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What field is the article from? | Title: Axiomatic Preference Modeling for Longform Question Answering
Abstract: The remarkable abilities of large language models (LLMs) like GPT-4 partially
stem from post-training processes like Reinforcement Learning from Human
Feedback (RLHF) involving human preferences encoded in a reward model. However,
these rewa... | Artificial Intelligence |
What field is the article from? | Title: Survey on AI Ethics: A Socio-technical Perspective
Abstract: The past decade has observed a great advancement in AI with deep
learning-based models being deployed in diverse scenarios including
safety-critical applications. As these AI systems become deeply embedded in our
societal infrastructure, the repercussi... | Computers and Society |
What field is the article from? | Title: QWID: Quantized Weed Identification Deep neural network
Abstract: In this paper, we present an efficient solution for weed classification in
agriculture. We focus on optimizing model performance at inference while
respecting the constraints of the agricultural domain. We propose a Quantized
Deep Neural Network m... | Computer Vision |
What field is the article from? | Title: Can Reinforcement Learning support policy makers? A preliminary study with Integrated Assessment Models
Abstract: Governments around the world aspire to ground decision-making on evidence.
Many of the foundations of policy making - e.g. sensing patterns that relate to
societal needs, developing evidence-based pr... | Artificial Intelligence |
What field is the article from? | Title: Spatio-Temporal Anomaly Detection with Graph Networks for Data Quality Monitoring of the Hadron Calorimeter
Abstract: The compact muon solenoid (CMS) experiment is a general-purpose detector for
high-energy collision at the large hadron collider (LHC) at CERN. It employs an
online data quality monitoring (DQM) s... | Machine Learning |
What field is the article from? | Title: Word for Person: Zero-shot Composed Person Retrieval
Abstract: Searching for specific person has great security value and social benefits,
and it often involves a combination of visual and textual information.
Conventional person retrieval methods, whether image-based or text-based,
usually fall short in effecti... | Computer Vision |
What field is the article from? | Title: Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations
Abstract: Peer learning is a novel high-level reinforcement learning framework for
agents learning in groups. While standard reinforcement learning trains an
individual agent in trial-and-error fashion, all on its own, pee... | Machine Learning |
What field is the article from? | Title: Implementation of AI Deep Learning Algorithm For Multi-Modal Sentiment Analysis
Abstract: A multi-modal emotion recognition method was established by combining
two-channel convolutional neural network with ring network. This method can
extract emotional information effectively and improve learning efficiency. Th... | Artificial Intelligence |
What field is the article from? | Title: Understanding Practices around Computational News Discovery Tools in the Domain of Science Journalism
Abstract: Science and technology journalists today face challenges in finding
newsworthy leads due to increased workloads, reduced resources, and expanding
scientific publishing ecosystems. Given this context, w... | Human-Computer Interaction |
What field is the article from? | Title: Successor Features for Efficient Multisubject Controlled Text Generation
Abstract: While large language models (LLMs) have achieved impressive performance in
generating fluent and realistic text, controlling the generated text so that it
exhibits properties such as safety, factuality, and non-toxicity remains
ch... | Computational Linguistics |
What field is the article from? | Title: SEA++: Multi-Graph-based High-Order Sensor Alignment for Multivariate Time-Series Unsupervised Domain Adaptation
Abstract: Unsupervised Domain Adaptation (UDA) methods have been successful in reducing
label dependency by minimizing the domain discrepancy between a labeled source
domain and an unlabeled target do... | Machine Learning |
What field is the article from? | Title: Beyond Isolation: Multi-Agent Synergy for Improving Knowledge Graph Construction
Abstract: Knowledge graph construction (KGC) is a multifaceted undertaking involving
the extraction of entities, relations, and events. Traditionally, large
language models (LLMs) have been viewed as solitary task-solving agents in ... | Artificial Intelligence |
What field is the article from? | Title: Navigating Open Set Scenarios for Skeleton-based Action Recognition
Abstract: In real-world scenarios, human actions often fall outside the distribution of
training data, making it crucial for models to recognize known actions and
reject unknown ones. However, using pure skeleton data in such open-set
conditions... | Computer Vision |
What field is the article from? | Title: A Novel Neural Network-Based Federated Learning System for Imbalanced and Non-IID Data
Abstract: With the growth of machine learning techniques, privacy of data of users has
become a major concern. Most of the machine learning algorithms rely heavily on
large amount of data which may be collected from various so... | Machine Learning |
What field is the article from? | Title: Large Trajectory Models are Scalable Motion Predictors and Planners
Abstract: Motion prediction and planning are vital tasks in autonomous driving, and
recent efforts have shifted to machine learning-based approaches. The
challenges include understanding diverse road topologies, reasoning traffic
dynamics over a... | Robotics |
What field is the article from? | Title: Exploring the Potential of Generative AI for the World Wide Web
Abstract: Generative Artificial Intelligence (AI) is a cutting-edge technology capable
of producing text, images, and various media content leveraging generative
models and user prompts. Between 2022 and 2023, generative AI surged in
popularity with... | Artificial Intelligence |
What field is the article from? | Title: Data Science for Social Good
Abstract: Data science has been described as the fourth paradigm for scientific
discovery. The latest wave of data science research, pertaining to machine
learning and artificial intelligence (AI), is growing exponentially and
garnering millions of annual citations. However, this gro... | Computers and Society |
What field is the article from? | Title: Large Language Model Enhanced Multi-Agent Systems for 6G Communications
Abstract: The rapid development of the Large Language Model (LLM) presents huge
opportunities for 6G communications, e.g., network optimization and management
by allowing users to input task requirements to LLMs by nature language.
However, ... | Artificial Intelligence |
What field is the article from? | Title: JADE: A Linguistics-based Safety Evaluation Platform for Large Language Models
Abstract: In this paper, we present JADE, a targeted linguistic fuzzing platform which
strengthens the linguistic complexity of seed questions to simultaneously and
consistently break a wide range of widely-used LLMs categorized in th... | Computational Linguistics |
What field is the article from? | Title: Cost Aware Untargeted Poisoning Attack against Graph Neural Networks,
Abstract: Graph Neural Networks (GNNs) have become widely used in the field of graph
mining. However, these networks are vulnerable to structural perturbations.
While many research efforts have focused on analyzing vulnerability through
poison... | Artificial Intelligence |
What field is the article from? | Title: A New Fine-grained Alignment Method for Image-text Matching
Abstract: Image-text retrieval is a widely studied topic in the field of computer
vision due to the exponential growth of multimedia data, whose core concept is
to measure the similarity between images and text. However, most existing
retrieval methods ... | Computer Vision |
What field is the article from? | Title: Multi-view Relation Learning for Cross-domain Few-shot Hyperspectral Image Classification
Abstract: Cross-domain few-shot hyperspectral image classification focuses on learning
prior knowledge from a large number of labeled samples from source domain and
then transferring the knowledge to the tasks which contain... | Computer Vision |
What field is the article from? | Title: FinA: Fairness of Adverse Effects in Decision-Making of Human-Cyber-Physical-System
Abstract: Ensuring fairness in decision-making systems within
Human-Cyber-Physical-Systems (HCPS) is a pressing concern, particularly when
diverse individuals, each with varying behaviors and expectations, coexist
within the same... | Artificial Intelligence |
What field is the article from? | Title: Color-Emotion Associations in Art: Fuzzy Approach
Abstract: Art objects can evoke certain emotions. Color is a fundamental element of
visual art and plays a significant role in how art is perceived. This paper
introduces a novel approach to classifying emotions in art using Fuzzy Sets. We
employ a fuzzy approach... | Computer Vision |
What field is the article from? | Title: Co-guiding for Multi-intent Spoken Language Understanding
Abstract: Recent graph-based models for multi-intent SLU have obtained promising
results through modeling the guidance from the prediction of intents to the
decoding of slot filling. However, existing methods (1) only model the
unidirectional guidance fro... | Computational Linguistics |
What field is the article from? | Title: AI and Jobs: Has the Inflection Point Arrived? Evidence from an Online Labor Platform
Abstract: Artificial intelligence (AI) refers to the ability of machines or software to
mimic or even surpass human intelligence in a given cognitive task. While
humans learn by both induction and deduction, the success of curr... | Artificial Intelligence |
What field is the article from? | Title: On Computing Makespan-Optimal Solutions for Generalized Sliding-Tile Puzzles
Abstract: In the $15$-puzzle game, $15$ labeled square tiles are reconfigured on a
$4\times 4$ board through an escort, wherein each (time) step, a single tile
neighboring it may slide into it, leaving the space previously occupied by t... | Robotics |
What field is the article from? | Title: HalluciDoctor: Mitigating Hallucinatory Toxicity in Visual Instruction Data
Abstract: Multi-modal Large Language Models (MLLMs) tuned on machine-generated
instruction-following data have demonstrated remarkable performance in various
multi-modal understanding and generation tasks. However, the hallucinations
inh... | Computer Vision |
What field is the article from? | Title: PhytNet -- Tailored Convolutional Neural Networks for Custom Botanical Data
Abstract: Automated disease, weed and crop classification with computer vision will be
invaluable in the future of agriculture. However, existing model architectures
like ResNet, EfficientNet and ConvNeXt often underperform on smaller,
s... | Computer Vision |
What field is the article from? | Title: NCL-SM: A Fully Annotated Dataset of Images from Human Skeletal Muscle Biopsies
Abstract: Single cell analysis of human skeletal muscle (SM) tissue cross-sections is a
fundamental tool for understanding many neuromuscular disorders. For this
analysis to be reliable and reproducible, identification of individual ... | Computer Vision |
What field is the article from? | Title: Leveraging Activation Maximization and Generative Adversarial Training to Recognize and Explain Patterns in Natural Areas in Satellite Imagery
Abstract: Natural protected areas are vital for biodiversity, climate change
mitigation, and supporting ecological processes. Despite their significance,
comprehensive ma... | Computer Vision |
What field is the article from? | Title: How Multilingual is Multilingual LLM?
Abstract: Large Language Models (LLMs), trained predominantly on extensive English
data, often exhibit limitations when applied to other languages. Current
research is primarily focused on enhancing the multilingual capabilities of
these models by employing various tuning st... | Computational Linguistics |
What field is the article from? | Title: Towards Verifiable Text Generation with Symbolic References
Abstract: Large language models (LLMs) have demonstrated an impressive ability to
synthesize plausible and fluent text. However they remain vulnerable to
hallucinations, and thus their outputs generally require manual human
verification for high-stakes ... | Computational Linguistics |
What field is the article from? | Title: Artificial Intelligence for reverse engineering: application to detergents using Raman spectroscopy
Abstract: The reverse engineering of a complex mixture, regardless of its nature, has
become significant today. Being able to quickly assess the potential toxicity
of new commercial products in relation to the env... | Artificial Intelligence |
What field is the article from? | Title: LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models
Abstract: Large language models (LLMs) provide excellent text-generation capabilities,
but standard prompting and generation methods generally do not lead to
intentional or goal-directed agents and might necessitate considerable prom... | Computational Linguistics |
What field is the article from? | Title: TransformCode: A Contrastive Learning Framework for Code Embedding via Subtree transformation
Abstract: Large-scale language models have made great progress in the field of software
engineering in recent years. They can be used for many code-related tasks such
as code clone detection, code-to-code search, and me... | Software Engineering |
What field is the article from? | Title: Generation of Games for Opponent Model Differentiation
Abstract: Protecting against adversarial attacks is a common multiagent problem.
Attackers in the real world are predominantly human actors, and the protection
methods often incorporate opponent models to improve the performance when
facing humans. Previous ... | Artificial Intelligence |
What field is the article from? | Title: Emotion-Oriented Behavior Model Using Deep Learning
Abstract: Emotions, as a fundamental ingredient of any social interaction, lead to
behaviors that represent the effectiveness of the interaction through facial
expressions and gestures in humans. Hence an agent must possess the social and
cognitive abilities to... | Computational Linguistics |
What field is the article from? | Title: Devil in the Landscapes: Inferring Epidemic Exposure Risks from Street View Imagery
Abstract: Built environment supports all the daily activities and shapes our health.
Leveraging informative street view imagery, previous research has established
the profound correlation between the built environment and chronic... | Computer Vision |
What field is the article from? | Title: Reinforcement Learning for Solving Stochastic Vehicle Routing Problem
Abstract: This study addresses a gap in the utilization of Reinforcement Learning (RL)
and Machine Learning (ML) techniques in solving the Stochastic Vehicle Routing
Problem (SVRP) that involves the challenging task of optimizing vehicle route... | Artificial Intelligence |
What field is the article from? | Title: BClean: A Bayesian Data Cleaning System
Abstract: There is a considerable body of work on data cleaning which employs various
principles to rectify erroneous data and transform a dirty dataset into a
cleaner one. One of prevalent approaches is probabilistic methods, including
Bayesian methods. However, existing ... | Artificial Intelligence |
What field is the article from? | Title: The WHY in Business Processes: Discovery of Causal Execution Dependencies
Abstract: A crucial element in predicting the outcomes of process interventions and
making informed decisions about the process is unraveling the genuine
relationships between the execution of process activities. Contemporary process
disco... | Artificial Intelligence |
What field is the article from? | Title: Entropy and the Kullback-Leibler Divergence for Bayesian Networks: Computational Complexity and Efficient Implementation
Abstract: Bayesian networks (BNs) are a foundational model in machine learning and
causal inference. Their graphical structure can handle high-dimensional
problems, divide-and-conquering them ... | Artificial Intelligence |
What field is the article from? | Title: Re-Scoring Using Image-Language Similarity for Few-Shot Object Detection
Abstract: Few-shot object detection, which focuses on detecting novel objects with few
labels, is an emerging challenge in the community. Recent studies show that
adapting a pre-trained model or modified loss function can improve performanc... | Computer Vision |
What field is the article from? | Title: Towards Model-Based Data Acquisition for Subjective Multi-Task NLP Problems
Abstract: Data annotated by humans is a source of knowledge by describing the
peculiarities of the problem and therefore fueling the decision process of the
trained model. Unfortunately, the annotation process for subjective natural
lang... | Computational Linguistics |
What field is the article from? | Title: Dual-path convolutional neural network using micro-FTIR imaging to predict breast cancer subtypes and biomarkers levels: estrogen receptor, progesterone receptor, HER2 and Ki67
Abstract: Breast cancer molecular subtypes classification plays an import role to sort
patients with divergent prognosis. The biomarkers... | Machine Learning |
What field is the article from? | Title: Qilin-Med-VL: Towards Chinese Large Vision-Language Model for General Healthcare
Abstract: Large Language Models (LLMs) have introduced a new era of proficiency in
comprehending complex healthcare and biomedical topics. However, there is a
noticeable lack of models in languages other than English and models that... | Computer Vision |
What field is the article from? | Title: Emergence of Abstract State Representations in Embodied Sequence Modeling
Abstract: Decision making via sequence modeling aims to mimic the success of language
models, where actions taken by an embodied agent are modeled as tokens to
predict. Despite their promising performance, it remains unclear if embodied
se... | Machine Learning |
What field is the article from? | Title: ChatGPT and post-test probability
Abstract: Reinforcement learning-based large language models, such as ChatGPT, are
believed to have potential to aid human experts in many domains, including
healthcare. There is, however, little work on ChatGPT's ability to perform a
key task in healthcare: formal, probabilisti... | Artificial Intelligence |
What field is the article from? | Title: ChatGPT as a Math Questioner? Evaluating ChatGPT on Generating Pre-university Math Questions
Abstract: Mathematical questioning is crucial for assessing students problem-solving
skills. Since manually creating such questions requires substantial effort,
automatic methods have been explored. Existing state-of-the... | Computational Linguistics |
What field is the article from? | Title: Utilizing Language Models for Energy Load Forecasting
Abstract: Energy load forecasting plays a crucial role in optimizing resource
allocation and managing energy consumption in buildings and cities. In this
paper, we propose a novel approach that leverages language models for energy
load forecasting. We employ ... | Artificial Intelligence |
What field is the article from? | Title: AdaDiff: Adaptive Step Selection for Fast Diffusion
Abstract: Diffusion models, as a type of generative models, have achieved impressive
results in generating images and videos conditioned on textual conditions.
However, the generation process of diffusion models involves denoising for
dozens of steps to produce... | Computer Vision |
What field is the article from? | Title: Beyond Detection: Unveiling Fairness Vulnerabilities in Abusive Language Models
Abstract: This work investigates the potential of undermining both fairness and
detection performance in abusive language detection. In a dynamic and complex
digital world, it is crucial to investigate the vulnerabilities of these
de... | Computational Linguistics |
What field is the article from? | Title: RACER: Rational Artificial Intelligence Car-following-model Enhanced by Reality
Abstract: This paper introduces RACER, the Rational Artificial Intelligence
Car-following model Enhanced by Reality, a cutting-edge deep learning
car-following model, that satisfies partial derivative constraints, designed to
predict... | Artificial Intelligence |
What field is the article from? | Title: Deep learning for 3D Object Detection and Tracking in Autonomous Driving: A Brief Survey
Abstract: Object detection and tracking are vital and fundamental tasks for autonomous
driving, aiming at identifying and locating objects from those predefined
categories in a scene. 3D point cloud learning has been attract... | Computer Vision |
What field is the article from? | Title: GPT-4 Enhanced Multimodal Grounding for Autonomous Driving: Leveraging Cross-Modal Attention with Large Language Models
Abstract: In the field of autonomous vehicles (AVs), accurately discerning commander
intent and executing linguistic commands within a visual context presents a
significant challenge. This pape... | Computer Vision |
What field is the article from? | Title: Discretionary Trees: Understanding Street-Level Bureaucracy via Machine Learning
Abstract: Street-level bureaucrats interact directly with people on behalf of
government agencies to perform a wide range of functions, including, for
example, administering social services and policing. A key feature of
street-leve... | Machine Learning |
What field is the article from? | Title: Augmenting deep neural networks with symbolic knowledge: Towards trustworthy and interpretable AI for education
Abstract: Artificial neural networks (ANNs) have shown to be amongst the most important
artificial intelligence (AI) techniques in educational applications, providing
adaptive educational services. How... | Artificial Intelligence |
What field is the article from? | Title: Evaluating Large Language Models through Gender and Racial Stereotypes
Abstract: Language Models have ushered a new age of AI gaining traction within the NLP
community as well as amongst the general population. AI's ability to make
predictions, generations and its applications in sensitive decision-making
scenar... | Computational Linguistics |
What field is the article from? | Title: R$^3$ Prompting: Review, Rephrase and Resolve for Chain-of-Thought Reasoning in Large Language Models under Noisy Context
Abstract: With the help of Chain-of-Thought (CoT) prompting, Large Language Models
(LLMs) have achieved remarkable performance on various reasoning tasks.
However, most of them have been eval... | Computational Linguistics |
What field is the article from? | Title: Towards Knowledge-driven Autonomous Driving
Abstract: This paper explores the emerging knowledge-driven autonomous driving
technologies. Our investigation highlights the limitations of current
autonomous driving systems, in particular their sensitivity to data bias,
difficulty in handling long-tail scenarios, an... | Robotics |
What field is the article from? | Title: Modality-Agnostic Self-Supervised Learning with Meta-Learned Masked Auto-Encoder
Abstract: Despite its practical importance across a wide range of modalities, recent
advances in self-supervised learning (SSL) have been primarily focused on a few
well-curated domains, e.g., vision and language, often relying on t... | Machine Learning |
What field is the article from? | Title: Towards Full-scene Domain Generalization in Multi-agent Collaborative Bird's Eye View Segmentation for Connected and Autonomous Driving
Abstract: Collaborative perception has recently gained significant attention in
autonomous driving, improving perception quality by enabling the exchange of
additional informati... | Computer Vision |
What field is the article from? | Title: Code Ownership in Open-Source AI Software Security
Abstract: As open-source AI software projects become an integral component in the AI
software development, it is critical to develop a novel methods to ensure and
measure the security of the open-source projects for developers. Code
ownership, pivotal in the evo... | Software Engineering |
What field is the article from? | Title: C-Procgen: Empowering Procgen with Controllable Contexts
Abstract: We present C-Procgen, an enhanced suite of environments on top of the Procgen
benchmark. C-Procgen provides access to over 200 unique game contexts across 16
games. It allows for detailed configuration of environments, ranging from game
mechanics... | Artificial Intelligence |
What field is the article from? | Title: AV2AV: Direct Audio-Visual Speech to Audio-Visual Speech Translation with Unified Audio-Visual Speech Representation
Abstract: This paper proposes a novel direct Audio-Visual Speech to Audio-Visual Speech
Translation (AV2AV) framework, where the input and output of the system are
multimodal (i.e., audio and visu... | Computer Vision |
What field is the article from? | Title: Rethinking Benchmark and Contamination for Language Models with Rephrased Samples
Abstract: Large language models are increasingly trained on all the data ever produced
by humans. Many have raised concerns about the trustworthiness of public
benchmarks due to potential contamination in pre-training or fine-tunin... | Computational Linguistics |
What field is the article from? | Title: Tell, don't show: Declarative facts influence how LLMs generalize
Abstract: We examine how large language models (LLMs) generalize from abstract
declarative statements in their training data. As an illustration, consider an
LLM that is prompted to generate weather reports for London in 2050. One
possibility is t... | Artificial Intelligence |
What field is the article from? | Title: Enhancing the Rationale-Input Alignment for Self-explaining Rationalization
Abstract: Rationalization empowers deep learning models with self-explaining
capabilities through a cooperative game, where a generator selects a
semantically consistent subset of the input as a rationale, and a subsequent
predictor make... | Artificial Intelligence |
What field is the article from? | Title: Enhancing Explainability in Mobility Data Science through a combination of methods
Abstract: In the domain of Mobility Data Science, the intricate task of interpreting
models trained on trajectory data, and elucidating the spatio-temporal movement
of entities, has persistently posed significant challenges. Conve... | Artificial Intelligence |
What field is the article from? | Title: Can large language models replace humans in the systematic review process? Evaluating GPT-4's efficacy in screening and extracting data from peer-reviewed and grey literature in multiple languages
Abstract: Systematic reviews are vital for guiding practice, research, and policy, yet
they are often slow and labou... | Computational Linguistics |
What field is the article from? | Title: Hybrid Focal and Full-Range Attention Based Graph Transformers
Abstract: The paradigm of Transformers using the self-attention mechanism has
manifested its advantage in learning graph-structured data. Yet, Graph
Transformers are capable of modeling full range dependencies but are often
deficient in extracting in... | Machine Learning |
What field is the article from? | Title: The Hyperdimensional Transform: a Holographic Representation of Functions
Abstract: Integral transforms are invaluable mathematical tools to map functions into
spaces where they are easier to characterize. We introduce the hyperdimensional
transform as a new kind of integral transform. It converts square-integra... | Machine Learning |
What field is the article from? | Title: InteraSSort: Interactive Assortment Planning Using Large Language Models
Abstract: Assortment planning, integral to multiple commercial offerings, is a key
problem studied in e-commerce and retail settings. Numerous variants of the
problem along with their integration into business solutions have been
thoroughly... | Artificial Intelligence |
What field is the article from? | Title: Think While You Write: Hypothesis Verification Promotes Faithful Knowledge-to-Text Generation
Abstract: Neural knowledge-to-text generation models often struggle to faithfully
generate descriptions for the input facts: they may produce hallucinations that
contradict the given facts, or describe facts not present... | Computational Linguistics |
What field is the article from? | Title: De-identification of clinical free text using natural language processing: A systematic review of current approaches
Abstract: Background: Electronic health records (EHRs) are a valuable resource for
data-driven medical research. However, the presence of protected health
information (PHI) makes EHRs unsuitable t... | Computational Linguistics |
What field is the article from? | Title: Forte: An Interactive Visual Analytic Tool for Trust-Augmented Net Load Forecasting
Abstract: Accurate net load forecasting is vital for energy planning, aiding decisions
on trade and load distribution. However, assessing the performance of
forecasting models across diverse input variables, like temperature and
... | Human-Computer Interaction |
What field is the article from? | Title: Video-Bench: A Comprehensive Benchmark and Toolkit for Evaluating Video-based Large Language Models
Abstract: Video-based large language models (Video-LLMs) have been recently introduced,
targeting both fundamental improvements in perception and comprehension, and a
diverse range of user inquiries. In pursuit of... | Computer Vision |
What field is the article from? | Title: Traffic Sign Interpretation in Real Road Scene
Abstract: Most existing traffic sign-related works are dedicated to detecting and
recognizing part of traffic signs individually, which fails to analyze the
global semantic logic among signs and may convey inaccurate traffic
instruction. Following the above issues, ... | Computer Vision |
What field is the article from? | Title: Synthetic Speaking Children -- Why We Need Them and How to Make Them
Abstract: Contemporary Human Computer Interaction (HCI) research relies primarily on
neural network models for machine vision and speech understanding of a system
user. Such models require extensively annotated training datasets for optimal
per... | Human-Computer Interaction |
What field is the article from? | Title: GPT-4V Takes the Wheel: Evaluating Promise and Challenges for Pedestrian Behavior Prediction
Abstract: Existing pedestrian behavior prediction methods rely primarily on deep neural
networks that utilize features extracted from video frame sequences. Although
these vision-based models have shown promising results... | Computer Vision |
What field is the article from? | Title: LLMs-augmented Contextual Bandit
Abstract: Contextual bandits have emerged as a cornerstone in reinforcement learning,
enabling systems to make decisions with partial feedback. However, as contexts
grow in complexity, traditional bandit algorithms can face challenges in
adequately capturing and utilizing such co... | Machine Learning |
What field is the article from? | Title: Canaries and Whistles: Resilient Drone Communication Networks with (or without) Deep Reinforcement Learning
Abstract: Communication networks able to withstand hostile environments are critically
important for disaster relief operations. In this paper, we consider a
challenging scenario where drones have been com... | Cryptography and Security |
What field is the article from? | Title: Neural Markov Prolog
Abstract: The recent rapid advance of AI has been driven largely by innovations in
neural network architectures. A concomitant concern is how to understand these
resulting systems. In this paper, we propose a tool to assist in both the
design of further innovative architectures and the simpl... | Artificial Intelligence |
What field is the article from? | Title: FD-MIA: Efficient Attacks on Fairness-enhanced Models
Abstract: Previous studies have developed fairness methods for biased models that
exhibit discriminatory behaviors towards specific subgroups. While these models
have shown promise in achieving fair predictions, recent research has
identified their potential ... | Machine Learning |
What field is the article from? | Title: Imitate the Good and Avoid the Bad: An Incremental Approach to Safe Reinforcement Learning
Abstract: A popular framework for enforcing safe actions in Reinforcement Learning (RL)
is Constrained RL, where trajectory based constraints on expected cost (or
other cost measures) are employed to enforce safety and mor... | Machine Learning |
What field is the article from? | Title: SiGeo: Sub-One-Shot NAS via Information Theory and Geometry of Loss Landscape
Abstract: Neural Architecture Search (NAS) has become a widely used tool for automating
neural network design. While one-shot NAS methods have successfully reduced
computational requirements, they often require extensive training. On t... | Machine Learning |
What field is the article from? | Title: A Systems-Theoretical Formalization of Closed Systems
Abstract: There is a lack of formalism for some key foundational concepts in systems
engineering. One of the most recently acknowledged deficits is the inadequacy
of systems engineering practices for engineering intelligent systems. In our
previous works, we ... | Artificial Intelligence |
What field is the article from? | Title: RLHF and IIA: Perverse Incentives
Abstract: Existing algorithms for reinforcement learning from human feedback (RLHF) can
incentivize responses at odds with preferences because they are based on models
that assume independence of irrelevant alternatives (IIA). The perverse
incentives induced by IIA give rise to ... | Machine Learning |
What field is the article from? | Title: Enhancing Trajectory Prediction through Self-Supervised Waypoint Noise Prediction
Abstract: Trajectory prediction is an important task that involves modeling the
indeterminate nature of traffic actors to forecast future trajectories given
the observed trajectory sequences. However, current methods confine themse... | Robotics |
What field is the article from? | Title: Automatic Bug Detection in Games using LSTM Networks
Abstract: We introduced a new framework to detect perceptual bugs using a Long
Short-Term Memory (LSTM) network, which detects bugs in video games as
anomalies. The detected buggy frames are then clustered to determine the
category of the occurred bug. The fra... | Machine Learning |
What field is the article from? | Title: NeRFiller: Completing Scenes via Generative 3D Inpainting
Abstract: We propose NeRFiller, an approach that completes missing portions of a 3D
capture via generative 3D inpainting using off-the-shelf 2D visual generative
models. Often parts of a captured 3D scene or object are missing due to mesh
reconstruction f... | Computer Vision |
What field is the article from? | Title: HAL 9000: Skynet's Risk Manager
Abstract: Intrusion Tolerant Systems (ITSs) are a necessary component for
cyber-services/infrastructures. Additionally, as cyberattacks follow a
multi-domain attack surface, a similar defensive approach should be applied,
namely, the use of an evolving multi-disciplinary solution ... | Cryptography and Security |
What field is the article from? | Title: Concept Prerequisite Relation Prediction by Using Permutation-Equivariant Directed Graph Neural Networks
Abstract: This paper studies the problem of CPRP, concept prerequisite relation
prediction, which is a fundamental task in using AI for education. CPRP is
usually formulated into a link-prediction task on a r... | Machine Learning |
What field is the article from? | Title: Re-evaluating Retrosynthesis Algorithms with Syntheseus
Abstract: The planning of how to synthesize molecules, also known as retrosynthesis,
has been a growing focus of the machine learning and chemistry communities in
recent years. Despite the appearance of steady progress, we argue that
imperfect benchmarks an... | Machine Learning |
What field is the article from? | Title: Regularization by Texts for Latent Diffusion Inverse Solvers
Abstract: The recent advent of diffusion models has led to significant progress in
solving inverse problems, leveraging these models as effective generative
priors. Nonetheless, challenges related to the ill-posed nature of such
problems remain, often ... | Computer Vision |
What field is the article from? | Title: Leveraging Domain Adaptation and Data Augmentation to Improve Qur'anic IR in English and Arabic
Abstract: In this work, we approach the problem of Qur'anic information retrieval (IR)
in Arabic and English. Using the latest state-of-the-art methods in neural IR,
we research what helps to tackle this task more eff... | Computational Linguistics |
What field is the article from? | Title: Deriving Comprehensible Theories from Probabilistic Circuits
Abstract: The field of Explainable AI (XAI) is seeking to shed light on the inner
workings of complex AI models and uncover the rationale behind their decisions.
One of the models gaining attention are probabilistic circuits (PCs), which are
a general ... | Artificial Intelligence |
What field is the article from? | Title: PixLore: A Dataset-driven Approach to Rich Image Captioning
Abstract: In the domain of vision-language integration, generating detailed image
captions poses a significant challenge due to the lack of a curated and rich
dataset. This study introduces PixLore, a novel method that leverages Querying
Transformers th... | Computer Vision |
What field is the article from? | Title: A novel post-hoc explanation comparison metric and applications
Abstract: Explanatory systems make the behavior of machine learning models more
transparent, but are often inconsistent. To quantify the differences between
explanatory systems, this paper presents the Shreyan Distance, a novel metric
based on the w... | Machine Learning |
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