instruction stringclasses 1
value | input stringlengths 260 2.07k | output stringclasses 10
values |
|---|---|---|
What field is the article from? | Title: Gauge-optimal approximate learning for small data classification problems
Abstract: Small data learning problems are characterized by a significant discrepancy
between the limited amount of response variable observations and the large
feature space dimension. In this setting, the common learning tools struggle t... | Machine Learning |
What field is the article from? | Title: Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning
Abstract: In real-world reinforcement learning problems, the state information is often
only partially observable, which breaks the basic assumption in Markov decision
processes, and thus, leads to inferior performanc... | Machine Learning |
What field is the article from? | Title: Quantifying Divergence for Human-AI Collaboration and Cognitive Trust
Abstract: Predicting the collaboration likelihood and measuring cognitive trust to AI
systems is more important than ever. To do that, previous research mostly focus
solely on the model features (e.g., accuracy, confidence) and ignore the huma... | Artificial Intelligence |
What field is the article from? | Title: Do personality tests generalize to Large Language Models?
Abstract: With large language models (LLMs) appearing to behave increasingly human-like
in text-based interactions, it has become popular to attempt to evaluate
various properties of these models using tests originally designed for humans.
While re-using ... | Computational Linguistics |
What field is the article from? | Title: Domain Knowledge Injection in Bayesian Search for New Materials
Abstract: In this paper we propose DKIBO, a Bayesian optimization (BO) algorithm that
accommodates domain knowledge to tune exploration in the search space. Bayesian
optimization has recently emerged as a sample-efficient optimizer for many
intracta... | Artificial Intelligence |
What field is the article from? | Title: Manifold Preserving Guided Diffusion
Abstract: Despite the recent advancements, conditional image generation still faces
challenges of cost, generalizability, and the need for task-specific training.
In this paper, we propose Manifold Preserving Guided Diffusion (MPGD), a
training-free conditional generation fra... | Machine Learning |
What field is the article from? | Title: FLIP: Towards Fine-grained Alignment between ID-based Models and Pretrained Language Models for CTR Prediction
Abstract: Click-through rate (CTR) prediction plays as a core function module in
various personalized online services. The traditional ID-based models for CTR
prediction take as inputs the one-hot encod... | Information Retrieval |
What field is the article from? | Title: Erasing Self-Supervised Learning Backdoor by Cluster Activation Masking
Abstract: Researchers have recently found that Self-Supervised Learning (SSL) is
vulnerable to backdoor attacks. The attacker can embed hidden SSL backdoors via
a few poisoned examples in the training dataset and maliciously manipulate the
b... | Computer Vision |
What field is the article from? | Title: Rosetta Stone at the Arabic Reverse Dictionary Shared Task: A Hop From Language Modeling To Word--Definition Alignment
Abstract: A Reverse Dictionary is a tool enabling users to discover a word based on its
provided definition, meaning, or description. Such a technique proves valuable
in various scenarios, aidin... | Computational Linguistics |
What field is the article from? | Title: A Taxonomy of Rater Disagreements: Surveying Challenges & Opportunities from the Perspective of Annotating Online Toxicity
Abstract: Toxicity is an increasingly common and severe issue in online spaces.
Consequently, a rich line of machine learning research over the past decade has
focused on computationally det... | Computational Linguistics |
What field is the article from? | Title: BEDD: The MineRL BASALT Evaluation and Demonstrations Dataset for Training and Benchmarking Agents that Solve Fuzzy Tasks
Abstract: The MineRL BASALT competition has served to catalyze advances in learning
from human feedback through four hard-to-specify tasks in Minecraft, such as
create and photograph a waterf... | Artificial Intelligence |
What field is the article from? | Title: Investigating Responsible AI for Scientific Research: An Empirical Study
Abstract: Scientific research organizations that are developing and deploying
Artificial Intelligence (AI) systems are at the intersection of technological
progress and ethical considerations. The push for Responsible AI (RAI) in such
insti... | Artificial Intelligence |
What field is the article from? | Title: Foundation Models for Weather and Climate Data Understanding: A Comprehensive Survey
Abstract: As artificial intelligence (AI) continues to rapidly evolve, the realm of
Earth and atmospheric sciences is increasingly adopting data-driven models,
powered by progressive developments in deep learning (DL). Specifica... | Machine Learning |
What field is the article from? | Title: On the Initialization of Graph Neural Networks
Abstract: Graph Neural Networks (GNNs) have displayed considerable promise in graph
representation learning across various applications. The core learning process
requires the initialization of model weight matrices within each GNN layer,
which is typically accompli... | Machine Learning |
What field is the article from? | Title: Authoring Worked Examples for Java Programming with Human-AI Collaboration
Abstract: Worked examples (solutions to typical programming problems presented as a
source code in a certain language and are used to explain the topics from a
programming class) are among the most popular types of learning content in
pro... | Human-Computer Interaction |
What field is the article from? | Title: Deep Learning-Empowered Semantic Communication Systems with a Shared Knowledge Base
Abstract: Deep learning-empowered semantic communication is regarded as a promising
candidate for future 6G networks. Although existing semantic communication
systems have achieved superior performance compared to traditional met... | Artificial Intelligence |
What field is the article from? | Title: Reward Certification for Policy Smoothed Reinforcement Learning
Abstract: Reinforcement Learning (RL) has achieved remarkable success in
safety-critical areas, but it can be weakened by adversarial attacks. Recent
studies have introduced "smoothed policies" in order to enhance its robustness.
Yet, it is still ch... | Machine Learning |
What field is the article from? | Title: SCADI: Self-supervised Causal Disentanglement in Latent Variable Models
Abstract: Causal disentanglement has great potential for capturing complex situations.
However, there is a lack of practical and efficient approaches. It is already
known that most unsupervised disentangling methods are unable to produce
ide... | Machine Learning |
What field is the article from? | Title: The perpetual motion machine of AI-generated data and the distraction of ChatGPT-as-scientist
Abstract: Since ChatGPT works so well, are we on the cusp of solving science with AI?
Is not AlphaFold2 suggestive that the potential of LLMs in biology and the
sciences more broadly is limitless? Can we use AI itself t... | Machine Learning |
What field is the article from? | Title: Explainable artificial intelligence for Healthcare applications using Random Forest Classifier with LIME and SHAP
Abstract: With the advances in computationally efficient artificial Intelligence (AI)
techniques and their numerous applications in our everyday life, there is a
pressing need to understand the compu... | Machine Learning |
What field is the article from? | Title: FRDiff: Feature Reuse for Exquisite Zero-shot Acceleration of Diffusion Models
Abstract: The substantial computational costs of diffusion models, particularly due to
the repeated denoising steps crucial for high-quality image generation, present
a major obstacle to their widespread adoption. While several studie... | Computer Vision |
What field is the article from? | Title: Evaluating the Utility of Model Explanations for Model Development
Abstract: One of the motivations for explainable AI is to allow humans to make better
and more informed decisions regarding the use and deployment of AI models. But
careful evaluations are needed to assess whether this expectation has been
fulfil... | Artificial Intelligence |
What field is the article from? | Title: ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning
Abstract: Climate models have been key for assessing the impact of climate change and
simulating future climate scenarios. The machine learning (ML) community has
taken an increased interest in supporting climate scientists' efforts on
various ... | Machine Learning |
What field is the article from? | Title: Learning-based Scheduling for Information Accuracy and Freshness in Wireless Networks
Abstract: We consider a system of multiple sources, a single communication channel, and
a single monitoring station. Each source measures a time-varying quantity with
varying levels of accuracy and one of them sends its update ... | Artificial Intelligence |
What field is the article from? | Title: Ransomware Detection and Classification using Machine Learning
Abstract: Vicious assaults, malware, and various ransomware pose a cybersecurity
threat, causing considerable damage to computer structures, servers, and mobile
and web apps across various industries and businesses. These safety concerns
are importan... | Cryptography and Security |
What field is the article from? | Title: STEP CATFormer: Spatial-Temporal Effective Body-Part Cross Attention Transformer for Skeleton-based Action Recognition
Abstract: Graph convolutional networks (GCNs) have been widely used and achieved
remarkable results in skeleton-based action recognition. We think the key to
skeleton-based action recognition is... | Computer Vision |
What field is the article from? | Title: On the Effects of Randomness on Stability of Learning with Limited Labelled Data: A Systematic Literature Review
Abstract: Learning with limited labelled data, such as few-shot learning, meta-learning
or transfer learning, aims to effectively train a model using only small amount
of labelled samples. However, th... | Machine Learning |
What field is the article from? | Title: Stacking the Odds: Transformer-Based Ensemble for AI-Generated Text Detection
Abstract: This paper reports our submission under the team name `SynthDetectives' to
the ALTA 2023 Shared Task. We use a stacking ensemble of Transformers for the
task of AI-generated text detection. Our approach is novel in terms of i... | Computational Linguistics |
What field is the article from? | Title: Is one brick enough to break the wall of spoken dialogue state tracking?
Abstract: In Task-Oriented Dialogue (TOD) systems, correctly updating the system's
understanding of the user's needs (a.k.a dialogue state tracking) is key to a
smooth interaction. Traditionally, TOD systems perform this update in three
ste... | Computational Linguistics |
What field is the article from? | Title: LDM$^2$: A Large Decision Model Imitating Human Cognition with Dynamic Memory Enhancement
Abstract: With the rapid development of large language models (LLMs), it is highly
demanded that LLMs can be adopted to make decisions to enable the artificial
general intelligence. Most approaches leverage manually crafted... | Machine Learning |
What field is the article from? | Title: Human Machine Co-Creation. A Complementary Cognitive Approach to Creative Character Design Process Using GANs
Abstract: Recent advances in Generative Adversarial Networks GANs applications continue
to attract the attention of researchers in different fields. In such a
framework, two neural networks compete adver... | Artificial Intelligence |
What field is the article from? | Title: A Large-Scale Car Parts (LSCP) Dataset for Lightweight Fine-Grained Detection
Abstract: Automotive related datasets have previously been used for training autonomous
driving systems or vehicle classification tasks. However, there is a lack of
datasets in the field of automotive AI for car parts detection, and mo... | Computer Vision |
What field is the article from? | Title: Prompt Me Up: Unleashing the Power of Alignments for Multimodal Entity and Relation Extraction
Abstract: How can we better extract entities and relations from text? Using multimodal
extraction with images and text obtains more signals for entities and
relations, and aligns them through graphs or hierarchical fus... | Computational Linguistics |
What field is the article from? | Title: Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale
Abstract: Neural Architecture Search (NAS) has demonstrated its efficacy in computer
vision and potential for ranking systems. However, prior work focused on
academic problems, which are evaluated at small scale under well-contro... | Machine Learning |
What field is the article from? | Title: Deep Dynamics: Vehicle Dynamics Modeling with a Physics-Informed Neural Network for Autonomous Racing
Abstract: Autonomous racing is a critical research area for autonomous driving,
presenting significant challenges in vehicle dynamics modeling, such as
balancing model precision and computational efficiency at h... | Robotics |
What field is the article from? | Title: Comparative Analysis of Transformers for Modeling Tabular Data: A Casestudy using Industry Scale Dataset
Abstract: We perform a comparative analysis of transformer-based models designed for
modeling tabular data, specifically on an industry-scale dataset. While earlier
studies demonstrated promising outcomes on ... | Machine Learning |
What field is the article from? | Title: Digital Life Project: Autonomous 3D Characters with Social Intelligence
Abstract: In this work, we present Digital Life Project, a framework utilizing language
as the universal medium to build autonomous 3D characters, who are capable of
engaging in social interactions and expressing with articulated body motion... | Computer Vision |
What field is the article from? | Title: Towards Garment Sewing Pattern Reconstruction from a Single Image
Abstract: Garment sewing pattern represents the intrinsic rest shape of a garment, and
is the core for many applications like fashion design, virtual try-on, and
digital avatars. In this work, we explore the challenging problem of recovering
garme... | Computer Vision |
What field is the article from? | Title: Identifying Semantic Component for Robust Molecular Property Prediction
Abstract: Although graph neural networks have achieved great success in the task of
molecular property prediction in recent years, their generalization ability
under out-of-distribution (OOD) settings is still under-explored. Different
from ... | Machine Learning |
What field is the article from? | Title: Voice Recognition Robot with Real-Time Surveillance and Automation
Abstract: Voice recognition technology enables the execution of real-world operations
through a single voice command. This paper introduces a voice recognition
system that involves converting input voice signals into corresponding text
using an A... | Robotics |
What field is the article from? | Title: The Power of the Senses: Generalizable Manipulation from Vision and Touch through Masked Multimodal Learning
Abstract: Humans rely on the synergy of their senses for most essential tasks. For
tasks requiring object manipulation, we seamlessly and effectively exploit the
complementarity of our senses of vision an... | Robotics |
What field is the article from? | Title: Sparse4D v3: Advancing End-to-End 3D Detection and Tracking
Abstract: In autonomous driving perception systems, 3D detection and tracking are the
two fundamental tasks. This paper delves deeper into this field, building upon
the Sparse4D framework. We introduce two auxiliary training tasks (Temporal
Instance Den... | Computer Vision |
What field is the article from? | Title: On the Inadequacy of Similarity-based Privacy Metrics: Reconstruction Attacks against "Truly Anonymous Synthetic Data''
Abstract: Training generative models to produce synthetic data is meant to provide a
privacy-friendly approach to data release. However, we get robust guarantees
only when models are trained to... | Cryptography and Security |
What field is the article from? | Title: MARRS: Multimodal Reference Resolution System
Abstract: Successfully handling context is essential for any dialog understanding task.
This context maybe be conversational (relying on previous user queries or
system responses), visual (relying on what the user sees, for example, on their
screen), or background (b... | Computational Linguistics |
What field is the article from? | Title: Enhancing Sentiment Analysis Results through Outlier Detection Optimization
Abstract: When dealing with text data containing subjective labels like speaker
emotions, inaccuracies or discrepancies among labelers are not uncommon. Such
discrepancies can significantly affect the performance of machine learning
algo... | Machine Learning |
What field is the article from? | Title: Ensemble Federated Learning: an approach for collaborative pneumonia diagnosis
Abstract: Federated learning is a very convenient approach for scenarios where (i) the
exchange of data implies privacy concerns and/or (ii) a quick reaction is
needed. In smart healthcare systems, both aspects are usually required. I... | Computer Vision |
What field is the article from? | Title: GraphRARE: Reinforcement Learning Enhanced Graph Neural Network with Relative Entropy
Abstract: Graph neural networks (GNNs) have shown advantages in graph-based analysis
tasks. However, most existing methods have the homogeneity assumption and show
poor performance on heterophilic graphs, where the linked nodes... | Machine Learning |
What field is the article from? | Title: Accelerating Reinforcement Learning of Robotic Manipulations via Feedback from Large Language Models
Abstract: Reinforcement Learning (RL) plays an important role in the robotic
manipulation domain since it allows self-learning from trial-and-error
interactions with the environment. Still, sample efficiency and ... | Robotics |
What field is the article from? | Title: The Claire French Dialogue Dataset
Abstract: We present the Claire French Dialogue Dataset (CFDD), a resource created by
members of LINAGORA Labs in the context of the OpenLLM France initiative. CFDD
is a corpus containing roughly 160 million words from transcripts and stage
plays in French that we have assemble... | Computational Linguistics |
What field is the article from? | Title: Speak Like a Native: Prompting Large Language Models in a Native Style
Abstract: Existing work has found that the prompt engineering heavily influences the
performance of large language models (LLMs). Chain-of-thought (CoT), as a
popular prompt engineering technique, prompted LLMs using in-context examples
with ... | Artificial Intelligence |
What field is the article from? | Title: Modified Genetic Algorithm for Feature Selection and Hyper Parameter Optimization: Case of XGBoost in Spam Prediction
Abstract: Recently, spam on online social networks has attracted attention in the
research and business world. Twitter has become the preferred medium to spread
spam content. Many research effort... | Machine Learning |
What field is the article from? | Title: Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning
Abstract: Offline-to-online reinforcement learning (RL) is a training paradigm that
combines pre-training on a pre-collected dataset with fine-tuning in an online
environment. However, the incorporation of online fine-... | Machine Learning |
What field is the article from? | Title: Regions are Who Walk Them: a Large Pre-trained Spatiotemporal Model Based on Human Mobility for Ubiquitous Urban Sensing
Abstract: User profiling and region analysis are two tasks of significant commercial
value. However, in practical applications, modeling different features
typically involves four main steps: ... | Machine Learning |
What field is the article from? | Title: APoLLo: Unified Adapter and Prompt Learning for Vision Language Models
Abstract: The choice of input text prompt plays a critical role in the performance of
Vision-Language Pretrained (VLP) models such as CLIP. We present APoLLo, a
unified multi-modal approach that combines Adapter and Prompt learning for
Vision... | Machine Learning |
What field is the article from? | Title: A Review of the Evidence for Existential Risk from AI via Misaligned Power-Seeking
Abstract: Rapid advancements in artificial intelligence (AI) have sparked growing
concerns among experts, policymakers, and world leaders regarding the potential
for increasingly advanced AI systems to pose existential risks. This... | Computers and Society |
What field is the article from? | Title: Accelerating Exploration with Unlabeled Prior Data
Abstract: Learning to solve tasks from a sparse reward signal is a major challenge for
standard reinforcement learning (RL) algorithms. However, in the real world,
agents rarely need to solve sparse reward tasks entirely from scratch. More
often, we might posses... | Machine Learning |
What field is the article from? | Title: Building Trustworthy NeuroSymbolic AI Systems: Consistency, Reliability, Explainability, and Safety
Abstract: Explainability and Safety engender Trust. These require a model to exhibit
consistency and reliability. To achieve these, it is necessary to use and
analyze data and knowledge with statistical and symbol... | Artificial Intelligence |
What field is the article from? | Title: CAT: A Causally Graph Attention Network for Trimming Heterophilic Graph
Abstract: Local Attention-guided Message Passing Mechanism (LAMP) adopted in Graph
Attention Networks (GATs) is designed to adaptively learn the importance of
neighboring nodes for better local aggregation on the graph, which can bring
the r... | Machine Learning |
What field is the article from? | Title: Harmonic Mobile Manipulation
Abstract: Recent advancements in robotics have enabled robots to navigate complex
scenes or manipulate diverse objects independently. However, robots are still
impotent in many household tasks requiring coordinated behaviors such as
opening doors. The factorization of navigation and ... | Robotics |
What field is the article from? | Title: Pedestrian Attribute Recognition via CLIP based Prompt Vision-Language Fusion
Abstract: Existing pedestrian attribute recognition (PAR) algorithms adopt pre-trained
CNN (e.g., ResNet) as their backbone network for visual feature learning, which
might obtain sub-optimal results due to the insufficient employment ... | Computer Vision |
What field is the article from? | Title: Lite-Mind: Towards Efficient and Versatile Brain Representation Network
Abstract: Research in decoding visual information from the brain, particularly through
the non-invasive fMRI method, is rapidly progressing. The challenge arises from
the limited data availability and the low signal-to-noise ratio of fMRI
si... | Computer Vision |
What field is the article from? | Title: Guardians of Trust: Navigating Data Security in AIOps through Vendor Partnerships
Abstract: Artificial Intelligence for IT Operations (AIOps) is a rapidly growing field
that applies artificial intelligence and machine learning to automate and
optimize IT operations. AIOps vendors provide services that ingest end... | Cryptography and Security |
What field is the article from? | Title: Unlearn What You Want to Forget: Efficient Unlearning for LLMs
Abstract: Large language models (LLMs) have achieved significant progress from
pre-training on and memorizing a wide range of textual data, however, this
process might suffer from privacy issues and violations of data protection
regulations. As a res... | Computational Linguistics |
What field is the article from? | Title: FedTruth: Byzantine-Robust and Backdoor-Resilient Federated Learning Framework
Abstract: Federated Learning (FL) enables collaborative machine learning model training
across multiple parties without sharing raw data. However, FL's distributed
nature allows malicious clients to impact model training through Byzan... | Machine Learning |
What field is the article from? | Title: LLM A*: Human in the Loop Large Language Models Enabled A* Search for Robotics
Abstract: This research focuses on how Large Language Models (LLMs) can help with path
planning for mobile embodied agents such as robots, in a human-in-the-loop and
interactive manner. A novel framework named LLM A*, aims to leverage... | Robotics |
What field is the article from? | Title: Unsupervised Graph Attention Autoencoder for Attributed Networks using K-means Loss
Abstract: Several natural phenomena and complex systems are often represented as
networks. Discovering their community structure is a fundamental task for
understanding these networks. Many algorithms have been proposed, but rece... | Computational Linguistics |
What field is the article from? | Title: Selectively Sharing Experiences Improves Multi-Agent Reinforcement Learning
Abstract: We present a novel multi-agent RL approach, Selective Multi-Agent Prioritized
Experience Relay, in which agents share with other agents a limited number of
transitions they observe during training. The intuition behind this is ... | Machine Learning |
What field is the article from? | Title: Unify Change Point Detection and Segment Classification in a Regression Task for Transportation Mode Identification
Abstract: Identifying travelers' transportation modes is important in transportation
science and location-based services. It's appealing for researchers to leverage
GPS trajectory data to infer tra... | Computer Vision |
What field is the article from? | Title: PotholeGuard: A Pothole Detection Approach by Point Cloud Semantic Segmentation
Abstract: Pothole detection is crucial for road safety and maintenance, traditionally
relying on 2D image segmentation. However, existing 3D Semantic Pothole
Segmentation research often overlooks point cloud sparsity, leading to
subo... | Computer Vision |
What field is the article from? | Title: Augmentation is AUtO-Net: Augmentation-Driven Contrastive Multiview Learning for Medical Image Segmentation
Abstract: The utilisation of deep learning segmentation algorithms that learn complex
organs and tissue patterns and extract essential regions of interest from the
noisy background to improve the visual ab... | Computer Vision |
What field is the article from? | Title: Probabilistic Copyright Protection Can Fail for Text-to-Image Generative Models
Abstract: The booming use of text-to-image generative models has raised concerns about
their high risk of producing copyright-infringing content. While probabilistic
copyright protection methods provide a probabilistic guarantee agai... | Cryptography and Security |
What field is the article from? | Title: Comprehensive Evaluation and Insights into the Use of Deep Neural Networks to Detect and Quantify Lymphoma Lesions in PET/CT Images
Abstract: This study performs comprehensive evaluation of four neural network
architectures (UNet, SegResNet, DynUNet, and SwinUNETR) for lymphoma lesion
segmentation from PET/CT im... | Computer Vision |
What field is the article from? | Title: Multiscale Vision Transformer With Deep Clustering-Guided Refinement for Weakly Supervised Object Localization
Abstract: This work addresses the task of weakly-supervised object localization. The
goal is to learn object localization using only image-level class labels, which
are much easier to obtain compared to... | Computer Vision |
What field is the article from? | Title: Finetuning an LLM on Contextual Knowledge of Classics for Q&A
Abstract: The open-source publishing of large language models (LLMs) has created many
possibilities for how anyone who understands language and has access to a
computer can interact with significant tools of artificial intelligence,
particularly in th... | Computational Linguistics |
What field is the article from? | Title: How Well Do Large Language Models Truly Ground?
Abstract: Reliance on the inherent knowledge of Large Language Models (LLMs) can cause
issues such as hallucinations, lack of control, and difficulties in integrating
variable knowledge. To mitigate this, LLMs can be probed to generate responses
by grounding on ext... | Computational Linguistics |
What field is the article from? | Title: Image and Data Mining in Reticular Chemistry Using GPT-4V
Abstract: The integration of artificial intelligence into scientific research has
reached a new pinnacle with GPT-4V, a large language model featuring enhanced
vision capabilities, accessible through ChatGPT or an API. This study
demonstrates the remarkab... | Artificial Intelligence |
What field is the article from? | Title: Rethinking Urban Mobility Prediction: A Super-Multivariate Time Series Forecasting Approach
Abstract: Long-term urban mobility predictions play a crucial role in the effective
management of urban facilities and services. Conventionally, urban mobility
data has been structured as spatiotemporal videos, treating l... | Machine Learning |
What field is the article from? | Title: Never Lost in the Middle: Improving Large Language Models via Attention Strengthening Question Answering
Abstract: While large language models (LLMs) are equipped with longer text input
capabilities than before, they are struggling to seek correct information in
long contexts. The "lost in the middle" problem ch... | Computational Linguistics |
What field is the article from? | Title: ViVid-1-to-3: Novel View Synthesis with Video Diffusion Models
Abstract: Generating novel views of an object from a single image is a challenging
task. It requires an understanding of the underlying 3D structure of the object
from an image and rendering high-quality, spatially consistent new views. While
recent ... | Computer Vision |
What field is the article from? | Title: A Communication Theory Perspective on Prompting Engineering Methods for Large Language Models
Abstract: The springing up of Large Language Models (LLMs) has shifted the community
from single-task-orientated natural language processing (NLP) research to a
holistic end-to-end multi-task learning paradigm. Along th... | Computational Linguistics |
What field is the article from? | Title: A Comprehensive Literature Review on Sweet Orange Leaf Diseases
Abstract: Sweet orange leaf diseases are significant to agricultural productivity. Leaf
diseases impact fruit quality in the citrus industry. The apparition of machine
learning makes the development of disease finder. Early detection and diagnosis
a... | Computer Vision |
What field is the article from? | Title: SPHINX: The Joint Mixing of Weights, Tasks, and Visual Embeddings for Multi-modal Large Language Models
Abstract: We present SPHINX, a versatile multi-modal large language model (MLLM) with a
joint mixing of model weights, tuning tasks, and visual embeddings. First, for
stronger vision-language alignment, we unf... | Computer Vision |
What field is the article from? | Title: Adaptive Uncertainty Estimation via High-Dimensional Testing on Latent Representations
Abstract: Uncertainty estimation aims to evaluate the confidence of a trained deep
neural network. However, existing uncertainty estimation approaches rely on
low-dimensional distributional assumptions and thus suffer from the... | Machine Learning |
What field is the article from? | Title: CRAB: Assessing the Strength of Causal Relationships Between Real-world Events
Abstract: Understanding narratives requires reasoning about the cause-and-effect
relationships between events mentioned in the text. While existing foundation
models yield impressive results in many NLP tasks requiring reasoning, it i... | Computational Linguistics |
What field is the article from? | Title: Intrinsic Harmonization for Illumination-Aware Compositing
Abstract: Despite significant advancements in network-based image harmonization
techniques, there still exists a domain disparity between typical training
pairs and real-world composites encountered during inference. Most existing
methods are trained to ... | Computer Vision |
What field is the article from? | Title: LRM: Large Reconstruction Model for Single Image to 3D
Abstract: We propose the first Large Reconstruction Model (LRM) that predicts the 3D
model of an object from a single input image within just 5 seconds. In contrast
to many previous methods that are trained on small-scale datasets such as
ShapeNet in a categ... | Computer Vision |
What field is the article from? | Title: From Images to Connections: Can DQN with GNNs learn the Strategic Game of Hex?
Abstract: The gameplay of strategic board games such as chess, Go and Hex is often
characterized by combinatorial, relational structures -- capturing distinct
interactions and non-local patterns -- and not just images. Nonetheless, mo... | Machine Learning |
What field is the article from? | Title: DALE: Generative Data Augmentation for Low-Resource Legal NLP
Abstract: We present DALE, a novel and effective generative Data Augmentation framework
for low-resource LEgal NLP. DALE addresses the challenges existing frameworks
pose in generating effective data augmentations of legal documents - legal
language, ... | Computational Linguistics |
What field is the article from? | Title: Latent Space Explorer: Visual Analytics for Multimodal Latent Space Exploration
Abstract: Machine learning models built on training data with multiple modalities can
reveal new insights that are not accessible through unimodal datasets. For
example, cardiac magnetic resonance images (MRIs) and electrocardiograms... | Machine Learning |
What field is the article from? | Title: Vision-based Learning for Drones: A Survey
Abstract: Drones as advanced cyber-physical systems are undergoing a transformative
shift with the advent of vision-based learning, a field that is rapidly gaining
prominence due to its profound impact on drone autonomy and functionality.
Different from existing task-sp... | Robotics |
What field is the article from? | Title: Global $\mathcal{L}^2$ minimization with certainty via geometrically adapted gradient descent in Deep Learning
Abstract: We consider the gradient descent flow widely used for the minimization of the
$\mathcal{L}^2$ cost function in Deep Learning networks, and introduce two
modified versions; one adapted for the ... | Machine Learning |
What field is the article from? | Title: PipeOptim: Ensuring Effective 1F1B Schedule with Optimizer-Dependent Weight Prediction
Abstract: Asynchronous pipeline model parallelism with a "1F1B" (one forward, one
backward) schedule generates little bubble overhead and always provides quite a
high throughput. However, the "1F1B" schedule inevitably leads t... | Machine Learning |
What field is the article from? | Title: Unveiling the Power of Audio-Visual Early Fusion Transformers with Dense Interactions through Masked Modeling
Abstract: Humans possess a remarkable ability to integrate auditory and visual
information, enabling a deeper understanding of the surrounding environment.
This early fusion of audio and visual cues, dem... | Computer Vision |
What field is the article from? | Title: Efficient Machine Learning Ensemble Methods for Detecting Gravitational Wave Glitches in LIGO Time Series
Abstract: The phenomenon of Gravitational Wave (GW) analysis has grown in popularity as
technology has advanced and the process of observing gravitational waves has
become more precise. Although the sensitiv... | Machine Learning |
What field is the article from? | Title: Tied-Lora: Enhacing parameter efficiency of LoRA with weight tying
Abstract: We propose Tied-LoRA, a simple paradigm utilizes weight tying and selective
training to further increase parameter efficiency of the Low-rank adaptation
(LoRA) method. Our investigations include all feasible combinations parameter
train... | Computational Linguistics |
What field is the article from? | Title: Transformer Based Model for Predicting Rapid Impact Compaction Outcomes: A Case Study of Utapao International Airport
Abstract: This paper introduces a novel deep learning approach to predict the
engineering properties of the ground improved by Rapid Impact Compaction (RIC),
which is a ground improvement techniq... | Machine Learning |
What field is the article from? | Title: Can Foundation Models Watch, Talk and Guide You Step by Step to Make a Cake?
Abstract: Despite tremendous advances in AI, it remains a significant challenge to
develop interactive task guidance systems that can offer situated, personalized
guidance and assist humans in various tasks. These systems need to have a... | Artificial Intelligence |
What field is the article from? | Title: Multiview Aerial Visual Recognition (MAVREC): Can Multi-view Improve Aerial Visual Perception?
Abstract: Despite the commercial abundance of UAVs, aerial data acquisition remains
challenging, and the existing Asia and North America-centric open-source UAV
datasets are small-scale or low-resolution and lack diver... | Computer Vision |
What field is the article from? | Title: Synthetic Imitation Edit Feedback for Factual Alignment in Clinical Summarization
Abstract: Large Language Models (LLMs) like the GPT and LLaMA families have
demonstrated exceptional capabilities in capturing and condensing critical
contextual information and achieving state-of-the-art performance in the
summari... | Computational Linguistics |
What field is the article from? | Title: Chain of Empathy: Enhancing Empathetic Response of Large Language Models Based on Psychotherapy Models
Abstract: We present a novel method, the Chain of Empathy (CoE) prompting, that
utilizes insights from psychotherapy to induce Large Language Models (LLMs) to
reason about human emotional states. This method is... | Computational Linguistics |
End of preview. Expand in Data Studio
README.md exists but content is empty.
- Downloads last month
- 19