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What field is the article from? | Title: Uncertainty Wrapper in the medical domain: Establishing transparent uncertainty quantification for opaque machine learning models in practice
Abstract: When systems use data-based models that are based on machine learning (ML),
errors in their results cannot be ruled out. This is particularly critical if
it rema... | Machine Learning |
What field is the article from? | Title: 1D-Convolutional transformer for Parkinson disease diagnosis from gait
Abstract: This paper presents an efficient deep neural network model for diagnosing
Parkinson's disease from gait. More specifically, we introduce a hybrid
ConvNet-Transformer architecture to accurately diagnose the disease by
detecting the s... | Computer Vision |
What field is the article from? | Title: Outlier Dimensions Encode Task-Specific Knowledge
Abstract: Representations from large language models (LLMs) are known to be dominated
by a small subset of dimensions with exceedingly high variance. Previous works
have argued that although ablating these outlier dimensions in LLM
representations hurts downstrea... | Computational Linguistics |
What field is the article from? | Title: United We Stand, Divided We Fall: UnityGraph for Unsupervised Procedure Learning from Videos
Abstract: Given multiple videos of the same task, procedure learning addresses
identifying the key-steps and determining their order to perform the task. For
this purpose, existing approaches use the signal generated fro... | Computer Vision |
What field is the article from? | Title: How Well Do Feature-Additive Explainers Explain Feature-Additive Predictors?
Abstract: Surging interest in deep learning from high-stakes domains has precipitated
concern over the inscrutable nature of black box neural networks. Explainable
AI (XAI) research has led to an abundance of explanation algorithms for ... | Machine Learning |
What field is the article from? | Title: Context-aware explainable recommendations over knowledge graphs
Abstract: Knowledge graphs contain rich semantic relationships related to items and
incorporating such semantic relationships into recommender systems helps to
explore the latent connections of items, thus improving the accuracy of
prediction and en... | Information Retrieval |
What field is the article from? | Title: Soil Organic Carbon Estimation from Climate-related Features with Graph Neural Network
Abstract: Soil organic carbon (SOC) plays a pivotal role in the global carbon cycle,
impacting climate dynamics and necessitating accurate estimation for
sustainable land and agricultural management. While traditional methods ... | Machine Learning |
What field is the article from? | Title: Training Dynamics of Contextual N-Grams in Language Models
Abstract: Prior work has shown the existence of contextual neurons in language models,
including a neuron that activates on German text. We show that this neuron
exists within a broader contextual n-gram circuit: we find late layer neurons
which recogniz... | Machine Learning |
What field is the article from? | Title: Ontology Learning Using Formal Concept Analysis and WordNet
Abstract: Manual ontology construction takes time, resources, and domain specialists.
Supporting a component of this process for automation or semi-automation would
be good. This project and dissertation provide a Formal Concept Analysis and
WordNet fra... | Computational Linguistics |
What field is the article from? | Title: Course Correcting Koopman Representations
Abstract: Koopman representations aim to learn features of nonlinear dynamical systems
(NLDS) which lead to linear dynamics in the latent space. Theoretically, such
features can be used to simplify many problems in modeling and control of NLDS.
In this work we study auto... | Machine Learning |
What field is the article from? | Title: A Survey of Adversarial CAPTCHAs on its History, Classification and Generation
Abstract: Completely Automated Public Turing test to tell Computers and Humans Apart,
short for CAPTCHA, is an essential and relatively easy way to defend against
malicious attacks implemented by bots. The security and usability trade... | Cryptography and Security |
What field is the article from? | Title: Safety-aware Causal Representation for Trustworthy Reinforcement Learning in Autonomous Driving
Abstract: In the domain of autonomous driving, the Learning from Demonstration (LfD)
paradigm has exhibited notable efficacy in addressing sequential
decision-making problems. However, consistently achieving safety in... | Robotics |
What field is the article from? | Title: Emu Edit: Precise Image Editing via Recognition and Generation Tasks
Abstract: Instruction-based image editing holds immense potential for a variety of
applications, as it enables users to perform any editing operation using a
natural language instruction. However, current models in this domain often
struggle wi... | Computer Vision |
What field is the article from? | Title: Learning impartial policies for sequential counterfactual explanations using Deep Reinforcement Learning
Abstract: In the field of explainable Artificial Intelligence (XAI), sequential
counterfactual (SCF) examples are often used to alter the decision of a trained
classifier by implementing a sequence of modific... | Machine Learning |
What field is the article from? | Title: Concept-free Causal Disentanglement with Variational Graph Auto-Encoder
Abstract: In disentangled representation learning, the goal is to achieve a compact
representation that consists of all interpretable generative factors in the
observational data. Learning disentangled representations for graphs becomes
incr... | Machine Learning |
What field is the article from? | Title: Digital Socrates: Evaluating LLMs through explanation critiques
Abstract: While LLMs can provide reasoned explanations along with their answers, the
nature and quality of those explanations are still poorly understood. In
response, our goal is to define a detailed way of characterizing the
explanation capabiliti... | Computational Linguistics |
What field is the article from? | Title: Constant-time Motion Planning with Anytime Refinement for Manipulation
Abstract: Robotic manipulators are essential for future autonomous systems, yet limited
trust in their autonomy has confined them to rigid, task-specific systems. The
intricate configuration space of manipulators, coupled with the challenges ... | Robotics |
What field is the article from? | Title: Interpretable Prototype-based Graph Information Bottleneck
Abstract: The success of Graph Neural Networks (GNNs) has led to a need for
understanding their decision-making process and providing explanations for
their predictions, which has given rise to explainable AI (XAI) that offers
transparent explanations fo... | Machine Learning |
What field is the article from? | Title: Dynamic Corrective Self-Distillation for Better Fine-Tuning of Pretrained Models
Abstract: We tackle the challenging issue of aggressive fine-tuning encountered during
the process of transfer learning of pre-trained language models (PLMs) with
limited labeled downstream data. This problem primarily results in a ... | Computational Linguistics |
What field is the article from? | Title: OC-NMN: Object-centric Compositional Neural Module Network for Generative Visual Analogical Reasoning
Abstract: A key aspect of human intelligence is the ability to imagine -- composing
learned concepts in novel ways -- to make sense of new scenarios. Such capacity
is not yet attained for machine learning system... | Artificial Intelligence |
What field is the article from? | Title: Learn to Optimize Denoising Scores for 3D Generation: A Unified and Improved Diffusion Prior on NeRF and 3D Gaussian Splatting
Abstract: We propose a unified framework aimed at enhancing the diffusion priors for 3D
generation tasks. Despite the critical importance of these tasks, existing
methodologies often str... | Computer Vision |
What field is the article from? | Title: COOL: A Constraint Object-Oriented Logic Programming Language and its Neural-Symbolic Compilation System
Abstract: This paper explores the integration of neural networks with logic
programming, addressing the longstanding challenges of combining the
generalization and learning capabilities of neural networks wit... | Artificial Intelligence |
What field is the article from? | Title: Self Generated Wargame AI: Double Layer Agent Task Planning Based on Large Language Model
Abstract: The large language models represented by ChatGPT have a disruptive impact on
the field of artificial intelligence. But it mainly focuses on natural language
processing, speech recognition, machine learning and nat... | Artificial Intelligence |
What field is the article from? | Title: Bi-directional Adapter for Multi-modal Tracking
Abstract: Due to the rapid development of computer vision, single-modal (RGB) object
tracking has made significant progress in recent years. Considering the
limitation of single imaging sensor, multi-modal images (RGB, Infrared, etc.)
are introduced to compensate f... | Computer Vision |
What field is the article from? | Title: Joint-Individual Fusion Structure with Fusion Attention Module for Multi-Modal Skin Cancer Classification
Abstract: Most convolutional neural network (CNN) based methods for skin cancer
classification obtain their results using only dermatological images. Although
good classification results have been shown, mor... | Computer Vision |
What field is the article from? | Title: Setting the Trap: Capturing and Defeating Backdoors in Pretrained Language Models through Honeypots
Abstract: In the field of natural language processing, the prevalent approach involves
fine-tuning pretrained language models (PLMs) using local samples. Recent
research has exposed the susceptibility of PLMs to b... | Machine Learning |
What field is the article from? | Title: Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt
Abstract: In this paper, we present Neural k-Opt (NeuOpt), a novel learning-to-search
(L2S) solver for routing problems. It learns to perform flexible k-opt
exchanges based on a tailored action factorization method ... | Machine Learning |
What field is the article from? | Title: Adversarial Estimation of Topological Dimension with Harmonic Score Maps
Abstract: Quantification of the number of variables needed to locally explain complex
data is often the first step to better understanding it. Existing techniques
from intrinsic dimension estimation leverage statistical models to glean this... | Machine Learning |
What field is the article from? | Title: A Novel Dataset for Financial Education Text Simplification in Spanish
Abstract: Text simplification, crucial in natural language processing, aims to make
texts more comprehensible, particularly for specific groups like visually
impaired Spanish speakers, a less-represented language in this field. In
Spanish, th... | Artificial Intelligence |
What field is the article from? | Title: Eval-GCSC: A New Metric for Evaluating ChatGPT's Performance in Chinese Spelling Correction
Abstract: ChatGPT has demonstrated impressive performance in various downstream tasks.
However, in the Chinese Spelling Correction (CSC) task, we observe a
discrepancy: while ChatGPT performs well under human evaluation, ... | Computational Linguistics |
What field is the article from? | Title: Auditing and Mitigating Cultural Bias in LLMs
Abstract: Culture fundamentally shapes people's reasoning, behavior, and communication.
Generative artificial intelligence (AI) technologies may cause a shift towards
a dominant culture. As people increasingly use AI to expedite and even automate
various professional... | Computational Linguistics |
What field is the article from? | Title: Histopathological Image Analysis with Style-Augmented Feature Domain Mixing for Improved Generalization
Abstract: Histopathological images are essential for medical diagnosis and treatment
planning, but interpreting them accurately using machine learning can be
challenging due to variations in tissue preparation... | Computer Vision |
What field is the article from? | Title: OCGEC: One-class Graph Embedding Classification for DNN Backdoor Detection
Abstract: Deep neural networks (DNNs) have been found vulnerable to backdoor attacks,
raising security concerns about their deployment in mission-critical
applications. There are various approaches to detect backdoor attacks, however
they... | Machine Learning |
What field is the article from? | Title: RLIF: Interactive Imitation Learning as Reinforcement Learning
Abstract: Although reinforcement learning methods offer a powerful framework for
automatic skill acquisition, for practical learning-based control problems in
domains such as robotics, imitation learning often provides a more convenient
and accessibl... | Artificial Intelligence |
What field is the article from? | Title: KEEC: Embed to Control on An Equivariant Geometry
Abstract: This paper investigates how representation learning can enable optimal
control in unknown and complex dynamics, such as chaotic and non-linear
systems, without relying on prior domain knowledge of the dynamics. The core
idea is to establish an equivaria... | Machine Learning |
What field is the article from? | Title: Variants of Tagged Sentential Decision Diagrams
Abstract: A recently proposed canonical form of Boolean functions, namely tagged
sentential decision diagrams (TSDDs), exploits both the standard and
zero-suppressed trimming rules. The standard ones minimize the size of
sentential decision diagrams (SDDs) while th... | Artificial Intelligence |
What field is the article from? | Title: Hyper-Relational Knowledge Graph Neural Network for Next POI
Abstract: With the advancement of mobile technology, Point of Interest (POI)
recommendation systems in Location-based Social Networks (LBSN) have brought
numerous benefits to both users and companies. Many existing works employ
Knowledge Graph (KG) to ... | Artificial Intelligence |
What field is the article from? | Title: Categorizing the Visual Environment and Analyzing the Visual Attention of Dogs
Abstract: Dogs have a unique evolutionary relationship with humans and serve many
important roles e.g. search and rescue, blind assistance, emotional support.
However, few datasets exist to categorize visual features and objects avail... | Computer Vision |
What field is the article from? | Title: ChatGPT-3.5, ChatGPT-4, Google Bard, and Microsoft Bing to Improve Health Literacy and Communication in Pediatric Populations and Beyond
Abstract: Purpose: Enhanced health literacy has been linked to better health outcomes;
however, few interventions have been studied. We investigate whether large
language model... | Computational Linguistics |
What field is the article from? | Title: Is a Seat at the Table Enough? Engaging Teachers and Students in Dataset Specification for ML in Education
Abstract: Despite the promises of ML in education, its adoption in the classroom has
surfaced numerous issues regarding fairness, accountability, and transparency,
as well as concerns about data privacy and... | Computers and Society |
What field is the article from? | Title: Anatomically-aware Uncertainty for Semi-supervised Image Segmentation
Abstract: Semi-supervised learning relaxes the need of large pixel-wise labeled
datasets for image segmentation by leveraging unlabeled data. A prominent way
to exploit unlabeled data is to regularize model predictions. Since the
predictions o... | Computer Vision |
What field is the article from? | Title: StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization
Abstract: In this paper, we investigate the long-term memory learning capabilities of
state-space models (SSMs) from the perspective of parameterization. We prove
that state-space models without any reparameterizat... | Machine Learning |
What field is the article from? | Title: Large Multimodal Model Compression via Efficient Pruning and Distillation at AntGroup
Abstract: The deployment of Large Multimodal Models (LMMs) within AntGroup has
significantly advanced multimodal tasks in payment, security, and advertising,
notably enhancing advertisement audition tasks in Alipay. However, th... | Artificial Intelligence |
What field is the article from? | Title: Transfer Learning-based Real-time Handgun Detection
Abstract: Traditional surveillance systems rely on human attention, limiting their
effectiveness. This study employs convolutional neural networks and transfer
learning to develop a real-time computer vision system for automatic handgun
detection. Comprehensive... | Computer Vision |
What field is the article from? | Title: CMed-GPT: Prompt Tuning for Entity-Aware Chinese Medical Dialogue Generation
Abstract: Medical dialogue generation relies on natural language generation techniques
to enable online medical consultations. Recently, the widespread adoption of
large-scale models in the field of natural language processing has facil... | Computational Linguistics |
What field is the article from? | Title: Accommodating Missing Modalities in Time-Continuous Multimodal Emotion Recognition
Abstract: Decades of research indicate that emotion recognition is more effective when
drawing information from multiple modalities. But what if some modalities are
sometimes missing? To address this problem, we propose a novel
Tr... | Machine Learning |
What field is the article from? | Title: Language Models: A Guide for the Perplexed
Abstract: Given the growing importance of AI literacy, we decided to write this
tutorial to help narrow the gap between the discourse among those who study
language models -- the core technology underlying ChatGPT and similar products
-- and those who are intrigued and ... | Computational Linguistics |
What field is the article from? | Title: Maximal Consistent Subsystems of Max-T Fuzzy Relational Equations
Abstract: In this article, we study the inconsistency of a system of $\max-T$ fuzzy
relational equations of the form $A \Box_{T}^{\max} x = b$, where $T$ is a
t-norm among $\min$, the product or Lukasiewicz's t-norm. For an inconsistent
$\max-T$ s... | Artificial Intelligence |
What field is the article from? | Title: How Far Can Fairness Constraints Help Recover From Biased Data?
Abstract: Blum & Stangl (2019) propose a data bias model to simulate
under-representation and label bias in underprivileged population. For a
stylized data distribution with i.i.d. label noise, under certain simple
conditions on the bias parameters,... | Machine Learning |
What field is the article from? | Title: The devil is in the fine-grained details: Evaluating open-vocabulary object detectors for fine-grained understanding
Abstract: Recent advancements in large vision-language models enabled visual object
detection in open-vocabulary scenarios, where object classes are defined in
free-text formats during inference. ... | Computer Vision |
What field is the article from? | Title: Weighted Sampled Split Learning (WSSL): Balancing Privacy, Robustness, and Fairness in Distributed Learning Environments
Abstract: This study presents Weighted Sampled Split Learning (WSSL), an innovative
framework tailored to bolster privacy, robustness, and fairness in distributed
machine learning systems. Unl... | Machine Learning |
What field is the article from? | Title: Long-Horizon Dialogue Understanding for Role Identification in the Game of Avalon with Large Language Models
Abstract: Deception and persuasion play a critical role in long-horizon dialogues
between multiple parties, especially when the interests, goals, and motivations
of the participants are not aligned. Such ... | Computational Linguistics |
What field is the article from? | Title: On Training Implicit Meta-Learning With Applications to Inductive Weighing in Consistency Regularization
Abstract: Meta-learning that uses implicit gradient have provided an exciting
alternative to standard techniques which depend on the trajectory of the inner
loop training. Implicit meta-learning (IML), howeve... | Machine Learning |
What field is the article from? | Title: AdaptiX -- A Transitional XR Framework for Development and Evaluation of Shared Control Applications in Assistive Robotics
Abstract: With the ongoing efforts to empower people with mobility impairments and the
increase in technological acceptance by the general public, assistive
technologies, such as collaborati... | Human-Computer Interaction |
What field is the article from? | Title: Spreeze: High-Throughput Parallel Reinforcement Learning Framework
Abstract: The promotion of large-scale applications of reinforcement learning (RL)
requires efficient training computation. While existing parallel RL frameworks
encompass a variety of RL algorithms and parallelization techniques, the
excessively... | Machine Learning |
What field is the article from? | Title: Complexity-Guided Curriculum Learning for Text Graphs
Abstract: Curriculum learning provides a systematic approach to training. It refines
training progressively, tailors training to task requirements, and improves
generalization through exposure to diverse examples. We present a curriculum
learning approach tha... | Computational Linguistics |
What field is the article from? | Title: ESG Accountability Made Easy: DocQA at Your Service
Abstract: We present Deep Search DocQA. This application enables information extraction
from documents via a question-answering conversational assistant. The system
integrates several technologies from different AI disciplines consisting of
document conversion ... | Computational Linguistics |
What field is the article from? | Title: How ChatGPT is Solving Vulnerability Management Problem
Abstract: Recently, ChatGPT has attracted great attention from the code analysis
domain. Prior works show that ChatGPT has the capabilities of processing
foundational code analysis tasks, such as abstract syntax tree generation,
which indicates the potentia... | Software Engineering |
What field is the article from? | Title: FP8-BERT: Post-Training Quantization for Transformer
Abstract: Transformer-based models, such as BERT, have been widely applied in a wide
range of natural language processing tasks. However, one inevitable side effect
is that they require massive memory storage and inference cost when deployed in
production. Qua... | Artificial Intelligence |
What field is the article from? | Title: Examining the Effect of Implementation Factors on Deep Learning Reproducibility
Abstract: Reproducing published deep learning papers to validate their conclusions can
be difficult due to sources of irreproducibility. We investigate the impact
that implementation factors have on the results and how they affect
re... | Artificial Intelligence |
What field is the article from? | Title: JPAVE: A Generation and Classification-based Model for Joint Product Attribute Prediction and Value Extraction
Abstract: Product attribute value extraction is an important task in e-Commerce which
can help several downstream applications such as product search and
recommendation. Most previous models handle this... | Computational Linguistics |
What field is the article from? | Title: EDA: Evolving and Distinct Anchors for Multimodal Motion Prediction
Abstract: Motion prediction is a crucial task in autonomous driving, and one of its
major challenges lands in the multimodality of future behaviors. Many
successful works have utilized mixture models which require identification of
positive mixt... | Computer Vision |
What field is the article from? | Title: Modular Blended Attention Network for Video Question Answering
Abstract: In multimodal machine learning tasks, it is due to the complexity of the
assignments that the network structure, in most cases, is assembled in a
sophisticated way. The holistic architecture can be separated into several
logical parts accor... | Computer Vision |
What field is the article from? | Title: Investigating Deep-Learning NLP for Automating the Extraction of Oncology Efficacy Endpoints from Scientific Literature
Abstract: Benchmarking drug efficacy is a critical step in clinical trial design and
planning. The challenge is that much of the data on efficacy endpoints is
stored in scientific papers in fre... | Computational Linguistics |
What field is the article from? | Title: Unveiling Empirical Pathologies of Laplace Approximation for Uncertainty Estimation
Abstract: In this paper, we critically evaluate Bayesian methods for uncertainty
estimation in deep learning, focusing on the widely applied Laplace
approximation and its variants. Our findings reveal that the conventional
method... | Machine Learning |
What field is the article from? | Title: One Shot Learning as Instruction Data Prospector for Large Language Models
Abstract: Aligning large language models(LLMs) with human is a critical step in
effectively utilizing their pre-trained capabilities across a wide array of
language tasks. Current instruction tuning practices often rely on expanding
datas... | Computational Linguistics |
What field is the article from? | Title: Wide Flat Minimum Watermarking for Robust Ownership Verification of GANs
Abstract: We propose a novel multi-bit box-free watermarking method for the protection
of Intellectual Property Rights (IPR) of GANs with improved robustness against
white-box attacks like fine-tuning, pruning, quantization, and surrogate m... | Computer Vision |
What field is the article from? | Title: Bayesian Neural Networks: A Min-Max Game Framework
Abstract: Bayesian neural networks use random variables to describe the neural networks
rather than deterministic neural networks and are mostly trained by variational
inference which updates the mean and variance at the same time. Here, we
formulate the Bayesia... | Machine Learning |
What field is the article from? | Title: A Weighted K-Center Algorithm for Data Subset Selection
Abstract: The success of deep learning hinges on enormous data and large models, which
require labor-intensive annotations and heavy computation costs. Subset
selection is a fundamental problem that can play a key role in identifying
smaller portions of the... | Machine Learning |
What field is the article from? | Title: Mesh Neural Cellular Automata
Abstract: Modeling and synthesizing textures are essential for enhancing the realism of
virtual environments. Methods that directly synthesize textures in 3D offer
distinct advantages to the UV-mapping-based methods as they can create seamless
textures and align more closely with th... | Computer Vision |
What field is the article from? | Title: ArTST: Arabic Text and Speech Transformer
Abstract: We present ArTST, a pre-trained Arabic text and speech transformer for
supporting open-source speech technologies for the Arabic language. The model
architecture follows the unified-modal framework, SpeechT5, that was recently
released for English, and is focus... | Computational Linguistics |
What field is the article from? | Title: TimelyGPT: Recurrent Convolutional Transformer for Long Time-series Representation
Abstract: Pre-trained models (PTMs) have gained prominence in Natural Language
Processing and Computer Vision domains. When it comes to time-series PTMs,
their development has been limited. Previous research on time-series
transfo... | Machine Learning |
What field is the article from? | Title: Scheming AIs: Will AIs fake alignment during training in order to get power?
Abstract: This report examines whether advanced AIs that perform well in training will
be doing so in order to gain power later -- a behavior I call "scheming" (also
sometimes called "deceptive alignment"). I conclude that scheming is a... | Computers and Society |
What field is the article from? | Title: A Universal Anti-Spoofing Approach for Contactless Fingerprint Biometric Systems
Abstract: With the increasing integration of smartphones into our daily lives,
fingerphotos are becoming a potential contactless authentication method. While
it offers convenience, it is also more vulnerable to spoofing using variou... | Computer Vision |
What field is the article from? | Title: Grounding for Artificial Intelligence
Abstract: A core function of intelligence is grounding, which is the process of
connecting the natural language and abstract knowledge to the internal
representation of the real world in an intelligent being, e.g., a human. Human
cognition is grounded in our sensorimotor exp... | Artificial Intelligence |
What field is the article from? | Title: Efficient Open-world Reinforcement Learning via Knowledge Distillation and Autonomous Rule Discovery
Abstract: Deep reinforcement learning suffers from catastrophic forgetting and sample
inefficiency making it less applicable to the ever-changing real world.
However, the ability to use previously learned knowled... | Artificial Intelligence |
What field is the article from? | Title: Medical Image Classification Using Transfer Learning and Chaos Game Optimization on the Internet of Medical Things
Abstract: The Internet of Medical Things (IoMT) has dramatically benefited medical
professionals that patients and physicians can access from all regions.
Although the automatic detection and predic... | Computer Vision |
What field is the article from? | Title: An Expectation-Realization Model for Metaphor Detection
Abstract: We propose a metaphor detection architecture that is structured around two
main modules: an expectation component that estimates representations of
literal word expectations given a context, and a realization component that
computes representation... | Computational Linguistics |
What field is the article from? | Title: Uncertainty-guided Boundary Learning for Imbalanced Social Event Detection
Abstract: Real-world social events typically exhibit a severe class-imbalance
distribution, which makes the trained detection model encounter a serious
generalization challenge. Most studies solve this problem from the frequency
perspecti... | Artificial Intelligence |
What field is the article from? | Title: KirchhoffNet: A Circuit Bridging Message Passing and Continuous-Depth Models
Abstract: In this paper, we exploit a fundamental principle of analog electronic
circuitry, Kirchhoff's current law, to introduce a unique class of neural
network models that we refer to as KirchhoffNet. KirchhoffNet establishes close
c... | Machine Learning |
What field is the article from? | Title: Fast Scalable and Accurate Discovery of DAGs Using the Best Order Score Search and Grow-Shrink Trees
Abstract: Learning graphical conditional independence structures is an important
machine learning problem and a cornerstone of causal discovery. However, the
accuracy and execution time of learning algorithms gen... | Machine Learning |
What field is the article from? | Title: Muscle volume quantification: guiding transformers with anatomical priors
Abstract: Muscle volume is a useful quantitative biomarker in sports, but also for the
follow-up of degenerative musculo-skelletal diseases. In addition to volume,
other shape biomarkers can be extracted by segmenting the muscles of intere... | Computer Vision |
What field is the article from? | Title: Gene-MOE: A sparsely gated prognosis and classification framework exploiting pan-cancer genomic information
Abstract: Benefiting from the advancements in deep learning, various genomic analytical
techniques, such as survival analysis, classification of tumors and their
subtypes, and exploration of specific pathw... | Machine Learning |
What field is the article from? | Title: WaterBench: Towards Holistic Evaluation of Watermarks for Large Language Models
Abstract: To mitigate the potential misuse of large language models (LLMs), recent
research has developed watermarking algorithms, which restrict the generation
process to leave an invisible trace for watermark detection. Due to the
... | Computational Linguistics |
What field is the article from? | Title: CoSeR: Bridging Image and Language for Cognitive Super-Resolution
Abstract: Existing super-resolution (SR) models primarily focus on restoring local
texture details, often neglecting the global semantic information within the
scene. This oversight can lead to the omission of crucial semantic details or
the intro... | Computer Vision |
What field is the article from? | Title: Mixture of Weak & Strong Experts on Graphs
Abstract: Realistic graphs contain both rich self-features of nodes and informative
structures of neighborhoods, jointly handled by a GNN in the typical setup. We
propose to decouple the two modalities by mixture of weak and strong experts
(Mowst), where the weak expert... | Machine Learning |
What field is the article from? | Title: Co-training and Co-distillation for Quality Improvement and Compression of Language Models
Abstract: Knowledge Distillation (KD) compresses computationally expensive pre-trained
language models (PLMs) by transferring their knowledge to smaller models,
allowing their use in resource-constrained or real-time setti... | Computational Linguistics |
What field is the article from? | Title: Towards A Holistic Landscape of Situated Theory of Mind in Large Language Models
Abstract: Large Language Models (LLMs) have generated considerable interest and debate
regarding their potential emergence of Theory of Mind (ToM). Several recent
inquiries reveal a lack of robust ToM in these models and pose a pres... | Computational Linguistics |
What field is the article from? | Title: LanGWM: Language Grounded World Model
Abstract: Recent advances in deep reinforcement learning have showcased its potential
in tackling complex tasks. However, experiments on visual control tasks have
revealed that state-of-the-art reinforcement learning models struggle with
out-of-distribution generalization. C... | Machine Learning |
What field is the article from? | Title: From Coupled Oscillators to Graph Neural Networks: Reducing Over-smoothing via a Kuramoto Model-based Approach
Abstract: We propose the Kuramoto Graph Neural Network (KuramotoGNN), a novel class of
continuous-depth graph neural networks (GNNs) that employs the Kuramoto model
to mitigate the over-smoothing phenom... | Machine Learning |
What field is the article from? | Title: MindLLM: Pre-training Lightweight Large Language Model from Scratch, Evaluations and Domain Applications
Abstract: Large Language Models (LLMs) have demonstrated remarkable performance across
various natural language tasks, marking significant strides towards general
artificial intelligence. While general artifi... | Computational Linguistics |
What field is the article from? | Title: CERN for AGI: A Theoretical Framework for Autonomous Simulation-Based Artificial Intelligence Testing and Alignment
Abstract: This paper explores the potential of a multidisciplinary approach to testing
and aligning artificial general intelligence (AGI) and LLMs. Due to the rapid
development and wide application... | Computers and Society |
What field is the article from? | Title: Inferring Latent Class Statistics from Text for Robust Visual Few-Shot Learning
Abstract: In the realm of few-shot learning, foundation models like CLIP have proven
effective but exhibit limitations in cross-domain robustness especially in
few-shot settings. Recent works add text as an extra modality to enhance ... | Computer Vision |
What field is the article from? | Title: Visual Explanations via Iterated Integrated Attributions
Abstract: We introduce Iterated Integrated Attributions (IIA) - a generic method for
explaining the predictions of vision models. IIA employs iterative integration
across the input image, the internal representations generated by the model,
and their gradi... | Computer Vision |
What field is the article from? | Title: Robust Fine-Tuning of Vision-Language Models for Domain Generalization
Abstract: Transfer learning enables the sharing of common knowledge among models for a
variety of downstream tasks, but traditional methods suffer in limited training
data settings and produce narrow models incapable of effectively generalizi... | Computer Vision |
What field is the article from? | Title: Quantifying Impairment and Disease Severity Using AI Models Trained on Healthy Subjects
Abstract: Automatic assessment of impairment and disease severity is a key challenge in
data-driven medicine. We propose a novel framework to address this challenge,
which leverages AI models trained exclusively on healthy in... | Machine Learning |
What field is the article from? | Title: Optimizing IaC Configurations: a Case Study Using Nature-inspired Computing
Abstract: In the last years, one of the fields of artificial intelligence that has been
investigated the most is nature-inspired computing. The research done on this
specific topic showcases the interest that sparks in researchers and
pr... | Software Engineering |
What field is the article from? | Title: Towards a Unified Conversational Recommendation System: Multi-task Learning via Contextualized Knowledge Distillation
Abstract: In Conversational Recommendation System (CRS), an agent is asked to recommend
a set of items to users within natural language conversations. To address the
need for both conversational ... | Computational Linguistics |
What field is the article from? | Title: HeTriNet: Heterogeneous Graph Triplet Attention Network for Drug-Target-Disease Interaction
Abstract: Modeling the interactions between drugs, targets, and diseases is paramount
in drug discovery and has significant implications for precision medicine and
personalized treatments. Current approaches frequently co... | Machine Learning |
What field is the article from? | Title: Classification of Tabular Data by Text Processing
Abstract: Natural Language Processing technology has advanced vastly in the past
decade. Text processing has been successfully applied to a wide variety of
domains. In this paper, we propose a novel framework, Text Based
Classification(TBC), that uses state of th... | Artificial Intelligence |
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