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What field is the article from? | Title: Evaluating Large Language Models for Health-related Queries with Presuppositions
Abstract: As corporations rush to integrate large language models (LLMs) to their
search offerings, it is critical that they provide factually accurate
information that is robust to any presuppositions that a user may express. In
th... | Computational Linguistics |
What field is the article from? | Title: Can Large Language Models Capture Public Opinion about Global Warming? An Empirical Assessment of Algorithmic Fidelity and Bias
Abstract: Large language models (LLMs) have demonstrated their potential in social
science research by emulating human perceptions and behaviors, a concept
referred to as algorithmic fi... | Artificial Intelligence |
What field is the article from? | Title: On the verification of Embeddings using Hybrid Markov Logic
Abstract: The standard approach to verify representations learned by Deep Neural
Networks is to use them in specific tasks such as classification or regression,
and measure their performance based on accuracy in such tasks. However, in many
cases, we wo... | Machine Learning |
What field is the article from? | Title: Alpha-CLIP: A CLIP Model Focusing on Wherever You Want
Abstract: Contrastive Language-Image Pre-training (CLIP) plays an essential role in
extracting valuable content information from images across diverse tasks. It
aligns textual and visual modalities to comprehend the entire image, including
all the details, e... | Computer Vision |
What field is the article from? | Title: Heuristics-Driven Link-of-Analogy Prompting: Enhancing Large Language Models for Document-Level Event Argument Extraction
Abstract: In this study, we investigate in-context learning (ICL) in document-level
event argument extraction (EAE). The paper identifies key challenges in this
problem, including example sel... | Computational Linguistics |
What field is the article from? | Title: Combining Past, Present and Future: A Self-Supervised Approach for Class Incremental Learning
Abstract: Class Incremental Learning (CIL) aims to handle the scenario where data of
novel classes occur continuously and sequentially. The model should recognize
the sequential novel classes while alleviating the catas... | Computer Vision |
What field is the article from? | Title: The voraus-AD Dataset for Anomaly Detection in Robot Applications
Abstract: During the operation of industrial robots, unusual events may endanger the
safety of humans and the quality of production. When collecting data to detect
such cases, it is not ensured that data from all potentially occurring errors
is in... | Robotics |
What field is the article from? | Title: StyleCrafter: Enhancing Stylized Text-to-Video Generation with Style Adapter
Abstract: Text-to-video (T2V) models have shown remarkable capabilities in generating
diverse videos. However, they struggle to produce user-desired stylized videos
due to (i) text's inherent clumsiness in expressing specific styles and... | Computer Vision |
What field is the article from? | Title: TRIALSCOPE: A Unifying Causal Framework for Scaling Real-World Evidence Generation with Biomedical Language Models
Abstract: The rapid digitization of real-world data offers an unprecedented opportunity
for optimizing healthcare delivery and accelerating biomedical discovery. In
practice, however, such data is m... | Machine Learning |
What field is the article from? | Title: MIMONets: Multiple-Input-Multiple-Output Neural Networks Exploiting Computation in Superposition
Abstract: With the advent of deep learning, progressively larger neural networks have
been designed to solve complex tasks. We take advantage of these capacity-rich
models to lower the cost of inference by exploiting... | Machine Learning |
What field is the article from? | Title: Thermal Face Image Classification using Deep Learning Techniques
Abstract: Thermal images have various applications in security, medical and industrial
domains. This paper proposes a practical deep-learning approach for thermal
image classification. Accurate and efficient classification of thermal images
poses a... | Computer Vision |
What field is the article from? | Title: Integration and Implementation Strategies for AI Algorithm Deployment with Smart Routing Rules and Workflow Management
Abstract: This paper reviews the challenges hindering the widespread adoption of
artificial intelligence (AI) solutions in the healthcare industry, focusing on
computer vision applications for m... | Artificial Intelligence |
What field is the article from? | Title: Extracting Self-Consistent Causal Insights from Users Feedback with LLMs and In-context Learning
Abstract: Microsoft Windows Feedback Hub is designed to receive customer feedback on a
wide variety of subjects including critical topics such as power and battery.
Feedback is one of the most effective ways to have ... | Artificial Intelligence |
What field is the article from? | Title: The Development of LLMs for Embodied Navigation
Abstract: In recent years, the rapid advancement of Large Language Models (LLMs) such
as the Generative Pre-trained Transformer (GPT) has attracted increasing
attention due to their potential in a variety of practical applications. The
application of LLMs with Embo... | Artificial Intelligence |
What field is the article from? | Title: RECALL: A Benchmark for LLMs Robustness against External Counterfactual Knowledge
Abstract: LLMs and AI chatbots have improved people's efficiency in various fields.
However, the necessary knowledge for answering the question may be beyond the
models' knowledge boundaries. To mitigate this issue, many researcher... | Computational Linguistics |
What field is the article from? | Title: EduGym: An Environment Suite for Reinforcement Learning Education
Abstract: Due to the empirical success of reinforcement learning, an increasing number
of students study the subject. However, from our practical teaching experience,
we see students entering the field (bachelor, master and early PhD) often
strugg... | Machine Learning |
What field is the article from? | Title: The Ethics of Automating Legal Actors
Abstract: The introduction of large public legal datasets has brought about a
renaissance in legal NLP. Many of these datasets are comprised of legal
judgements - the product of judges deciding cases. This fact, together with the
way machine learning works, means that severa... | Computational Linguistics |
What field is the article from? | Title: War and Peace (WarAgent): Large Language Model-based Multi-Agent Simulation of World Wars
Abstract: Can we avoid wars at the crossroads of history? This question has been
pursued by individuals, scholars, policymakers, and organizations throughout
human history. In this research, we attempt to answer the questio... | Artificial Intelligence |
What field is the article from? | Title: Sleep Deprivation in the Forward-Forward Algorithm
Abstract: This paper aims to explore the separation of the two forward passes in the
Forward-Forward algorithm from a biological perspective in the context of
sleep. We show the size of the gap between the sleep and awake phase influences
the learning capabiliti... | Artificial Intelligence |
What field is the article from? | Title: Sequence-Level Certainty Reduces Hallucination In Knowledge-Grounded Dialogue Generation
Abstract: Model hallucination has been a crucial interest of research in Natural
Language Generation (NLG). In this work, we propose sequence-level certainty as
a common theme over hallucination in NLG, and explore the corre... | Computational Linguistics |
What field is the article from? | Title: Towards Explainable Strategy Templates using NLP Transformers
Abstract: This paper bridges the gap between mathematical heuristic strategies learned
from Deep Reinforcement Learning (DRL) in automated agent negotiation, and
comprehensible, natural language explanations. Our aim is to make these
strategies more a... | Artificial Intelligence |
What field is the article from? | Title: Beyond Size: How Gradients Shape Pruning Decisions in Large Language Models
Abstract: Large Language Models (LLMs) with a billion or more parameters are prime
targets for network pruning, which aims to reduce a portion of the network
weights without compromising performance. Prior approaches such as Weights
Magn... | Computational Linguistics |
What field is the article from? | Title: A Cross Attention Approach to Diagnostic Explainability using Clinical Practice Guidelines for Depression
Abstract: The lack of explainability using relevant clinical knowledge hinders the
adoption of Artificial Intelligence-powered analysis of unstructured clinical
dialogue. A wealth of relevant, untapped Menta... | Artificial Intelligence |
What field is the article from? | Title: Deep Unsupervised Domain Adaptation for Time Series Classification: a Benchmark
Abstract: Unsupervised Domain Adaptation (UDA) aims to harness labeled source data to
train models for unlabeled target data. Despite extensive research in domains
like computer vision and natural language processing, UDA remains und... | Machine Learning |
What field is the article from? | Title: DocPedia: Unleashing the Power of Large Multimodal Model in the Frequency Domain for Versatile Document Understanding
Abstract: This work presents DocPedia, a novel large multimodal model (LMM) for
versatile OCR-free document understanding, capable of parsing images up to
2,560$\times$2,560 resolution. Unlike ex... | Computer Vision |
What field is the article from? | Title: Movement Primitive Diffusion: Learning Gentle Robotic Manipulation of Deformable Objects
Abstract: Policy learning in robot-assisted surgery (RAS) lacks data efficient and
versatile methods that exhibit the desired motion quality for delicate surgical
interventions. To this end, we introduce Movement Primitive D... | Robotics |
What field is the article from? | Title: Comparing Generative Chatbots Based on Process Requirements
Abstract: Business processes are commonly represented by modelling languages, such as
Event-driven Process Chain (EPC), Yet Another Workflow Language (YAWL), and the
most popular standard notation for modelling business processes, the Business
Process M... | Computational Linguistics |
What field is the article from? | Title: SurreyAI 2023 Submission for the Quality Estimation Shared Task
Abstract: Quality Estimation (QE) systems are important in situations where it is
necessary to assess the quality of translations, but there is no reference
available. This paper describes the approach adopted by the SurreyAI team for
addressing the... | Computational Linguistics |
What field is the article from? | Title: AI Competitions and Benchmarks: towards impactful challenges with post-challenge papers, benchmarks and other dissemination actions
Abstract: Organising an AI challenge does not end with the final event. The
long-lasting impact also needs to be organised. This chapter covers the various
activities after the chal... | Machine Learning |
What field is the article from? | Title: Are we going MAD? Benchmarking Multi-Agent Debate between Language Models for Medical Q&A
Abstract: Recent advancements in large language models (LLMs) underscore their
potential for responding to medical inquiries. However, ensuring that
generative agents provide accurate and reliable answers remains an ongoing... | Computational Linguistics |
What field is the article from? | Title: A Bag of Receptive Fields for Time Series Extrinsic Predictions
Abstract: High-dimensional time series data poses challenges due to its dynamic nature,
varying lengths, and presence of missing values. This kind of data requires
extensive preprocessing, limiting the applicability of existing Time Series
Classific... | Machine Learning |
What field is the article from? | Title: Unmasking Bias and Inequities: A Systematic Review of Bias Detection and Mitigation in Healthcare Artificial Intelligence Using Electronic Health Records
Abstract: Objectives: Artificial intelligence (AI) applications utilizing electronic
health records (EHRs) have gained popularity, but they also introduce vari... | Artificial Intelligence |
What field is the article from? | Title: Weakly Supervised Semantic Parsing with Execution-based Spurious Program Filtering
Abstract: The problem of spurious programs is a longstanding challenge when training a
semantic parser from weak supervision. To eliminate such programs that have
wrong semantics but correct denotation, existing methods focus on e... | Computational Linguistics |
What field is the article from? | Title: A Meta-Level Learning Algorithm for Sequential Hyper-Parameter Space Reduction in AutoML
Abstract: AutoML platforms have numerous options for the algorithms to try for each
step of the analysis, i.e., different possible algorithms for imputation,
transformations, feature selection, and modelling. Finding the opt... | Machine Learning |
What field is the article from? | Title: OASIS: Offsetting Active Reconstruction Attacks in Federated Learning
Abstract: Federated Learning (FL) has garnered significant attention for its potential
to protect user privacy while enhancing model training efficiency. However,
recent research has demonstrated that FL protocols can be easily compromised by
... | Cryptography and Security |
What field is the article from? | Title: Difference of Probability and Information Entropy for Skills Classification and Prediction in Student Learning
Abstract: The probability of an event is in the range of [0, 1]. In a sample space S,
the value of probability determines whether an outcome is true or false. The
probability of an event Pr(A) that will... | Artificial Intelligence |
What field is the article from? | Title: A novel transformer-based approach for soil temperature prediction
Abstract: Soil temperature is one of the most significant parameters that plays a
crucial role in glacier energy, dynamics of mass balance, processes of surface
hydrological, coaction of glacier-atmosphere, nutrient cycling, ecological
stability,... | Machine Learning |
What field is the article from? | Title: Deep Group Interest Modeling of Full Lifelong User Behaviors for CTR Prediction
Abstract: Extracting users' interests from their lifelong behavior sequence is crucial
for predicting Click-Through Rate (CTR). Most current methods employ a
two-stage process for efficiency: they first select historical behaviors
re... | Information Retrieval |
What field is the article from? | Title: chatGPT for generating questions and assessments based on accreditations
Abstract: This research aims to take advantage of artificial intelligence techniques in
producing students assessment that is compatible with the different academic
accreditations of the same program. The possibility of using generative
art... | Computers and Society |
What field is the article from? | Title: Hourglass Tokenizer for Efficient Transformer-Based 3D Human Pose Estimation
Abstract: Transformers have been successfully applied in the field of video-based 3D
human pose estimation. However, the high computational costs of these video
pose transformers (VPTs) make them impractical on resource-constrained devi... | Computer Vision |
What field is the article from? | Title: The Disagreement Problem in Faithfulness Metrics
Abstract: The field of explainable artificial intelligence (XAI) aims to explain how
black-box machine learning models work. Much of the work centers around the
holy grail of providing post-hoc feature attributions to any model
architecture. While the pace of inno... | Machine Learning |
What field is the article from? | Title: Is Feedback All You Need? Leveraging Natural Language Feedback in Goal-Conditioned Reinforcement Learning
Abstract: Despite numerous successes, the field of reinforcement learning (RL) remains
far from matching the impressive generalisation power of human behaviour
learning. One possible way to help bridge this ... | Computational Linguistics |
What field is the article from? | Title: INTERVENOR: Prompt the Coding Ability of Large Language Models with the Interactive Chain of Repairing
Abstract: This paper proposes INTERactiVE chaiN Of Repairing (INTERVENOR), which mimics
human code repairing behavior (iteratively judging, rethinking, and repairing)
and prompts the coding ability of regard La... | Software Engineering |
What field is the article from? | Title: Forcing Generative Models to Degenerate Ones: The Power of Data Poisoning Attacks
Abstract: Growing applications of large language models (LLMs) trained by a third party
raise serious concerns on the security vulnerability of LLMs.It has been
demonstrated that malicious actors can covertly exploit these vulnerab... | Cryptography and Security |
What field is the article from? | Title: Do Smaller Language Models Answer Contextualised Questions Through Memorisation Or Generalisation?
Abstract: A distinction is often drawn between a model's ability to predict a label for
an evaluation sample that is directly memorised from highly similar training
samples versus an ability to predict the label vi... | Computational Linguistics |
What field is the article from? | Title: Advancing Post Hoc Case Based Explanation with Feature Highlighting
Abstract: Explainable AI (XAI) has been proposed as a valuable tool to assist in
downstream tasks involving human and AI collaboration. Perhaps the most
psychologically valid XAI techniques are case based approaches which display
'whole' exempla... | Artificial Intelligence |
What field is the article from? | Title: TFMQ-DM: Temporal Feature Maintenance Quantization for Diffusion Models
Abstract: The Diffusion model, a prevalent framework for image generation, encounters
significant challenges in terms of broad applicability due to its extended
inference times and substantial memory requirements. Efficient Post-training
Qua... | Computer Vision |
What field is the article from? | Title: ChatGPT in the context of precision agriculture data analytics
Abstract: In this study we argue that integrating ChatGPT into the data processing
pipeline of automated sensors in precision agriculture has the potential to
bring several benefits and enhance various aspects of modern farming practices.
Policy make... | Artificial Intelligence |
What field is the article from? | Title: QualEval: Qualitative Evaluation for Model Improvement
Abstract: Quantitative evaluation metrics have traditionally been pivotal in gauging
the advancements of artificial intelligence systems, including large language
models (LLMs). However, these metrics have inherent limitations. Given the
intricate nature of ... | Machine Learning |
What field is the article from? | Title: diff History for Long-Context Language Agents
Abstract: Language Models (LMs) offer an exciting solution for general-purpose embodied
control. However, a key technical issue arises when using an LM-based
controller: environment observations must be converted to text, which coupled
with history, leads to prohibit... | Artificial Intelligence |
What field is the article from? | Title: Divide-and-Conquer Attack: Harnessing the Power of LLM to Bypass the Censorship of Text-to-Image Generation Model
Abstract: Text-to-image generative models offer many innovative services but also raise
ethical concerns due to their potential to generate unethical images. Most
publicly available text-to-image mod... | Artificial Intelligence |
What field is the article from? | Title: Dense Video Captioning: A Survey of Techniques, Datasets and Evaluation Protocols
Abstract: Untrimmed videos have interrelated events, dependencies, context, overlapping
events, object-object interactions, domain specificity, and other semantics
that are worth highlighting while describing a video in natural lan... | Computer Vision |
What field is the article from? | Title: Explainable Product Classification for Customs
Abstract: The task of assigning internationally accepted commodity codes (aka HS codes)
to traded goods is a critical function of customs offices. Like court decisions
made by judges, this task follows the doctrine of precedent and can be
nontrivial even for experie... | Artificial Intelligence |
What field is the article from? | Title: Robust Data Pruning under Label Noise via Maximizing Re-labeling Accuracy
Abstract: Data pruning, which aims to downsize a large training set into a small
informative subset, is crucial for reducing the enormous computational costs of
modern deep learning. Though large-scale data collections invariably contain
a... | Machine Learning |
What field is the article from? | Title: CAMRA: Copilot for AMR Annotation
Abstract: In this paper, we introduce CAMRA (Copilot for AMR Annotatations), a
cutting-edge web-based tool designed for constructing Abstract Meaning
Representation (AMR) from natural language text. CAMRA offers a novel approach
to deep lexical semantics annotation such as AMR, ... | Computational Linguistics |
What field is the article from? | Title: The Rise of the AI Co-Pilot: Lessons for Design from Aviation and Beyond
Abstract: The fast pace of advances in AI promises to revolutionize various aspects of
knowledge work, extending its influence to daily life and professional fields
alike. We advocate for a paradigm where AI is seen as a collaborative co-pi... | Human-Computer Interaction |
What field is the article from? | Title: Data Contamination Quiz: A Tool to Detect and Estimate Contamination in Large Language Models
Abstract: We propose the Data Contamination Quiz, a simple and effective approach to
detect data contamination in large language models (LLMs) and estimate the
amount of it. Specifically, we frame data contamination det... | Computational Linguistics |
What field is the article from? | Title: Multi-criteria recommendation systems to foster online grocery
Abstract: With the exponential increase in information, it has become imperative to
design mechanisms that allow users to access what matters to them as quickly as
possible. The recommendation system ($RS$) with information technology
development is ... | Information Retrieval |
What field is the article from? | Title: Generalization to New Sequential Decision Making Tasks with In-Context Learning
Abstract: Training autonomous agents that can learn new tasks from only a handful of
demonstrations is a long-standing problem in machine learning. Recently,
transformers have been shown to learn new language or vision tasks without ... | Machine Learning |
What field is the article from? | Title: Math-Shepherd: A Label-Free Step-by-Step Verifier for LLMs in Mathematical Reasoning
Abstract: Large language models (LLMs) have demonstrated remarkable capabilities across
a wide range of tasks. However, even the most advanced open-source LLMs, such
as the LLaMA family models, still face challenges when it come... | Artificial Intelligence |
What field is the article from? | Title: Replay across Experiments: A Natural Extension of Off-Policy RL
Abstract: Replaying data is a principal mechanism underlying the stability and data
efficiency of off-policy reinforcement learning (RL). We present an effective
yet simple framework to extend the use of replays across multiple experiments,
minimall... | Machine Learning |
What field is the article from? | Title: End-to-End Autoregressive Retrieval via Bootstrapping for Smart Reply Systems
Abstract: Reply suggestion systems represent a staple component of many instant
messaging and email systems. However, the requirement to produce sets of
replies, rather than individual replies, makes the task poorly suited for
out-of-t... | Computational Linguistics |
What field is the article from? | Title: NNG-Mix: Improving Semi-supervised Anomaly Detection with Pseudo-anomaly Generation
Abstract: Anomaly detection (AD) is essential in identifying rare and often critical
events in complex systems, finding applications in fields such as network
intrusion detection, financial fraud detection, and fault detection in... | Machine Learning |
What field is the article from? | Title: Predicting Ground Reaction Force from Inertial Sensors
Abstract: The study of ground reaction forces (GRF) is used to characterize the
mechanical loading experienced by individuals in movements such as running,
which is clinically applicable to identify athletes at risk for stress-related
injuries. Our aim in th... | Machine Learning |
What field is the article from? | Title: Causality and Explainability for Trustworthy Integrated Pest Management
Abstract: Pesticides serve as a common tool in agricultural pest control but
significantly contribute to the climate crisis. To combat this, Integrated Pest
Management (IPM) stands as a climate-smart alternative. Despite its potential,
IPM f... | Machine Learning |
What field is the article from? | Title: Multi-modal Latent Space Learning for Chain-of-Thought Reasoning in Language Models
Abstract: Chain-of-thought (CoT) reasoning has exhibited impressive performance in
language models for solving complex tasks and answering questions. However,
many real-world questions require multi-modal information, such as tex... | Artificial Intelligence |
What field is the article from? | Title: Systematic AI Approach for AGI: Addressing Alignment, Energy, and AGI Grand Challenges
Abstract: AI faces a trifecta of grand challenges the Energy Wall, the Alignment
Problem and the Leap from Narrow AI to AGI. Contemporary AI solutions consume
unsustainable amounts of energy during model training and daily
ope... | Artificial Intelligence |
What field is the article from? | Title: Internet of Federated Digital Twins (IoFDT): Connecting Twins Beyond Borders for Society 5.0
Abstract: The concept of digital twin (DT), which enables the creation of a
programmable, digital representation of physical systems, is expected to
revolutionize future industries and will lie at the heart of the vision... | Artificial Intelligence |
What field is the article from? | Title: FedReverse: Multiparty Reversible Deep Neural Network Watermarking
Abstract: The proliferation of Deep Neural Networks (DNN) in commercial applications is
expanding rapidly. Simultaneously, the increasing complexity and cost of
training DNN models have intensified the urgency surrounding the protection of
intell... | Cryptography and Security |
What field is the article from? | Title: Learning Multi-graph Structure for Temporal Knowledge Graph Reasoning
Abstract: Temporal Knowledge Graph (TKG) reasoning that forecasts future events based
on historical snapshots distributed over timestamps is denoted as extrapolation
and has gained significant attention. Owing to its extreme versatility and
va... | Artificial Intelligence |
What field is the article from? | Title: Context Shift Reduction for Offline Meta-Reinforcement Learning
Abstract: Offline meta-reinforcement learning (OMRL) utilizes pre-collected offline
datasets to enhance the agent's generalization ability on unseen tasks.
However, the context shift problem arises due to the distribution discrepancy
between the con... | Machine Learning |
What field is the article from? | Title: Responsibility in Extensive Form Games
Abstract: Two different forms of responsibility, counterfactual and seeing-to-it, have
been extensively discussed in the philosophy and AI in the context of a single
agent or multiple agents acting simultaneously. Although the generalisation of
counterfactual responsibility... | Artificial Intelligence |
What field is the article from? | Title: TPTU-v2: Boosting Task Planning and Tool Usage of Large Language Model-based Agents in Real-world Systems
Abstract: Large Language Models (LLMs) have demonstrated proficiency in addressing
tasks that necessitate a combination of task planning and the usage of external
tools that require a blend of task planning ... | Artificial Intelligence |
What field is the article from? | Title: PIE-NeRF: Physics-based Interactive Elastodynamics with NeRF
Abstract: We show that physics-based simulations can be seamlessly integrated with NeRF
to generate high-quality elastodynamics of real-world objects. Unlike existing
methods, we discretize nonlinear hyperelasticity in a meshless way, obviating
the nec... | Computer Vision |
What field is the article from? | Title: Polynomial-based Self-Attention for Table Representation learning
Abstract: Structured data, which constitutes a significant portion of existing data
types, has been a long-standing research topic in the field of machine
learning. Various representation learning methods for tabular data have been
proposed, rangi... | Artificial Intelligence |
What field is the article from? | Title: Make me an Offer: Forward and Reverse Auctioning Problems in the Tourism Industry
Abstract: Most tourist destinations are facing regular and consistent seasonality with
significant economic and social impacts. This phenomenon is more pronounced in
the post-covid era, where demand for travel has increased but une... | Artificial Intelligence |
What field is the article from? | Title: Optimizing the Passenger Flow for Airport Security Check
Abstract: Due to the necessary security for the airport and flight, passengers are
required to have strict security check before getting aboard. However, there
are frequent complaints of wasting huge amount of time while waiting for the
security check. Thi... | Artificial Intelligence |
What field is the article from? | Title: Modular Control Architecture for Safe Marine Navigation: Reinforcement Learning and Predictive Safety Filters
Abstract: Many autonomous systems face safety challenges, requiring robust closed-loop
control to handle physical limitations and safety constraints. Real-world
systems, like autonomous ships, encounter ... | Robotics |
What field is the article from? | Title: Federated Learning for 6G: Paradigms, Taxonomy, Recent Advances and Insights
Abstract: Artificial Intelligence (AI) is expected to play an instrumental role in the
next generation of wireless systems, such as sixth-generation (6G) mobile
network. However, massive data, energy consumption, training complexity, an... | Machine Learning |
What field is the article from? | Title: Limited Data, Unlimited Potential: A Study on ViTs Augmented by Masked Autoencoders
Abstract: Vision Transformers (ViTs) have become ubiquitous in computer vision. Despite
their success, ViTs lack inductive biases, which can make it difficult to train
them with limited data. To address this challenge, prior stud... | Computer Vision |
What field is the article from? | Title: Automaton Distillation: Neuro-Symbolic Transfer Learning for Deep Reinforcement Learning
Abstract: Reinforcement learning (RL) is a powerful tool for finding optimal policies
in sequential decision processes. However, deep RL methods suffer from two
weaknesses: collecting the amount of agent experience required ... | Machine Learning |
What field is the article from? | Title: The language of prompting: What linguistic properties make a prompt successful?
Abstract: The latest generation of LLMs can be prompted to achieve impressive zero-shot
or few-shot performance in many NLP tasks. However, since performance is highly
sensitive to the choice of prompts, considerable effort has been ... | Computational Linguistics |
What field is the article from? | Title: Knowledge Plugins: Enhancing Large Language Models for Domain-Specific Recommendations
Abstract: The significant progress of large language models (LLMs) provides a promising
opportunity to build human-like systems for various practical applications.
However, when applied to specific task domains, an LLM pre-tra... | Information Retrieval |
What field is the article from? | Title: Understanding Parameter Saliency via Extreme Value Theory
Abstract: Deep neural networks are being increasingly implemented throughout society in
recent years. It is useful to identify which parameters trigger
misclassification in diagnosing undesirable model behaviors. The concept of
parameter saliency is propo... | Computer Vision |
What field is the article from? | Title: To Tell The Truth: Language of Deception and Language Models
Abstract: Text-based misinformation permeates online discourses, yet evidence of
people's ability to discern truth from such deceptive textual content is
scarce. We analyze a novel TV game show data where conversations in a
high-stake environment betwe... | Computational Linguistics |
What field is the article from? | Title: Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes the Lead
Abstract: Anomaly detection is a crucial task across different domains and data types.
However, existing anomaly detection models are often designed for specific
domains and modalities. This study exp... | Computer Vision |
What field is the article from? | Title: Continual Learning with Low Rank Adaptation
Abstract: Recent work using pretrained transformers has shown impressive performance
when fine-tuned with data from the downstream problem of interest. However,
they struggle to retain that performance when the data characteristics changes.
In this paper, we focus on c... | Machine Learning |
What field is the article from? | Title: SmartMask: Context Aware High-Fidelity Mask Generation for Fine-grained Object Insertion and Layout Control
Abstract: The field of generative image inpainting and object insertion has made
significant progress with the recent advent of latent diffusion models.
Utilizing a precise object mask can greatly enhance ... | Computer Vision |
What field is the article from? | Title: Jailbreaking GPT-4V via Self-Adversarial Attacks with System Prompts
Abstract: Existing work on jailbreak Multimodal Large Language Models (MLLMs) has
focused primarily on adversarial examples in model inputs, with less attention
to vulnerabilities in model APIs. To fill the research gap, we carry out the
follow... | Cryptography and Security |
What field is the article from? | Title: Transformers Learn Higher-Order Optimization Methods for In-Context Learning: A Study with Linear Models
Abstract: Transformers are remarkably good at in-context learning (ICL) -- learning
from demonstrations without parameter updates -- but how they perform ICL
remains a mystery. Recent work suggests that Trans... | Machine Learning |
What field is the article from? | Title: Explainable AI in Grassland Monitoring: Enhancing Model Performance and Domain Adaptability
Abstract: Grasslands are known for their high biodiversity and ability to provide
multiple ecosystem services. Challenges in automating the identification of
indicator plants are key obstacles to large-scale grassland mon... | Machine Learning |
What field is the article from? | Title: Exploring Machine Learning Models for Federated Learning: A Review of Approaches, Performance, and Limitations
Abstract: In the growing world of artificial intelligence, federated learning is a
distributed learning framework enhanced to preserve the privacy of individuals'
data. Federated learning lays the groun... | Machine Learning |
What field is the article from? | Title: DeSIQ: Towards an Unbiased, Challenging Benchmark for Social Intelligence Understanding
Abstract: Social intelligence is essential for understanding and reasoning about human
expressions, intents and interactions. One representative benchmark for its
study is Social Intelligence Queries (Social-IQ), a dataset of... | Computational Linguistics |
What field is the article from? | Title: MASP: Scalable GNN-based Planning for Multi-Agent Navigation
Abstract: We investigate the problem of decentralized multi-agent navigation tasks,
where multiple agents need to reach initially unassigned targets in a limited
time. Classical planning-based methods suffer from expensive computation
overhead at each ... | Machine Learning |
What field is the article from? | Title: Adinkra Symbol Recognition using Classical Machine Learning and Deep Learning
Abstract: Artificial intelligence (AI) has emerged as a transformative influence,
engendering paradigm shifts in global societies, spanning academia and
industry. However, in light of these rapid advances, addressing the
underrepresent... | Computer Vision |
What field is the article from? | Title: PromptBench: A Unified Library for Evaluation of Large Language Models
Abstract: The evaluation of large language models (LLMs) is crucial to assess their
performance and mitigate potential security risks. In this paper, we introduce
PromptBench, a unified library to evaluate LLMs. It consists of several key
com... | Artificial Intelligence |
What field is the article from? | Title: A Survey on Knowledge Editing of Neural Networks
Abstract: Deep neural networks are becoming increasingly pervasive in academia and
industry, matching and surpassing human performance on a wide variety of fields
and related tasks. However, just as humans, even the largest artificial neural
networks make mistakes... | Machine Learning |
What field is the article from? | Title: ZeST-NeRF: Using temporal aggregation for Zero-Shot Temporal NeRFs
Abstract: In the field of media production, video editing techniques play a pivotal
role. Recent approaches have had great success at performing novel view image
synthesis of static scenes. But adding temporal information adds an extra layer
of c... | Computer Vision |
What field is the article from? | Title: Mutual Enhancement of Large and Small Language Models with Cross-Silo Knowledge Transfer
Abstract: While large language models (LLMs) are empowered with broad knowledge, their
task-specific performance is often suboptimal. It necessitates fine-tuning LLMs
with task-specific data, but such data may be inaccessibl... | Artificial Intelligence |
What field is the article from? | Title: Meta-learning of semi-supervised learning from tasks with heterogeneous attribute spaces
Abstract: We propose a meta-learning method for semi-supervised learning that learns
from multiple tasks with heterogeneous attribute spaces. The existing
semi-supervised meta-learning methods assume that all tasks share the... | Machine Learning |
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