assess the performance of GPT-4
and GPT-3.5 in zero shot, fe... | Computational Linguistics |
What field is the article from? | Title: Large-Scale Application of Fault Injection into PyTorch Models -- an Extension to PyTorchFI for Validation Efficiency
Abstract: Transient or permanent faults in hardware can render the output of Neural
Networks (NN) incorrect without user-specific traces of the error, i.e. silent
data errors (SDE). On the other ... | Artificial Intelligence |
What field is the article from? | Title: User-Like Bots for Cognitive Automation: A Survey
Abstract: Software bots have attracted increasing interest and popularity in both
research and society. Their contributions span automation, digital twins, game
characters with conscious-like behavior, and social media. However, there is
still a lack of intellige... | Human-Computer Interaction |
What field is the article from? | Title: Generating Medical Prescriptions with Conditional Transformer
Abstract: Access to real-world medication prescriptions is essential for medical
research and healthcare quality improvement. However, access to real medication
prescriptions is often limited due to the sensitive nature of the information
expressed. A... | Computational Linguistics |
What field is the article from? | Title: Causal Structure Representation Learning of Confounders in Latent Space for Recommendation
Abstract: Inferring user preferences from the historical feedback of users is a
valuable problem in recommender systems. Conventional approaches often rely on
the assumption that user preferences in the feedback data are e... | Information Retrieval |
What field is the article from? | Title: An Improved Neural Network Model Based On CNN Using For Fruit Sugar Degree Detection
Abstract: Artificial Intelligence(AI) widely applies in Image Classification and
Recognition, Text Understanding and Natural Language Processing, which makes
great progress. In this paper, we introduced AI into the fruit quality... | Artificial Intelligence |
What field is the article from? | Title: Using linear initialisation to improve speed of convergence and fully-trained error in Autoencoders
Abstract: Good weight initialisation is an important step in successful training of
Artificial Neural Networks. Over time a number of improvements have been
proposed to this process. In this paper we introduce a n... | Machine Learning |
What field is the article from? | Title: Critical Analysis of 5G Networks Traffic Intrusion using PCA, t-SNE and UMAP Visualization and Classifying Attacks
Abstract: Networks, threat models, and malicious actors are advancing quickly. With the
increased deployment of the 5G networks, the security issues of the attached 5G
physical devices have also inc... | Cryptography and Security |
What field is the article from? | Title: Neural Network Models of Becoming a Cardinal Principle Knower
Abstract: As children enter elementary school, their understanding of the ordinal
structure of numbers transitions from a memorized count list of the first
50-100 numbers to knowing the successor function and understanding the
countably infinite. We i... | Machine Learning |
What field is the article from? | Title: E-Sparse: Boosting the Large Language Model Inference through Entropy-based N:M Sparsity
Abstract: Traditional pruning methods are known to be challenging to work in Large
Language Models (LLMs) for Generative AI because of their unaffordable training
process and large computational demands. For the first time, ... | Machine Learning |
What field is the article from? | Title: Are cascade dialogue state tracking models speaking out of turn in spoken dialogues?
Abstract: In Task-Oriented Dialogue (TOD) systems, correctly updating the system's
understanding of the user's needs is key to a smooth interaction. Traditionally
TOD systems are composed of several modules that interact with on... | Computational Linguistics |
What field is the article from? | Title: Vision-Language Foundation Models as Effective Robot Imitators
Abstract: Recent progress in vision language foundation models has shown their ability
to understand multimodal data and resolve complicated vision language tasks,
including robotics manipulation. We seek a straightforward way of making use of
existi... | Robotics |
What field is the article from? | Title: Brain-Driven Representation Learning Based on Diffusion Model
Abstract: Interpreting EEG signals linked to spoken language presents a complex
challenge, given the data's intricate temporal and spatial attributes, as well
as the various noise factors. Denoising diffusion probabilistic models (DDPMs),
which have r... | Computational Linguistics |
What field is the article from? | Title: Comparative Knowledge Distillation
Abstract: In the era of large scale pretrained models, Knowledge Distillation (KD)
serves an important role in transferring the wisdom of computationally heavy
teacher models to lightweight, efficient student models while preserving
performance. Traditional KD paradigms, howeve... | Machine Learning |
What field is the article from? | Title: A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis
Abstract: We present a novel usage of Transformers to make image classification
interpretable. Unlike mainstream classifiers that wait until the last
fully-connected layer to incorporate class information to make predictions, w... | Computer Vision |
What field is the article from? | Title: A Systematic Review of Deep Graph Neural Networks: Challenges, Classification, Architectures, Applications & Potential Utility in Bioinformatics
Abstract: In recent years, tasks of machine learning ranging from image processing &
audio/video analysis to natural language understanding have been transformed by
dee... | Machine Learning |
What field is the article from? | Title: SC-MIL: Sparsely Coded Multiple Instance Learning for Whole Slide Image Classification
Abstract: Multiple Instance Learning (MIL) has been widely used in weakly supervised
whole slide image (WSI) classification. Typical MIL methods include a feature
embedding part that embeds the instances into features via a pr... | Computer Vision |
What field is the article from? | Title: Hallucination-minimized Data-to-answer Framework for Financial Decision-makers
Abstract: Large Language Models (LLMs) have been applied to build several automation
and personalized question-answering prototypes so far. However, scaling such
prototypes to robust products with minimized hallucinations or fake resp... | Computational Linguistics |
What field is the article from? | Title: No Representation Rules Them All in Category Discovery
Abstract: In this paper we tackle the problem of Generalized Category Discovery (GCD).
Specifically, given a dataset with labelled and unlabelled images, the task is
to cluster all images in the unlabelled subset, whether or not they belong to
the labelled c... | Computer Vision |
What field is the article from? | Title: On the Noise Scheduling for Generating Plausible Designs with Diffusion Models
Abstract: Deep Generative Models (DGMs) are widely used to create innovative designs
across multiple industries, ranging from fashion to the automotive sector. In
addition to generating images of high visual quality, the task of struc... | Computer Vision |
What field is the article from? | Title: Continual Learning of Diffusion Models with Generative Distillation
Abstract: Diffusion models are powerful generative models that achieve state-of-the-art
performance in tasks such as image synthesis. However, training them demands
substantial amounts of data and computational resources. Continual learning
woul... | Machine Learning |
What field is the article from? | Title: IMPRESS: Evaluating the Resilience of Imperceptible Perturbations Against Unauthorized Data Usage in Diffusion-Based Generative AI
Abstract: Diffusion-based image generation models, such as Stable Diffusion or DALL-E
2, are able to learn from given images and generate high-quality samples
following the guidance ... | Computer Vision |
What field is the article from? | Title: Analyzing Vision Transformers for Image Classification in Class Embedding Space
Abstract: Despite the growing use of transformer models in computer vision, a
mechanistic understanding of these networks is still needed. This work
introduces a method to reverse-engineer Vision Transformers trained to solve
image c... | Computer Vision |
What field is the article from? | Title: Caring Trouble and Musical AI: Considerations towards a Feminist Musical AI
Abstract: The ethics of AI as both material and medium for interaction remains in murky
waters within the context of musical and artistic practice. The
interdisciplinarity of the field is revealing matters of concern and care,
which nece... | Human-Computer Interaction |
What field is the article from? | Title: DesignGPT: Multi-Agent Collaboration in Design
Abstract: Generative AI faces many challenges when entering the product design
workflow, such as interface usability and interaction patterns. Therefore,
based on design thinking and design process, we developed the DesignGPT
multi-agent collaboration framework, whi... | Artificial Intelligence |
What field is the article from? | Title: Not All Data Matters: An End-to-End Adaptive Dataset Pruning Framework for Enhancing Model Performance and Efficiency
Abstract: While deep neural networks have demonstrated remarkable performance across
various tasks, they typically require massive training data. Due to the
presence of redundancies and biases in... | Artificial Intelligence |
What field is the article from? | Title: Structural Information Guided Multimodal Pre-training for Vehicle-centric Perception
Abstract: Understanding vehicles in images is important for various applications such
as intelligent transportation and self-driving system. Existing vehicle-centric
works typically pre-train models on large-scale classification... | Computer Vision |
What field is the article from? | Title: Revisiting the Domain Shift and Sample Uncertainty in Multi-source Active Domain Transfer
Abstract: Active Domain Adaptation (ADA) aims to maximally boost model adaptation in a
new target domain by actively selecting a limited number of target data to
annotate.This setting neglects the more practical scenario wh... | Artificial Intelligence |
What field is the article from? | Title: QMGeo: Differentially Private Federated Learning via Stochastic Quantization with Mixed Truncated Geometric Distribution
Abstract: Federated learning (FL) is a framework which allows multiple users to jointly
train a global machine learning (ML) model by transmitting only model updates
under the coordination of ... | Machine Learning |
What field is the article from? | Title: Digital Twin Framework for Optimal and Autonomous Decision-Making in Cyber-Physical Systems: Enhancing Reliability and Adaptability in the Oil and Gas Industry
Abstract: The concept of creating a virtual copy of a complete Cyber-Physical System
opens up numerous possibilities, including real-time assessments of ... | Artificial Intelligence |
What field is the article from? | Title: AbsPyramid: Benchmarking the Abstraction Ability of Language Models with a Unified Entailment Graph
Abstract: Cognitive research indicates that abstraction ability is essential in human
intelligence, which remains under-explored in language models. In this paper,
we present AbsPyramid, a unified entailment graph... | Computational Linguistics |
What field is the article from? | Title: Gaussian Mixture Solvers for Diffusion Models
Abstract: Recently, diffusion models have achieved great success in generative tasks.
Sampling from diffusion models is equivalent to solving the reverse diffusion
stochastic differential equations (SDEs) or the corresponding probability flow
ordinary differential eq... | Machine Learning |
What field is the article from? | Title: Can Large Language Models Follow Concept Annotation Guidelines? A Case Study on Scientific and Financial Domains
Abstract: Although large language models (LLMs) exhibit remarkable capacity to leverage
in-context demonstrations, it is still unclear to what extent they can learn
new concepts or facts from ground-t... | Computational Linguistics |
What field is the article from? | Title: MechAgents: Large language model multi-agent collaborations can solve mechanics problems, generate new data, and integrate knowledge
Abstract: Solving mechanics problems using numerical methods requires comprehensive
intelligent capability of retrieving relevant knowledge and theory,
constructing and executing c... | Artificial Intelligence |
What field is the article from? | Title: Smart Traffic Management of Vehicles using Faster R-CNN based Deep Learning Method
Abstract: With constant growth of civilization and modernization of cities all across
the world since past few centuries smart traffic management of vehicles is one
of the most sorted after problem by research community. It is a c... | Computer Vision |
What field is the article from? | Title: ViP-Mixer: A Convolutional Mixer for Video Prediction
Abstract: Video prediction aims to predict future frames from a video's previous
content. Existing methods mainly process video data where the time dimension
mingles with the space and channel dimensions from three distinct angles: as a
sequence of individual... | Computer Vision |
What field is the article from? | Title: Innovative Horizons in Aerial Imagery: LSKNet Meets DiffusionDet for Advanced Object Detection
Abstract: In the realm of aerial image analysis, object detection plays a pivotal role,
with significant implications for areas such as remote sensing, urban planning,
and disaster management. This study addresses the ... | Computer Vision |
What field is the article from? | Title: Navigating Complex Search Tasks with AI Copilots
Abstract: As many of us in the information retrieval (IR) research community know and
appreciate, search is far from being a solved problem. Millions of people
struggle with tasks on search engines every day. Often, their struggles relate
to the intrinsic complexi... | Information Retrieval |
What field is the article from? | Title: Constrained Meta-Reinforcement Learning for Adaptable Safety Guarantee with Differentiable Convex Programming
Abstract: Despite remarkable achievements in artificial intelligence, the deployability
of learning-enabled systems in high-stakes real-world environments still faces
persistent challenges. For example, ... | Artificial Intelligence |
What field is the article from? | Title: Scene-Driven Multimodal Knowledge Graph Construction for Embodied AI
Abstract: Embodied AI is one of the most popular studies in artificial intelligence and
robotics, which can effectively improve the intelligence of real-world agents
(i.e. robots) serving human beings. Scene knowledge is important for an agent
... | Artificial Intelligence |
What field is the article from? | Title: Leveraging LLMs for Synthesizing Training Data Across Many Languages in Multilingual Dense Retrieval
Abstract: Dense retrieval models have predominantly been studied for English, where
models have shown great success, due to the availability of human-labeled
training pairs. However, there has been limited succes... | Information Retrieval |
What field is the article from? | Title: Temporal Knowledge Question Answering via Abstract Reasoning Induction
Abstract: In this paper, we tackle the significant challenge of temporal knowledge
reasoning in Large Language Models (LLMs), an area where such models frequently
encounter difficulties. These difficulties often result in the generation of
mi... | Computational Linguistics |
What field is the article from? | Title: Multimodal Clinical Benchmark for Emergency Care (MC-BEC): A Comprehensive Benchmark for Evaluating Foundation Models in Emergency Medicine
Abstract: We propose the Multimodal Clinical Benchmark for Emergency Care (MC-BEC), a
comprehensive benchmark for evaluating foundation models in Emergency Medicine
using a ... | Machine Learning |
What field is the article from? | Title: Cross-modal Contrastive Learning with Asymmetric Co-attention Network for Video Moment Retrieval
Abstract: Video moment retrieval is a challenging task requiring fine-grained
interactions between video and text modalities. Recent work in image-text
pretraining has demonstrated that most existing pretrained model... | Computer Vision |
What field is the article from? | Title: Training Multi-layer Neural Networks on Ising Machine
Abstract: As a dedicated quantum device, Ising machines could solve large-scale binary
optimization problems in milliseconds. There is emerging interest in utilizing
Ising machines to train feedforward neural networks due to the prosperity of
generative artif... | Machine Learning |
What field is the article from? | Title: A Survey on Vulnerability of Federated Learning: A Learning Algorithm Perspective
Abstract: This review paper takes a comprehensive look at malicious attacks against FL,
categorizing them from new perspectives on attack origins and targets, and
providing insights into their methodology and impact. In this survey... | Machine Learning |
What field is the article from? | Title: Developing Linguistic Patterns to Mitigate Inherent Human Bias in Offensive Language Detection
Abstract: With the proliferation of social media, there has been a sharp increase in
offensive content, particularly targeting vulnerable groups, exacerbating
social problems such as hatred, racism, and sexism. Detecti... | Computational Linguistics |
What field is the article from? | Title: Breaking the Entanglement of Homophily and Heterophily in Semi-supervised Node Classification
Abstract: Recently, graph neural networks (GNNs) have shown prominent performance in
semi-supervised node classification by leveraging knowledge from the graph
database. However, most existing GNNs follow the homophily ... | Machine Learning |
What field is the article from? | Title: Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications
Abstract: Machine learning algorithms minimizing average risk are susceptible to
distributional shifts. Distributionally Robust Optimization (DRO) addresses
this issue by optimizing the worst-case risk within an uncertainty set.
Howe... | Machine Learning |
What field is the article from? | Title: Contrastive Multi-view Subspace Clustering of Hyperspectral Images based on Graph Convolutional Networks
Abstract: High-dimensional and complex spectral structures make the clustering of
hyperspectral images (HSI) a challenging task. Subspace clustering is an
effective approach for addressing this problem. Howev... | Computer Vision |
What field is the article from? | Title: Virtual Fusion with Contrastive Learning for Single Sensor-based Activity Recognition
Abstract: Various types of sensors can be used for Human Activity Recognition (HAR),
and each of them has different strengths and weaknesses. Sometimes a single
sensor cannot fully observe the user's motions from its perspectiv... | Machine Learning |
What field is the article from? | Title: Adaptive Proximal Policy Optimization with Upper Confidence Bound
Abstract: Trust Region Policy Optimization (TRPO) attractively optimizes the policy
while constraining the update of the new policy within a trust region, ensuring
the stability and monotonic optimization. Building on the theoretical
guarantees of... | Machine Learning |
What field is the article from? | Title: Chatbots as social companions: How people perceive consciousness, human likeness, and social health benefits in machines
Abstract: As artificial intelligence (AI) becomes more widespread, one question that
arises is how human-AI interaction might impact human-human interaction.
Chatbots, for example, are increas... | Human-Computer Interaction |
What field is the article from? | Title: Efficient Data Fusion using the Tsetlin Machine
Abstract: We propose a novel way of assessing and fusing noisy dynamic data using a
Tsetlin Machine. Our approach consists in monitoring how explanations in form
of logical clauses that a TM learns changes with possible noise in dynamic
data. This way TM can recogn... | Artificial Intelligence |
What field is the article from? | Title: Italian Crossword Generator: Enhancing Education through Interactive Word Puzzles
Abstract: Educational crosswords offer numerous benefits for students, including
increased engagement, improved understanding, critical thinking, and memory
retention. Creating high-quality educational crosswords can be challenging... | Computational Linguistics |
What field is the article from? | Title: Improving Adaptability and Generalizability of Efficient Transfer Learning for Vision-Language Models
Abstract: Vision-Language Models (VLMs) like CLIP have demonstrated remarkable
applicability across a variety of downstream tasks, including zero-shot image
classification. Recently, the use of prompts or adapte... | Computer Vision |
What field is the article from? | Title: GOPlan: Goal-conditioned Offline Reinforcement Learning by Planning with Learned Models
Abstract: Offline goal-conditioned RL (GCRL) offers a feasible paradigm to learn
general-purpose policies from diverse and multi-task offline datasets. Despite
notable recent progress, the predominant offline GCRL methods hav... | Machine Learning |
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