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What field is the article from? | Title: Unleashing the potential of GNNs via Bi-directional Knowledge Transfer
Abstract: Based on the message-passing paradigm, there has been an amount of research
proposing diverse and impressive feature propagation mechanisms to improve the
performance of GNNs. However, less focus has been put on feature
transformati... | Machine Learning |
What field is the article from? | Title: @ve: A Chatbot for Latin
Abstract: Dead, extinct, and endangered languages have been preserved primarily through
audio conservation and the collection and digitization of scripts and have been
promoted through targeted language acquisition efforts. Another possibility
would be to build conversational agents that... | Computational Linguistics |
What field is the article from? | Title: Fake Alignment: Are LLMs Really Aligned Well?
Abstract: The growing awareness of safety concerns in large language models (LLMs) has
sparked considerable interest in the evaluation of safety within current
research endeavors. This study investigates an interesting issue pertaining to
the evaluation of LLMs, name... | Computational Linguistics |
What field is the article from? | Title: AutoML for Large Capacity Modeling of Meta's Ranking Systems
Abstract: Web-scale ranking systems at Meta serving billions of users is complex.
Improving ranking models is essential but engineering heavy. Automated Machine
Learning (AutoML) can release engineers from labor intensive work of tuning
ranking models;... | Information Retrieval |
What field is the article from? | Title: tagE: Enabling an Embodied Agent to Understand Human Instructions
Abstract: Natural language serves as the primary mode of communication when an
intelligent agent with a physical presence engages with human beings. While a
plethora of research focuses on natural language understanding (NLU),
encompassing endeavo... | Robotics |
What field is the article from? | Title: RSG: Fast Learning Adaptive Skills for Quadruped Robots by Skill Graph
Abstract: Developing robotic intelligent systems that can adapt quickly to unseen wild
situations is one of the critical challenges in pursuing autonomous robotics.
Although some impressive progress has been made in walking stability and skil... | Robotics |
What field is the article from? | Title: Dream to Adapt: Meta Reinforcement Learning by Latent Context Imagination and MDP Imagination
Abstract: Meta reinforcement learning (Meta RL) has been amply explored to quickly
learn an unseen task by transferring previously learned knowledge from similar
tasks. However, most state-of-the-art algorithms require ... | Machine Learning |
What field is the article from? | Title: Pre-training with Random Orthogonal Projection Image Modeling
Abstract: Masked Image Modeling (MIM) is a powerful self-supervised strategy for visual
pre-training without the use of labels. MIM applies random crops to input
images, processes them with an encoder, and then recovers the masked inputs
with a decode... | Computer Vision |
What field is the article from? | Title: Understanding and Improving In-Context Learning on Vision-language Models
Abstract: Recently, in-context learning (ICL) on large language models (LLMs) has
received great attention, and this technique can also be applied to
vision-language models (VLMs) built upon LLMs. These VLMs can respond to
queries by condi... | Computer Vision |
What field is the article from? | Title: Towards Calibrated Robust Fine-Tuning of Vision-Language Models
Abstract: While fine-tuning unlocks the potential of a pre-trained model for a specific
task, it compromises the model's ability to generalize to out-of-distribution
(OOD) datasets. To mitigate this, robust fine-tuning aims to ensure performance
on ... | Computer Vision |
What field is the article from? | Title: Anticipating User Needs: Insights from Design Fiction on Conversational Agents for Computational Thinking
Abstract: Computational thinking, and by extension, computer programming, is
notoriously challenging to learn. Conversational agents and generative
artificial intelligence (genAI) have the potential to facil... | Human-Computer Interaction |
What field is the article from? | Title: Post-Training Quantization for Re-parameterization via Coarse & Fine Weight Splitting
Abstract: Although neural networks have made remarkable advancements in various
applications, they require substantial computational and memory resources.
Network quantization is a powerful technique to compress neural networks... | Computer Vision |
What field is the article from? | Title: Global Transformer Architecture for Indoor Room Temperature Forecasting
Abstract: A thorough regulation of building energy systems translates in relevant
energy savings and in a better comfort for the occupants. Algorithms to predict
the thermal state of a building on a certain time horizon with a good
confidenc... | Machine Learning |
What field is the article from? | Title: Vital Sign Forecasting for Sepsis Patients in ICUs
Abstract: Sepsis and septic shock are a critical medical condition affecting millions
globally, with a substantial mortality rate. This paper uses state-of-the-art
deep learning (DL) architectures to introduce a multi-step forecasting system
to predict vital sig... | Machine Learning |
What field is the article from? | Title: Dataset Distillation in Large Data Era
Abstract: Dataset distillation aims to generate a smaller but representative subset
from a large dataset, which allows a model to be trained efficiently, meanwhile
evaluating on the original testing data distribution to achieve decent
performance. Many prior works have aime... | Computer Vision |
What field is the article from? | Title: Low-Rank MDPs with Continuous Action Spaces
Abstract: Low-Rank Markov Decision Processes (MDPs) have recently emerged as a
promising framework within the domain of reinforcement learning (RL), as they
allow for provably approximately correct (PAC) learning guarantees while also
incorporating ML algorithms for re... | Machine Learning |
What field is the article from? | Title: CreoleVal: Multilingual Multitask Benchmarks for Creoles
Abstract: Creoles represent an under-explored and marginalized group of languages, with
few available resources for NLP research. While the genealogical ties between
Creoles and other highly-resourced languages imply a significant potential for
transfer le... | Computational Linguistics |
What field is the article from? | Title: Beyond Expected Return: Accounting for Policy Reproducibility when Evaluating Reinforcement Learning Algorithms
Abstract: Many applications in Reinforcement Learning (RL) usually have noise or
stochasticity present in the environment. Beyond their impact on learning,
these uncertainties lead the exact same polic... | Machine Learning |
What field is the article from? | Title: Studying Artist Sentiments around AI-generated Artwork
Abstract: Art created using generated Artificial Intelligence has taken the world by
storm and generated excitement for many digital creators and technologists.
However, the reception and reaction from artists have been mixed. Concerns
about plagiarizing the... | Human-Computer Interaction |
What field is the article from? | Title: CLIP-Motion: Learning Reward Functions for Robotic Actions Using Consecutive Observations
Abstract: This paper presents a novel method for learning reward functions for robotic
motions by harnessing the power of a CLIP-based model. Traditional reward
function design often hinges on manual feature engineering, wh... | Robotics |
What field is the article from? | Title: Spatial Knowledge-Infused Hierarchical Learning: An Application in Flood Mapping on Earth Imagery
Abstract: Deep learning for Earth imagery plays an increasingly important role in
geoscience applications such as agriculture, ecology, and natural disaster
management. Still, progress is often hindered by the limit... | Artificial Intelligence |
What field is the article from? | Title: MemoryCompanion: A Smart Healthcare Solution to Empower Efficient Alzheimer's Care Via Unleashing Generative AI
Abstract: With the rise of Large Language Models (LLMs), notably characterized by GPT
frameworks, there emerges a catalyst for novel healthcare applications. Earlier
iterations of chatbot caregivers, t... | Computational Linguistics |
What field is the article from? | Title: Efficient Data Learning for Open Information Extraction with Pre-trained Language Models
Abstract: Open Information Extraction (OpenIE) is a fundamental yet challenging task in
Natural Language Processing, which involves extracting all triples (subject,
predicate, object) from a given sentence. While labeling-ba... | Computational Linguistics |
What field is the article from? | Title: Efficient Causal Discovery for Robotics Applications
Abstract: Using robots for automating tasks in environments shared with humans, such as
warehouses, shopping centres, or hospitals, requires these robots to comprehend
the fundamental physical interactions among nearby agents and objects.
Specifically, creatin... | Robotics |
What field is the article from? | Title: A Comprehensive Study of Vision Transformers in Image Classification Tasks
Abstract: Image Classification is a fundamental task in the field of computer vision
that frequently serves as a benchmark for gauging advancements in Computer
Vision. Over the past few years, significant progress has been made in image
c... | Computer Vision |
What field is the article from? | Title: Interaction is all You Need? A Study of Robots Ability to Understand and Execute
Abstract: This paper aims to address a critical challenge in robotics, which is
enabling them to operate seamlessly in human environments through natural
language interactions. Our primary focus is to equip robots with the ability t... | Robotics |
What field is the article from? | Title: Characterizing Large Language Models as Rationalizers of Knowledge-intensive Tasks
Abstract: Large language models (LLMs) are proficient at generating fluent text with
minimal task-specific supervision. Yet, their ability to provide well-grounded
rationalizations for knowledge-intensive tasks remains under-explo... | Computational Linguistics |
What field is the article from? | Title: Noise in Relation Classification Dataset TACRED: Characterization and Reduction
Abstract: The overarching objective of this paper is two-fold. First, to explore
model-based approaches to characterize the primary cause of the noise. in the
RE dataset TACRED Second, to identify the potentially noisy instances. Tow... | Computational Linguistics |
What field is the article from? | Title: Complex Organ Mask Guided Radiology Report Generation
Abstract: The goal of automatic report generation is to generate a clinically accurate
and coherent phrase from a single given X-ray image, which could alleviate the
workload of traditional radiology reporting. However, in a real-world scenario,
radiologists ... | Computer Vision |
What field is the article from? | Title: Fuse to Forget: Bias Reduction and Selective Memorization through Model Fusion
Abstract: Model fusion research aims to aggregate the knowledge of multiple models to
enhance performance by combining their weights. In this work, we study the
inverse, investigating whether and how can model fusion interfere and red... | Computational Linguistics |
What field is the article from? | Title: Enhancing Vehicle Entrance and Parking Management: Deep Learning Solutions for Efficiency and Security
Abstract: The auto-management of vehicle entrance and parking in any organization is a
complex challenge encompassing record-keeping, efficiency, and security
concerns. Manual methods for tracking vehicles and ... | Computer Vision |
What field is the article from? | Title: Modifying RL Policies with Imagined Actions: How Predictable Policies Can Enable Users to Perform Novel Tasks
Abstract: It is crucial that users are empowered to use the functionalities of a robot
to creatively solve problems on the fly. A user who has access to a
Reinforcement Learning (RL) based robot may want... | Robotics |
What field is the article from? | Title: Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions
Abstract: As systems based on opaque Artificial Intelligence (AI) continue to flourish
in diverse real-world applications, understanding these black box models has
become paramount. In response... | Artificial Intelligence |
What field is the article from? | Title: A Multifidelity Sim-to-Real Pipeline for Verifiable and Compositional Reinforcement Learning
Abstract: We propose and demonstrate a compositional framework for training and
verifying reinforcement learning (RL) systems within a multifidelity
sim-to-real pipeline, in order to deploy reliable and adaptable RL poli... | Robotics |
What field is the article from? | Title: RelVAE: Generative Pretraining for few-shot Visual Relationship Detection
Abstract: Visual relations are complex, multimodal concepts that play an important role
in the way humans perceive the world. As a result of their complexity,
high-quality, diverse and large scale datasets for visual relations are still
ab... | Computer Vision |
What field is the article from? | Title: Pearl: A Production-ready Reinforcement Learning Agent
Abstract: Reinforcement Learning (RL) offers a versatile framework for achieving
long-term goals. Its generality allows us to formalize a wide range of problems
that real-world intelligent systems encounter, such as dealing with delayed
rewards, handling par... | Machine Learning |
What field is the article from? | Title: Weakly-Supervised Audio-Visual Segmentation
Abstract: Audio-visual segmentation is a challenging task that aims to predict
pixel-level masks for sound sources in a video. Previous work applied a
comprehensive manually designed architecture with countless pixel-wise accurate
masks as supervision. However, these p... | Computer Vision |
What field is the article from? | Title: Alignment and Outer Shell Isotropy for Hyperbolic Graph Contrastive Learning
Abstract: Learning good self-supervised graph representations that are beneficial to
downstream tasks is challenging. Among a variety of methods, contrastive
learning enjoys competitive performance. The embeddings of contrastive learnin... | Machine Learning |
What field is the article from? | Title: A Stability Principle for Learning under Non-Stationarity
Abstract: We develop a versatile framework for statistical learning in non-stationary
environments. In each time period, our approach applies a stability principle
to select a look-back window that maximizes the utilization of historical data
while keepin... | Machine Learning |
What field is the article from? | Title: Analysis of the User Perception of Chatbots in Education Using A Partial Least Squares Structural Equation Modeling Approach
Abstract: The integration of Artificial Intelligence (AI) into education is a recent
development, with chatbots emerging as a noteworthy addition to this
transformative landscape. As onlin... | Human-Computer Interaction |
What field is the article from? | Title: Grounding Everything: Emerging Localization Properties in Vision-Language Transformers
Abstract: Vision-language foundation models have shown remarkable performance in
various zero-shot settings such as image retrieval, classification, or
captioning. But so far, those models seem to fall behind when it comes to
... | Computer Vision |
What field is the article from? | Title: Leveraging generative artificial intelligence to simulate student learning behavior
Abstract: Student simulation presents a transformative approach to enhance learning
outcomes, advance educational research, and ultimately shape the future of
effective pedagogy. We explore the feasibility of using large language... | Artificial Intelligence |
What field is the article from? | Title: Foundational Moral Values for AI Alignment
Abstract: Solving the AI alignment problem requires having clear, defensible values
towards which AI systems can align. Currently, targets for alignment remain
underspecified and do not seem to be built from a philosophically robust
structure. We begin the discussion of... | Computers and Society |
What field is the article from? | Title: General Policies, Subgoal Structure, and Planning Width
Abstract: It has been observed that many classical planning domains with atomic goals
can be solved by means of a simple polynomial exploration procedure, called IW,
that runs in time exponential in the problem width, which in these cases is
bounded and sma... | Artificial Intelligence |
What field is the article from? | Title: EQ-Bench: An Emotional Intelligence Benchmark for Large Language Models
Abstract: We introduce EQ-Bench, a novel benchmark designed to evaluate aspects of
emotional intelligence in Large Language Models (LLMs). We assess the ability
of LLMs to understand complex emotions and social interactions by asking them
to... | Computational Linguistics |
What field is the article from? | Title: LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents
Abstract: LLaVA-Plus is a general-purpose multimodal assistant that expands the
capabilities of large multimodal models. It maintains a skill repository of
pre-trained vision and vision-language models and can activate relevant tools
based on users... | Computer Vision |
What field is the article from? | Title: An advantage based policy transfer algorithm for reinforcement learning with metrics of transferability
Abstract: Reinforcement learning (RL) can enable sequential decision-making in complex
and high-dimensional environments if the acquisition of a new state-action pair
is efficient, i.e., when interaction with ... | Machine Learning |
What field is the article from? | Title: Self Model for Embodied Intelligence: Modeling Full-Body Human Musculoskeletal System and Locomotion Control with Hierarchical Low-Dimensional Representation
Abstract: Modeling and control of the human musculoskeletal system is important for
understanding human motion, developing embodied intelligence, and optim... | Artificial Intelligence |
What field is the article from? | Title: An Extensive Study on Adversarial Attack against Pre-trained Models of Code
Abstract: Transformer-based pre-trained models of code (PTMC) have been widely utilized
and have achieved state-of-the-art performance in many mission-critical
applications. However, they can be vulnerable to adversarial attacks through
... | Cryptography and Security |
What field is the article from? | Title: Personalized Path Recourse
Abstract: This paper introduces Personalized Path Recourse, a novel method that
generates recourse paths for an agent. The objective is to achieve desired
goals (e.g., better outcomes compared to the agent's original paths of action),
while ensuring a high similarity to the agent's ori... | Machine Learning |
What field is the article from? | Title: Exploring Lip Segmentation Techniques in Computer Vision: A Comparative Analysis
Abstract: Lip segmentation is crucial in computer vision, especially for lip reading.
Despite extensive face segmentation research, lip segmentation has received
limited attention. The aim of this study is to compare state-of-the-ar... | Computer Vision |
What field is the article from? | Title: TST$^\mathrm{R}$: Target Similarity Tuning Meets the Real World
Abstract: Target similarity tuning (TST) is a method of selecting relevant examples in
natural language (NL) to code generation through large language models (LLMs)
to improve performance. Its goal is to adapt a sentence embedding model to have
the ... | Artificial Intelligence |
What field is the article from? | Title: Touring sampling with pushforward maps
Abstract: The number of sampling methods could be daunting for a practitioner looking
to cast powerful machine learning methods to their specific problem. This paper
takes a theoretical stance to review and organize many sampling approaches in
the ``generative modeling'' se... | Machine Learning |
What field is the article from? | Title: The Quest for Content: A Survey of Search-Based Procedural Content Generation for Video Games
Abstract: Video games demand is constantly increasing, which requires the costly
production of large amounts of content. Towards this challenge, researchers
have developed Search-Based Procedural Content Generation (SBP... | Software Engineering |
What field is the article from? | Title: Sim-to-Real Causal Transfer: A Metric Learning Approach to Causally-Aware Interaction Representations
Abstract: Modeling spatial-temporal interactions among neighboring agents is at the
heart of multi-agent problems such as motion forecasting and crowd navigation.
Despite notable progress, it remains unclear to ... | Machine Learning |
What field is the article from? | Title: Controlled Decoding from Language Models
Abstract: We propose controlled decoding (CD), a novel off-policy reinforcement
learning method to control the autoregressive generation from language models
towards high reward outcomes. CD solves an off-policy reinforcement learning
problem through a value function for ... | Machine Learning |
What field is the article from? | Title: RoboSense At Edge: Detecting Slip, Crumple and Shape of the Object in Robotic Hand for Teleoprations
Abstract: Slip and crumple detection is essential for performing robust manipulation
tasks with a robotic hand (RH) like remote surgery. It has been one of the
challenging problems in the robotics manipulation co... | Robotics |
What field is the article from? | Title: GreenLightningAI: An Efficient AI System with Decoupled Structural and Quantitative Knowledge
Abstract: The number and complexity of artificial intelligence (AI) applications is
growing relentlessly. As a result, even with the many algorithmic and
mathematical advances experienced over past decades as well as th... | Machine Learning |
What field is the article from? | Title: Rapid Motor Adaptation for Robotic Manipulator Arms
Abstract: Developing generalizable manipulation skills is a core challenge in embodied
AI. This includes generalization across diverse task configurations,
encompassing variations in object shape, density, friction coefficient, and
external disturbances such as... | Robotics |
What field is the article from? | Title: OMNIINPUT: A Model-centric Evaluation Framework through Output Distribution
Abstract: We propose a novel model-centric evaluation framework, OmniInput, to evaluate
the quality of an AI/ML model's predictions on all possible inputs (including
human-unrecognizable ones), which is crucial for AI safety and reliabil... | Machine Learning |
What field is the article from? | Title: SynFundus: A synthetic fundus images dataset with millions of samples and multi-disease annotations
Abstract: In the field of medical imaging, there are seldom large-scale public datasets
with high-quality annotations due to data privacy and annotation cost. To
address this issue, we release SynFundus-1M, a high... | Computer Vision |
What field is the article from? | Title: UTBoost: A Tree-boosting based System for Uplift Modeling
Abstract: Uplift modeling refers to the set of machine learning techniques that a
manager may use to estimate customer uplift, that is, the net effect of an
action on some customer outcome. By identifying the subset of customers for
whom a treatment will ... | Machine Learning |
What field is the article from? | Title: Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding
Abstract: Large Vision-Language Models (LVLMs) have advanced considerably, intertwining
visual recognition and language understanding to generate content that is not
only coherent but also contextually attuned. D... | Computer Vision |
What field is the article from? | Title: Generative AI for Hate Speech Detection: Evaluation and Findings
Abstract: Automatic hate speech detection using deep neural models is hampered by the
scarcity of labeled datasets, leading to poor generalization. To mitigate this
problem, generative AI has been utilized to generate large amounts of synthetic
hat... | Computational Linguistics |
What field is the article from? | Title: Evaluating Large Language Models in Ophthalmology
Abstract: Purpose: The performance of three different large language models (LLMS)
(GPT-3.5, GPT-4, and PaLM2) in answering ophthalmology professional questions
was evaluated and compared with that of three different professional
populations (medical undergraduat... | Computational Linguistics |
What field is the article from? | Title: Education distillation:getting student models to learn in shcools
Abstract: Knowledge distillation is one of the methods for model compression, and
existing knowledge distillation techniques focus on how to improve the
distillation algorithm so as to enhance the distillation efficiency. This paper
introduces dyn... | Artificial Intelligence |
What field is the article from? | Title: "Close...but not as good as an educator." -- Using ChatGPT to provide formative feedback in large-class collaborative learning
Abstract: Delivering personalised, formative feedback to multiple problem-based
learning groups in a short time period can be almost impossible. We employed
ChatGPT to provide personalis... | Human-Computer Interaction |
What field is the article from? | Title: On Task-personalized Multimodal Few-shot Learning for Visually-rich Document Entity Retrieval
Abstract: Visually-rich document entity retrieval (VDER), which extracts key
information (e.g. date, address) from document images like invoices and
receipts, has become an important topic in industrial NLP applications... | Artificial Intelligence |
What field is the article from? | Title: CGS-Mask: Making Time Series Predictions Intuitive for Al
Abstract: Artificial intelligence (AI) has immense potential in time series prediction,
but most explainable tools have limited capabilities in providing a systematic
understanding of important features over time. These tools typically rely on
evaluating ... | Artificial Intelligence |
What field is the article from? | Title: Clinical Notes Reveal Physician Fatigue
Abstract: Physicians write notes about patients. In doing so, they reveal much about
themselves. Using data from 129,228 emergency room visits, we train a model to
identify notes written by fatigued physicians -- those who worked 5 or more of
the prior 7 days. In a hold-ou... | Computational Linguistics |
What field is the article from? | Title: Multi-Set Inoculation: Assessing Model Robustness Across Multiple Challenge Sets
Abstract: Language models, given their black-box nature, often exhibit sensitivity to
input perturbations, leading to trust issues due to hallucinations. To bolster
trust, it's essential to understand these models' failure modes and... | Computational Linguistics |
What field is the article from? | Title: High-fidelity Person-centric Subject-to-Image Synthesis
Abstract: Current subject-driven image generation methods encounter significant
challenges in person-centric image generation. The reason is that they learn
the semantic scene and person generation by fine-tuning a common pre-trained
diffusion, which involv... | Computer Vision |
What field is the article from? | Title: Relation Extraction from News Articles (RENA): A Tool for Epidemic Surveillance
Abstract: Relation Extraction from News Articles (RENA) is a browser-based tool
designed to extract key entities and their semantic relationships in English
language news articles related to infectious diseases. Constructed using the... | Computational Linguistics |
What field is the article from? | Title: Language Guided Visual Question Answering: Elevate Your Multimodal Language Model Using Knowledge-Enriched Prompts
Abstract: Visual question answering (VQA) is the task of answering questions about an
image. The task assumes an understanding of both the image and the question to
provide a natural language answer... | Computer Vision |
What field is the article from? | Title: Holodeck: Language Guided Generation of 3D Embodied AI Environments
Abstract: 3D simulated environments play a critical role in Embodied AI, but their
creation requires expertise and extensive manual effort, restricting their
diversity and scope. To mitigate this limitation, we present Holodeck, a system
that ge... | Computer Vision |
What field is the article from? | Title: Large Language Models with Retrieval-Augmented Generation for Zero-Shot Disease Phenotyping
Abstract: Identifying disease phenotypes from electronic health records (EHRs) is
critical for numerous secondary uses. Manually encoding physician knowledge
into rules is particularly challenging for rare diseases due to... | Artificial Intelligence |
What field is the article from? | Title: VisionTraj: A Noise-Robust Trajectory Recovery Framework based on Large-scale Camera Network
Abstract: Trajectory recovery based on the snapshots from the city-wide multi-camera
network facilitates urban mobility sensing and driveway optimization. The
state-of-the-art solutions devoted to such a vision-based sch... | Computer Vision |
What field is the article from? | Title: Applying Large Language Models for Causal Structure Learning in Non Small Cell Lung Cancer
Abstract: Causal discovery is becoming a key part in medical AI research. These methods
can enhance healthcare by identifying causal links between biomarkers,
demographics, treatments and outcomes. They can aid medical pro... | Artificial Intelligence |
What field is the article from? | Title: A Graph Neural Network-Based QUBO-Formulated Hamiltonian-Inspired Loss Function for Combinatorial Optimization using Reinforcement Learning
Abstract: Quadratic Unconstrained Binary Optimization (QUBO) is a generic technique to
model various NP-hard Combinatorial Optimization problems (CO) in the form of
binary v... | Machine Learning |
What field is the article from? | Title: A Spatial-Temporal Transformer based Framework For Human Pose Assessment And Correction in Education Scenarios
Abstract: Human pose assessment and correction play a crucial role in applications
across various fields, including computer vision, robotics, sports analysis,
healthcare, and entertainment. In this pap... | Computer Vision |
What field is the article from? | Title: Prompt-Engineering and Transformer-based Question Generation and Evaluation
Abstract: Question generation has numerous applications in the educational context.
Question generation can prove helpful for students when reviewing content and
testing themselves. Furthermore, a question generation model can aid teache... | Computational Linguistics |
What field is the article from? | Title: Mixed Pseudo Labels for Semi-Supervised Object Detection
Abstract: While the pseudo-label method has demonstrated considerable success in
semi-supervised object detection tasks, this paper uncovers notable limitations
within this approach. Specifically, the pseudo-label method tends to amplify
the inherent stren... | Computer Vision |
What field is the article from? | Title: Contactless Fingerprint Biometric Anti-Spoofing: An Unsupervised Deep Learning Approach
Abstract: Contactless fingerprint recognition offers a higher level of user comfort and
addresses hygiene concerns more effectively. However, it is also more
vulnerable to presentation attacks such as photo paper, paper-print... | Computer Vision |
What field is the article from? | Title: Optimal Wildfire Escape Route Planning for Drones under Dynamic Fire and Smoke
Abstract: In recent years, the increasing prevalence and intensity of wildfires have
posed significant challenges to emergency response teams. The utilization of
unmanned aerial vehicles (UAVs), commonly known as drones, has shown pro... | Robotics |
What field is the article from? | Title: Image Restoration Through Generalized Ornstein-Uhlenbeck Bridge
Abstract: Diffusion models possess powerful generative capabilities enabling the
mapping of noise to data using reverse stochastic differential equations.
However, in image restoration tasks, the focus is on the mapping relationship
from low-quality... | Computer Vision |
What field is the article from? | Title: Push it to the Demonstrated Limit: Multimodal Visuotactile Imitation Learning with Force Matching
Abstract: Optical tactile sensors have emerged as an effective means to acquire dense
contact information during robotic manipulation. A recently-introduced
`see-through-your-skin' (STS) variant of this type of sens... | Robotics |
What field is the article from? | Title: Relax: Composable Abstractions for End-to-End Dynamic Machine Learning
Abstract: Dynamic shape computations have become critical in modern machine learning
workloads, especially in emerging large language models. The success of these
models has driven demand for deploying them to a diverse set of backend
environ... | Machine Learning |
What field is the article from? | Title: Finnish 5th and 6th graders' misconceptions about Artificial Intelligence
Abstract: Research on children's initial conceptions of AI is in an emerging state,
which, from a constructivist viewpoint, challenges the development of
pedagogically sound AI-literacy curricula, methods, and materials. To
contribute to r... | Computers and Society |
What field is the article from? | Title: Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Models
Abstract: Retrieval-augmented language models (RALMs) represent a substantial
advancement in the capabilities of large language models, notably in reducing
factual hallucination by leveraging external knowledge sources. However, the
relia... | Computational Linguistics |
What field is the article from? | Title: Shortcut Bias Mitigation via Ensemble Diversity Using Diffusion Probabilistic Models
Abstract: Spurious correlations in the data, where multiple cues are predictive of the
target labels, often lead to a phenomenon known as simplicity bias, where a
model relies on erroneous, easy-to-learn cues while ignoring reli... | Machine Learning |
What field is the article from? | Title: Mission-driven Exploration for Accelerated Deep Reinforcement Learning with Temporal Logic Task Specifications
Abstract: This paper addresses the problem of designing optimal control policies for
mobile robots with mission and safety requirements specified using Linear
Temporal Logic (LTL). We consider robots wi... | Robotics |
What field is the article from? | Title: Uncertainty Quantification of Deep Learning for Spatiotemporal Data: Challenges and Opportunities
Abstract: With the advancement of GPS, remote sensing, and computational simulations,
large amounts of geospatial and spatiotemporal data are being collected at an
increasing speed. Such emerging spatiotemporal big ... | Machine Learning |
What field is the article from? | Title: Exploring Semi-supervised Hierarchical Stacked Encoder for Legal Judgement Prediction
Abstract: Predicting the judgment of a legal case from its unannotated case facts is a
challenging task. The lengthy and non-uniform document structure poses an even
greater challenge in extracting information for decision pred... | Computational Linguistics |
What field is the article from? | Title: CompeteAI: Understanding the Competition Behaviors in Large Language Model-based Agents
Abstract: Large language models (LLMs) have been widely used as agents to complete
different tasks, such as personal assistance or event planning. While most work
has focused on cooperation and collaboration between agents, l... | Artificial Intelligence |
What field is the article from? | Title: HEALNet -- Hybrid Multi-Modal Fusion for Heterogeneous Biomedical Data
Abstract: Technological advances in medical data collection such as high-resolution
histopathology and high-throughput genomic sequencing have contributed to the
rising requirement for multi-modal biomedical modelling, specifically for
image,... | Machine Learning |
What field is the article from? | Title: Train 'n Trade: Foundations of Parameter Markets
Abstract: Organizations typically train large models individually. This is costly and
time-consuming, particularly for large-scale foundation models. Such vertical
production is known to be suboptimal. Inspired by this economic insight, we ask
whether it is possib... | Machine Learning |
What field is the article from? | Title: On Surgical Fine-tuning for Language Encoders
Abstract: Fine-tuning all the layers of a pre-trained neural language encoder (either
using all the parameters or using parameter-efficient methods) is often the
de-facto way of adapting it to a new task. We show evidence that for different
downstream language tasks,... | Computational Linguistics |
What field is the article from? | Title: The New Frontier of Cybersecurity: Emerging Threats and Innovations
Abstract: In today's digitally interconnected world, cybersecurity threats have reached
unprecedented levels, presenting a pressing concern for individuals,
organizations, and governments. This study employs a qualitative research
approach to co... | Cryptography and Security |
What field is the article from? | Title: Distributed Global Structure-from-Motion with a Deep Front-End
Abstract: While initial approaches to Structure-from-Motion (SfM) revolved around both
global and incremental methods, most recent applications rely on incremental
systems to estimate camera poses due to their superior robustness. Though there
has be... | Computer Vision |
What field is the article from? | Title: ChatGPT and Beyond: The Generative AI Revolution in Education
Abstract: The wide adoption and usage of generative artificial intelligence (AI)
models, particularly ChatGPT, has sparked a surge in research exploring their
potential applications in the educational landscape. This survey examines
academic literatur... | Computers and Society |
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