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What field is the article from? | Title: FlowMur: A Stealthy and Practical Audio Backdoor Attack with Limited Knowledge
Abstract: Speech recognition systems driven by DNNs have revolutionized human-computer
interaction through voice interfaces, which significantly facilitate our daily
lives. However, the growing popularity of these systems also raises ... | Cryptography and Security |
What field is the article from? | Title: A General Neural Causal Model for Interactive Recommendation
Abstract: Survivor bias in observational data leads the optimization of recommender
systems towards local optima. Currently most solutions re-mines existing
human-system collaboration patterns to maximize longer-term satisfaction by
reinforcement learn... | Machine Learning |
What field is the article from? | Title: An Investigation of Darwiche and Pearl's Postulates for Iterated Belief Update
Abstract: Belief revision and update, two significant types of belief change, both
focus on how an agent modify her beliefs in presence of new information. The
most striking difference between them is that the former studies the chang... | Artificial Intelligence |
What field is the article from? | Title: Natural Language Interfaces for Tabular Data Querying and Visualization: A Survey
Abstract: The emergence of natural language processing has revolutionized the way users
interact with tabular data, enabling a shift from traditional query languages
and manual plotting to more intuitive, language-based interfaces.... | Computational Linguistics |
What field is the article from? | Title: Stock Movement and Volatility Prediction from Tweets, Macroeconomic Factors and Historical Prices
Abstract: Predicting stock market is vital for investors and policymakers, acting as a
barometer of the economic health. We leverage social media data, a potent
source of public sentiment, in tandem with macroeconom... | Artificial Intelligence |
What field is the article from? | Title: Responsible Emergent Multi-Agent Behavior
Abstract: Responsible AI has risen to the forefront of the AI research community. As
neural network-based learning algorithms continue to permeate real-world
applications, the field of Responsible AI has played a large role in ensuring
that such systems maintain a high-l... | Artificial Intelligence |
What field is the article from? | Title: Explaining black boxes with a SMILE: Statistical Model-agnostic Interpretability with Local Explanations
Abstract: Machine learning is currently undergoing an explosion in capability,
popularity, and sophistication. However, one of the major barriers to
widespread acceptance of machine learning (ML) is trustwort... | Machine Learning |
What field is the article from? | Title: SparseByteNN: A Novel Mobile Inference Acceleration Framework Based on Fine-Grained Group Sparsity
Abstract: To address the challenge of increasing network size, researchers have
developed sparse models through network pruning. However, maintaining model
accuracy while achieving significant speedups on general c... | Artificial Intelligence |
What field is the article from? | Title: A Survey on Detection of LLMs-Generated Content
Abstract: The burgeoning capabilities of advanced large language models (LLMs) such as
ChatGPT have led to an increase in synthetic content generation with
implications across a variety of sectors, including media, cybersecurity,
public discourse, and education. As... | Computational Linguistics |
What field is the article from? | Title: Learning to Act without Actions
Abstract: Pre-training large models on vast amounts of web data has proven to be an
effective approach for obtaining powerful, general models in several domains,
including language and vision. However, this paradigm has not yet taken hold in
deep reinforcement learning (RL). This ... | Machine Learning |
What field is the article from? | Title: GLaMM: Pixel Grounding Large Multimodal Model
Abstract: Large Multimodal Models (LMMs) extend Large Language Models to the vision
domain. Initial efforts towards LMMs used holistic images and text prompts to
generate ungrounded textual responses. Very recently, region-level LMMs have
been used to generate visual... | Computer Vision |
What field is the article from? | Title: Peer attention enhances student learning
Abstract: Human visual attention is susceptible to social influences. In education,
peer effects impact student learning, but their precise role in modulating
attention remains unclear. Our experiment (N=311) demonstrates that displaying
peer visual attention regions when... | Human-Computer Interaction |
What field is the article from? | Title: Plagiarism and AI Assistance Misuse in Web Programming: Unfair Benefits and Characteristics
Abstract: In programming education, plagiarism and misuse of artificial intelligence
(AI) assistance are emerging issues. However, not many relevant studies are
focused on web programming. We plan to develop automated too... | Artificial Intelligence |
What field is the article from? | Title: Neural Collage Transfer: Artistic Reconstruction via Material Manipulation
Abstract: Collage is a creative art form that uses diverse material scraps as a base
unit to compose a single image. Although pixel-wise generation techniques can
reproduce a target image in collage style, it is not a suitable method due ... | Computer Vision |
What field is the article from? | Title: Identifying Reasons for Bias: An Argumentation-Based Approach
Abstract: As algorithmic decision-making systems become more prevalent in society,
ensuring the fairness of these systems is becoming increasingly important.
Whilst there has been substantial research in building fair algorithmic
decision-making syste... | Machine Learning |
What field is the article from? | Title: Breathing Life into Faces: Speech-driven 3D Facial Animation with Natural Head Pose and Detailed Shape
Abstract: The creation of lifelike speech-driven 3D facial animation requires a natural
and precise synchronization between audio input and facial expressions.
However, existing works still fail to render shape... | Computer Vision |
What field is the article from? | Title: Autonomous 3D Exploration in Large-Scale Environments with Dynamic Obstacles
Abstract: Exploration in dynamic and uncertain real-world environments is an open
problem in robotics and constitutes a foundational capability of autonomous
systems operating in most of the real world. While 3D exploration planning has... | Robotics |
What field is the article from? | Title: A GAN Approach for Node Embedding in Heterogeneous Graphs Using Subgraph Sampling
Abstract: Our research addresses class imbalance issues in heterogeneous graphs using
graph neural networks (GNNs). We propose a novel method combining the strengths
of Generative Adversarial Networks (GANs) with GNNs, creating syn... | Machine Learning |
What field is the article from? | Title: Moral Foundations of Large Language Models
Abstract: Moral foundations theory (MFT) is a psychological assessment tool that
decomposes human moral reasoning into five factors, including care/harm,
liberty/oppression, and sanctity/degradation (Graham et al., 2009). People vary
in the weight they place on these di... | Artificial Intelligence |
What field is the article from? | Title: Decentralized Personalized Online Federated Learning
Abstract: Vanilla federated learning does not support learning in an online
environment, learning a personalized model on each client, and learning in a
decentralized setting. There are existing methods extending federated learning
in each of the three aspects... | Machine Learning |
What field is the article from? | Title: Large Language Models for Autonomous Driving: Real-World Experiments
Abstract: Autonomous driving systems are increasingly popular in today's technological
landscape, where vehicles with partial automation have already been widely
available on the market, and the full automation era with ``driverless''
capabilit... | Artificial Intelligence |
What field is the article from? | Title: The Rise of Creative Machines: Exploring the Impact of Generative AI
Abstract: This study looks at how generative artificial intelligence (AI) can
revolutionize marketing, product development, and research. It discusses the
latest developments in the field, easy-to-use resources, and moral and social
hazards. In... | Artificial Intelligence |
What field is the article from? | Title: NLQxform: A Language Model-based Question to SPARQL Transformer
Abstract: In recent years, scholarly data has grown dramatically in terms of both scale
and complexity. It becomes increasingly challenging to retrieve information
from scholarly knowledge graphs that include large-scale heterogeneous
relationships,... | Computational Linguistics |
What field is the article from? | Title: ABIGX: A Unified Framework for eXplainable Fault Detection and Classification
Abstract: For explainable fault detection and classification (FDC), this paper proposes
a unified framework, ABIGX (Adversarial fault reconstruction-Based Integrated
Gradient eXplanation). ABIGX is derived from the essentials of previo... | Machine Learning |
What field is the article from? | Title: The Cost of Compression: Investigating the Impact of Compression on Parametric Knowledge in Language Models
Abstract: Compressing large language models (LLMs), often consisting of billions of
parameters, provides faster inference, smaller memory footprints, and enables
local deployment. Two standard compression ... | Computational Linguistics |
What field is the article from? | Title: STOW: Discrete-Frame Segmentation and Tracking of Unseen Objects for Warehouse Picking Robots
Abstract: Segmentation and tracking of unseen object instances in discrete frames pose
a significant challenge in dynamic industrial robotic contexts, such as
distribution warehouses. Here, robots must handle object rea... | Robotics |
What field is the article from? | Title: Hierarchical Framework for Interpretable and Probabilistic Model-Based Safe Reinforcement Learning
Abstract: The difficulty of identifying the physical model of complex systems has led
to exploring methods that do not rely on such complex modeling of the systems.
Deep reinforcement learning has been the pioneer ... | Artificial Intelligence |
What field is the article from? | Title: DTL: Disentangled Transfer Learning for Visual Recognition
Abstract: When pre-trained models become rapidly larger, the cost of fine-tuning on
downstream tasks steadily increases, too. To economically fine-tune these
models, parameter-efficient transfer learning (PETL) is proposed, which only
tunes a tiny subset... | Computer Vision |
What field is the article from? | Title: LSA64: An Argentinian Sign Language Dataset
Abstract: Automatic sign language recognition is a research area that encompasses
human-computer interaction, computer vision and machine learning. Robust
automatic recognition of sign language could assist in the translation process
and the integration of hearing-impa... | Computer Vision |
What field is the article from? | Title: Nominality Score Conditioned Time Series Anomaly Detection by Point/Sequential Reconstruction
Abstract: Time series anomaly detection is challenging due to the complexity and
variety of patterns that can occur. One major difficulty arises from modeling
time-dependent relationships to find contextual anomalies wh... | Machine Learning |
What field is the article from? | Title: Promoting Counterfactual Robustness through Diversity
Abstract: Counterfactual explanations shed light on the decisions of black-box models
by explaining how an input can be altered to obtain a favourable decision from
the model (e.g., when a loan application has been rejected). However, as noted
recently, count... | Machine Learning |
What field is the article from? | Title: Differentiable Visual Computing for Inverse Problems and Machine Learning
Abstract: Originally designed for applications in computer graphics, visual computing
(VC) methods synthesize information about physical and virtual worlds, using
prescribed algorithms optimized for spatial computing. VC is used to analyze... | Machine Learning |
What field is the article from? | Title: PrivateLoRA For Efficient Privacy Preserving LLM
Abstract: End users face a choice between privacy and efficiency in current Large
Language Model (LLM) service paradigms. In cloud-based paradigms, users are
forced to compromise data locality for generation quality and processing speed.
Conversely, edge device pa... | Artificial Intelligence |
What field is the article from? | Title: LLM as an Art Director (LaDi): Using LLMs to improve Text-to-Media Generators
Abstract: Recent advancements in text-to-image generation have revolutionized numerous
fields, including art and cinema, by automating the generation of high-quality,
context-aware images and video. However, the utility of these techno... | Computational Linguistics |
What field is the article from? | Title: Machine Learning For An Explainable Cost Prediction of Medical Insurance
Abstract: Predictive modeling in healthcare continues to be an active actuarial
research topic as more insurance companies aim to maximize the potential of
Machine Learning approaches to increase their productivity and efficiency. In
this p... | Machine Learning |
What field is the article from? | Title: Orca 2: Teaching Small Language Models How to Reason
Abstract: Orca 1 learns from rich signals, such as explanation traces, allowing it to
outperform conventional instruction-tuned models on benchmarks like BigBench
Hard and AGIEval. In Orca 2, we continue exploring how improved training
signals can enhance smal... | Artificial Intelligence |
What field is the article from? | Title: MELA: Multilingual Evaluation of Linguistic Acceptability
Abstract: Recent benchmarks for Large Language Models (LLMs) have mostly focused on
application-driven tasks such as complex reasoning and code generation, and
this has led to a scarcity in purely linguistic evaluation of LLMs. Against
this background, we... | Computational Linguistics |
What field is the article from? | Title: Music Recommendation on Spotify using Deep Learning
Abstract: Hosting about 50 million songs and 4 billion playlists, there is an enormous
amount of data generated at Spotify every single day - upwards of 600 gigabytes
of data (harvard.edu). Since the algorithms that Spotify uses in recommendation
systems is pro... | Information Retrieval |
What field is the article from? | Title: Beyond Words: A Mathematical Framework for Interpreting Large Language Models
Abstract: Large language models (LLMs) are powerful AI tools that can generate and
comprehend natural language text and other complex information. However, the
field lacks a mathematical framework to systematically describe, compare an... | Machine Learning |
What field is the article from? | Title: Artificial intelligence and the limits of the humanities
Abstract: The complexity of cultures in the modern world is now beyond human
comprehension. Cognitive sciences cast doubts on the traditional explanations
based on mental models. The core subjects in humanities may lose their
importance. Humanities have to... | Artificial Intelligence |
What field is the article from? | Title: Meta Prompting for AGI Systems
Abstract: This paper presents an in-depth exploration of Meta Prompting, a novel
technique that revolutionizes the way large language models (LLMs), multi-modal
foundation models, and AI systems approach problem-solving and data
interpretation. Meta Prompting, rooted in type theory... | Artificial Intelligence |
What field is the article from? | Title: Unleashing the Potential of Large Language Model: Zero-shot VQA for Flood Disaster Scenario
Abstract: Visual question answering (VQA) is a fundamental and essential AI task, and
VQA-based disaster scenario understanding is a hot research topic. For
instance, we can ask questions about a disaster image by the VQA... | Computer Vision |
What field is the article from? | Title: Forms of Understanding of XAI-Explanations
Abstract: Explainability has become an important topic in computer science and
artificial intelligence, leading to a subfield called Explainable Artificial
Intelligence (XAI). The goal of providing or seeking explanations is to achieve
(better) 'understanding' on the pa... | Artificial Intelligence |
What field is the article from? | Title: Predicting Agricultural Commodities Prices with Machine Learning: A Review of Current Research
Abstract: Agricultural price prediction is crucial for farmers, policymakers, and other
stakeholders in the agricultural sector. However, it is a challenging task due
to the complex and dynamic nature of agricultural m... | Artificial Intelligence |
What field is the article from? | Title: Common (good) practices measuring trust in HRI
Abstract: Trust in robots is widely believed to be imperative for the adoption of
robots into people's daily lives. It is, therefore, understandable that the
literature of the last few decades focuses on measuring how much people trust
robots -- and more generally, ... | Robotics |
What field is the article from? | Title: KEN: Kernel Extensions using Natural Language
Abstract: The ability to modify and extend an operating system is an important feature
for improving a system's security, reliability, and performance. The extended
Berkeley Packet Filters (eBPF) ecosystem has emerged as the standard mechanism
for extending the Linux... | Artificial Intelligence |
What field is the article from? | Title: Federated Knowledge Graph Completion via Latent Embedding Sharing and Tensor Factorization
Abstract: Knowledge graphs (KGs), which consist of triples, are inherently incomplete
and always require completion procedure to predict missing triples. In
real-world scenarios, KGs are distributed across clients, complic... | Machine Learning |
What field is the article from? | Title: Multi-scale Diffusion Denoised Smoothing
Abstract: Along with recent diffusion models, randomized smoothing has become one of a
few tangible approaches that offers adversarial robustness to models at scale,
e.g., those of large pre-trained models. Specifically, one can perform
randomized smoothing on any classif... | Machine Learning |
What field is the article from? | Title: Multimodal Machine Unlearning
Abstract: Machine Unlearning is the process of removing specific training data samples
and their corresponding effects from an already trained model. It has
significant practical benefits, such as purging private, inaccurate, or
outdated information from trained models without the n... | Artificial Intelligence |
What field is the article from? | Title: On the Fairness ROAD: Robust Optimization for Adversarial Debiasing
Abstract: In the field of algorithmic fairness, significant attention has been put on
group fairness criteria, such as Demographic Parity and Equalized Odds.
Nevertheless, these objectives, measured as global averages, have raised
concerns about... | Machine Learning |
What field is the article from? | Title: LLVMs4Protest: Harnessing the Power of Large Language and Vision Models for Deciphering Protests in the News
Abstract: Large language and vision models have transformed how social movements
scholars identify protest and extract key protest attributes from multi-modal
data such as texts, images, and videos. This ... | Computer Vision |
What field is the article from? | Title: The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning
Abstract: The alignment tuning process of large language models (LLMs) typically
involves instruction learning through supervised fine-tuning (SFT) and
preference tuning via reinforcement learning from human feedback (RLHF). A
recent ... | Computational Linguistics |
What field is the article from? | Title: NestE: Modeling Nested Relational Structures for Knowledge Graph Reasoning
Abstract: Reasoning with knowledge graphs (KGs) has primarily focused on triple-shaped
facts. Recent advancements have been explored to enhance the semantics of these
facts by incorporating more potent representations, such as hyper-relat... | Artificial Intelligence |
What field is the article from? | Title: Causality is all you need
Abstract: In the fundamental statistics course, students are taught to remember the
well-known saying: "Correlation is not Causation". Till now, statistics (i.e.,
correlation) have developed various successful frameworks, such as Transformer
and Pre-training large-scale models, which ha... | Artificial Intelligence |
What field is the article from? | Title: Enhancing IoT Security via Automatic Network Traffic Analysis: The Transition from Machine Learning to Deep Learning
Abstract: This work provides a comparative analysis illustrating how Deep Learning (DL)
surpasses Machine Learning (ML) in addressing tasks within Internet of Things
(IoT), such as attack classifi... | Cryptography and Security |
What field is the article from? | Title: A Framework to Assess (Dis)agreement Among Diverse Rater Groups
Abstract: Recent advancements in conversational AI have created an urgent need for
safety guardrails that prevent users from being exposed to offensive and
dangerous content. Much of this work relies on human ratings and feedback, but
does not accou... | Computational Linguistics |
What field is the article from? | Title: Data-driven building energy efficiency prediction based on envelope heat losses using physics-informed neural networks
Abstract: The analytical prediction of building energy performance in residential
buildings based on the heat losses of its individual envelope components is a
challenging task. It is worth noti... | Machine Learning |
What field is the article from? | Title: Synthetic Data as Validation
Abstract: This study leverages synthetic data as a validation set to reduce overfitting
and ease the selection of the best model in AI development. While synthetic
data have been used for augmenting the training set, we find that synthetic
data can also significantly diversify the va... | Computer Vision |
What field is the article from? | Title: Challenges of Large Language Models for Mental Health Counseling
Abstract: The global mental health crisis is looming with a rapid increase in mental
disorders, limited resources, and the social stigma of seeking treatment. As
the field of artificial intelligence (AI) has witnessed significant
advancements in re... | Computational Linguistics |
What field is the article from? | Title: A method for recovery of multidimensional time series based on the detection of behavioral patterns and the use of autoencoders
Abstract: This article presents a method for recovering missing values in
multidimensional time series. The method combines neural network technologies
and an algorithm for searching sn... | Artificial Intelligence |
What field is the article from? | Title: Plug-and-Play Policy Planner for Large Language Model Powered Dialogue Agents
Abstract: Proactive dialogues serve as a practical yet challenging dialogue problem in
the era of large language models (LLMs), where the dialogue policy planning is
the key to improving the proactivity of LLMs. Most existing studies e... | Computational Linguistics |
What field is the article from? | Title: How to Configure Good In-Context Sequence for Visual Question Answering
Abstract: Inspired by the success of Large Language Models in dealing with new tasks
via In-Context Learning (ICL) in NLP, researchers have also developed Large
Vision-Language Models (LVLMs) with ICL capabilities. However, when
implementing... | Computer Vision |
What field is the article from? | Title: M2T2: Multi-Task Masked Transformer for Object-centric Pick and Place
Abstract: With the advent of large language models and large-scale robotic datasets,
there has been tremendous progress in high-level decision-making for object
manipulation. These generic models are able to interpret complex tasks using
langu... | Robotics |
What field is the article from? | Title: AI Agent as Urban Planner: Steering Stakeholder Dynamics in Urban Planning via Consensus-based Multi-Agent Reinforcement Learning
Abstract: In urban planning, land use readjustment plays a pivotal role in aligning
land use configurations with the current demands for sustainable urban
development. However, presen... | Artificial Intelligence |
What field is the article from? | Title: Data Acquisition: A New Frontier in Data-centric AI
Abstract: As Machine Learning (ML) systems continue to grow, the demand for relevant
and comprehensive datasets becomes imperative. There is limited study on the
challenges of data acquisition due to ad-hoc processes and lack of consistent
methodologies. We fir... | Artificial Intelligence |
What field is the article from? | Title: SENetV2: Aggregated dense layer for channelwise and global representations
Abstract: Convolutional Neural Networks (CNNs) have revolutionized image classification
by extracting spatial features and enabling state-of-the-art accuracy in
vision-based tasks. The squeeze and excitation network proposed module gather... | Computer Vision |
What field is the article from? | Title: Survey on Foundation Models for Prognostics and Health Management in Industrial Cyber-Physical Systems
Abstract: Industrial Cyber-Physical Systems (ICPS) integrate the disciplines of
computer science, communication technology, and engineering, and have emerged
as integral components of contemporary manufacturing... | Artificial Intelligence |
What field is the article from? | Title: Decoding Logic Errors: A Comparative Study on Bug Detection by Students and Large Language Models
Abstract: Identifying and resolving logic errors can be one of the most frustrating
challenges for novices programmers. Unlike syntax errors, for which a compiler
or interpreter can issue a message, logic errors can... | Human-Computer Interaction |
What field is the article from? | Title: Imitating Shortest Paths in Simulation Enables Effective Navigation and Manipulation in the Real World
Abstract: Reinforcement learning (RL) with dense rewards and imitation learning (IL)
with human-generated trajectories are the most widely used approaches for
training modern embodied agents. RL requires extens... | Robotics |
What field is the article from? | Title: Guarding Barlow Twins Against Overfitting with Mixed Samples
Abstract: Self-supervised Learning (SSL) aims to learn transferable feature
representations for downstream applications without relying on labeled data.
The Barlow Twins algorithm, renowned for its widespread adoption and
straightforward implementation... | Computer Vision |
What field is the article from? | Title: Multi-Scale and Multi-Modal Contrastive Learning Network for Biomedical Time Series
Abstract: Multi-modal biomedical time series (MBTS) data offers a holistic view of the
physiological state, holding significant importance in various bio-medical
applications. Owing to inherent noise and distribution gaps across ... | Machine Learning |
What field is the article from? | Title: LLaVA-Interactive: An All-in-One Demo for Image Chat, Segmentation, Generation and Editing
Abstract: LLaVA-Interactive is a research prototype for multimodal human-AI
interaction. The system can have multi-turn dialogues with human users by
taking multimodal user inputs and generating multimodal responses. Impor... | Computer Vision |
What field is the article from? | Title: Identifying Spurious Correlations using Counterfactual Alignment
Abstract: Models driven by spurious correlations often yield poor generalization
performance. We propose the counterfactual alignment method to detect and
explore spurious correlations of black box classifiers. Counterfactual images
generated with ... | Computer Vision |
What field is the article from? | Title: FOCAL: A Cost-Aware Video Dataset for Active Learning
Abstract: In this paper, we introduce the FOCAL (Ford-OLIVES Collaboration on Active
Learning) dataset which enables the study of the impact of annotation-cost
within a video active learning setting. Annotation-cost refers to the time it
takes an annotator to... | Computer Vision |
What field is the article from? | Title: Conformal Prediction in Multi-User Settings: An Evaluation
Abstract: Typically, machine learning models are trained and evaluated without making
any distinction between users (e.g, using traditional hold-out and
cross-validation). However, this produces inaccurate performance metrics
estimates in multi-user sett... | Machine Learning |
What field is the article from? | Title: BioLORD-2023: Semantic Textual Representations Fusing LLM and Clinical Knowledge Graph Insights
Abstract: In this study, we investigate the potential of Large Language Models to
complement biomedical knowledge graphs in the training of semantic models for
the biomedical and clinical domains. Drawing on the wealt... | Computational Linguistics |
What field is the article from? | Title: Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision
Abstract: Large language models (LLMs) have demonstrated remarkable capabilities in
various tasks. However, their suitability for domain-specific tasks, is limited
due to their immense scale at deplo... | Computational Linguistics |
What field is the article from? | Title: Generating High-Resolution Regional Precipitation Using Conditional Diffusion Model
Abstract: Climate downscaling is a crucial technique within climate research, serving
to project low-resolution (LR) climate data to higher resolutions (HR).
Previous research has demonstrated the effectiveness of deep learning f... | Machine Learning |
What field is the article from? | Title: HADES: Fast Singularity Detection with Local Measure Comparison
Abstract: We introduce Hades, an unsupervised algorithm to detect singularities in
data. This algorithm employs a kernel goodness-of-fit test, and as a
consequence it is much faster and far more scaleable than the existing
topology-based alternative... | Machine Learning |
What field is the article from? | Title: TrackDiffusion: Multi-object Tracking Data Generation via Diffusion Models
Abstract: Diffusion models have gained prominence in generating data for perception
tasks such as image classification and object detection. However, the potential
in generating high-quality tracking sequences, a crucial aspect in the fie... | Computer Vision |
What field is the article from? | Title: Improving Minority Stress Detection with Emotions
Abstract: Psychological stress detection is an important task for mental healthcare
research, but there has been little prior work investigating the effectiveness
of psychological stress models on minority individuals, who are especially
vulnerable to poor mental... | Computational Linguistics |
What field is the article from? | Title: Learning Decentralized Traffic Signal Controllers with Multi-Agent Graph Reinforcement Learning
Abstract: This paper considers optimal traffic signal control in smart cities, which
has been taken as a complex networked system control problem. Given the
interacting dynamics among traffic lights and road networks,... | Machine Learning |
What field is the article from? | Title: Instruct and Extract: Instruction Tuning for On-Demand Information Extraction
Abstract: Large language models with instruction-following capabilities open the door
to a wider group of users. However, when it comes to information extraction - a
classic task in natural language processing - most task-specific syst... | Computational Linguistics |
What field is the article from? | Title: Drilling Down into the Discourse Structure with LLMs for Long Document Question Answering
Abstract: We address the task of evidence retrieval for long document question
answering, which involves locating relevant paragraphs within a document to
answer a question. We aim to assess the applicability of large langu... | Computational Linguistics |
What field is the article from? | Title: Assessing Fidelity in XAI post-hoc techniques: A Comparative Study with Ground Truth Explanations Datasets
Abstract: The evaluation of the fidelity of eXplainable Artificial Intelligence (XAI)
methods to their underlying models is a challenging task, primarily due to the
absence of a ground truth for explanation... | Computer Vision |
What field is the article from? | Title: The logic of NTQR evaluations of noisy AI agents: Complete postulates and logically consistent error correlations
Abstract: In his "ship of state" allegory (\textit{Republic}, Book VI, 488) Plato poses
a question -- how can a crew of sailors presumed to know little about the art
of navigation recognize the true ... | Artificial Intelligence |
What field is the article from? | Title: Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations
Abstract: We introduce Llama Guard, an LLM-based input-output safeguard model geared
towards Human-AI conversation use cases. Our model incorporates a safety risk
taxonomy, a valuable tool for categorizing a specific set of safety risks fou... | Computational Linguistics |
What field is the article from? | Title: Reinforcement Learning-Based Bionic Reflex Control for Anthropomorphic Robotic Grasping exploiting Domain Randomization
Abstract: Achieving human-level dexterity in robotic grasping remains a challenging
endeavor. Robotic hands frequently encounter slippage and deformation during
object manipulation, issues rare... | Robotics |
What field is the article from? | Title: What a Whole Slide Image Can Tell? Subtype-guided Masked Transformer for Pathological Image Captioning
Abstract: Pathological captioning of Whole Slide Images (WSIs), though is essential in
computer-aided pathological diagnosis, has rarely been studied due to the
limitations in datasets and model training effica... | Computer Vision |
What field is the article from? | Title: Advancing State of the Art in Language Modeling
Abstract: Generalization is arguably the most important goal of statistical language
modeling research. Publicly available benchmarks and papers published with an
open-source code have been critical to advancing the field. However, it is
often very difficult, and s... | Computational Linguistics |
What field is the article from? | Title: Applying Large Language Models to Power Systems: Potential Security Threats
Abstract: Applying large language models (LLMs) to power systems presents a promising
avenue for enhancing decision-making and operational efficiency. However, this
action may also incur potential security threats, which have not been fu... | Artificial Intelligence |
What field is the article from? | Title: OccWorld: Learning a 3D Occupancy World Model for Autonomous Driving
Abstract: Understanding how the 3D scene evolves is vital for making decisions in
autonomous driving. Most existing methods achieve this by predicting the
movements of object boxes, which cannot capture more fine-grained scene
information. In t... | Computer Vision |
What field is the article from? | Title: METAL: Metamorphic Testing Framework for Analyzing Large-Language Model Qualities
Abstract: Large-Language Models (LLMs) have shifted the paradigm of natural language
data processing. However, their black-boxed and probabilistic characteristics
can lead to potential risks in the quality of outputs in diverse LLM... | Software Engineering |
What field is the article from? | Title: Calibrated Adaptive Teacher for Domain Adaptive Intelligent Fault Diagnosis
Abstract: Intelligent Fault Diagnosis (IFD) based on deep learning has proven to be an
effective and flexible solution, attracting extensive research. Deep neural
networks can learn rich representations from vast amounts of representativ... | Machine Learning |
What field is the article from? | Title: Exploring Popularity Bias in Session-based Recommendation
Abstract: Existing work has revealed that large-scale offline evaluation of recommender
systems for user-item interactions is prone to bias caused by the deployed
system itself, as a form of closed loop feedback. Many adopt the
\textit{propensity} concept... | Information Retrieval |
What field is the article from? | Title: Explore, Select, Derive, and Recall: Augmenting LLM with Human-like Memory for Mobile Task Automation
Abstract: The advent of large language models (LLMs) has opened up new opportunities in
the field of mobile task automation. Their superior language understanding and
reasoning capabilities allow users to automa... | Human-Computer Interaction |
What field is the article from? | Title: DiffusionSat: A Generative Foundation Model for Satellite Imagery
Abstract: Diffusion models have achieved state-of-the-art results on many modalities
including images, speech, and video. However, existing models are not tailored
to support remote sensing data, which is widely used in important applications
incl... | Computer Vision |
What field is the article from? | Title: Like an Open Book? Read Neural Network Architecture with Simple Power Analysis on 32-bit Microcontrollers
Abstract: Model extraction is a growing concern for the security of AI systems. For
deep neural network models, the architecture is the most important information
an adversary aims to recover. Being a sequen... | Cryptography and Security |
What field is the article from? | Title: Improving Robustness for Vision Transformer with a Simple Dynamic Scanning Augmentation
Abstract: Vision Transformer (ViT) has demonstrated promising performance in computer
vision tasks, comparable to state-of-the-art neural networks. Yet, this new
type of deep neural network architecture is vulnerable to adver... | Computer Vision |
What field is the article from? | Title: Vignat: Vulnerability identification by learning code semantics via graph attention networks
Abstract: Vulnerability identification is crucial to protect software systems from
attacks for cyber-security. However, huge projects have more than millions of
lines of code, and the complex dependencies make it hard to... | Cryptography and Security |
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