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What field is the article from? | Title: Peeking Inside the Schufa Blackbox: Explaining the German Housing Scoring System
Abstract: Explainable Artificial Intelligence is a concept aimed at making complex
algorithms transparent to users through a uniform solution. Researchers have
highlighted the importance of integrating domain specific contexts to de... | Artificial Intelligence |
What field is the article from? | Title: Forecasting Post-Wildfire Vegetation Recovery in California using a Convolutional Long Short-Term Memory Tensor Regression Network
Abstract: The study of post-wildfire plant regrowth is essential for developing
successful ecosystem recovery strategies. Prior research mainly examines key
ecological and biogeograp... | Machine Learning |
What field is the article from? | Title: Scalable Knowledge Graph Construction and Inference on Human Genome Variants
Abstract: Real-world knowledge can be represented as a graph consisting of entities and
relationships between the entities. The need for efficient and scalable
solutions arises when dealing with vast genomic data, like RNA-sequencing.
K... | Artificial Intelligence |
What field is the article from? | Title: MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations
Abstract: Imitation learning from a large set of human demonstrations has proved to be
an effective paradigm for building capable robot agents. However, the
demonstrations can be extremely costly and time-consuming to colle... | Robotics |
What field is the article from? | Title: Hot PATE: Private Aggregation of Distributions for Diverse Task
Abstract: The Private Aggregation of Teacher Ensembles (PATE)
framework~\cite{PapernotAEGT:ICLR2017} is a versatile approach to
privacy-preserving machine learning. In PATE, teacher models are trained on
distinct portions of sensitive data, and thei... | Machine Learning |
What field is the article from? | Title: Strategic Data Augmentation with CTGAN for Smart Manufacturing: Enhancing Machine Learning Predictions of Paper Breaks in Pulp-and-Paper Production
Abstract: A significant challenge for predictive maintenance in the pulp-and-paper
industry is the infrequency of paper breaks during the production process. In
this... | Machine Learning |
What field is the article from? | Title: Instrumental Variable Estimation for Causal Inference in Longitudinal Data with Time-Dependent Latent Confounders
Abstract: Causal inference from longitudinal observational data is a challenging
problem due to the difficulty in correctly identifying the time-dependent
confounders, especially in the presence of l... | Machine Learning |
What field is the article from? | Title: Ranking with Slot Constraints
Abstract: We introduce the problem of ranking with slot constraints, which can be used
to model a wide range of application problems -- from college admission with
limited slots for different majors, to composing a stratified cohort of
eligible participants in a medical trial. We sh... | Information Retrieval |
What field is the article from? | Title: Improving Factual Consistency of Text Summarization by Adversarially Decoupling Comprehension and Embellishment Abilities of LLMs
Abstract: Despite the recent progress in text summarization made by large language
models (LLMs), they often generate summaries that are factually inconsistent
with original articles,... | Computational Linguistics |
What field is the article from? | Title: Generate, Filter, and Fuse: Query Expansion via Multi-Step Keyword Generation for Zero-Shot Neural Rankers
Abstract: Query expansion has been proved to be effective in improving recall and
precision of first-stage retrievers, and yet its influence on a complicated,
state-of-the-art cross-encoder ranker remains u... | Information Retrieval |
What field is the article from? | Title: Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers
Abstract: The Geometric Algebra Transformer (GATr) is a versatile architecture for
geometric deep learning based on projective geometric algebra. We generalize
this architecture into a blueprint that allows one to constru... | Machine Learning |
What field is the article from? | Title: Hallucination Detection for Grounded Instruction Generation
Abstract: We investigate the problem of generating instructions to guide humans to
navigate in simulated residential environments. A major issue with current
models is hallucination: they generate references to actions or objects that
are inconsistent w... | Computational Linguistics |
What field is the article from? | Title: GeoLocator: a location-integrated large multimodal model for inferring geo-privacy
Abstract: Geographic privacy or geo-privacy refers to the keeping private of one's
geographic location, especially the restriction of geographical data maintained
by personal electronic equipment. Geo-privacy is a crucial aspect o... | Computers and Society |
What field is the article from? | Title: DevBots can co-design APIs
Abstract: DevBots are automated tools that perform various tasks in order to support
software development. They are a growing trend and have been used in
repositories to automate repetitive tasks, as code generators, and as
collaborators in eliciting requirements and defining architect... | Software Engineering |
What field is the article from? | Title: YUAN 2.0: A Large Language Model with Localized Filtering-based Attention
Abstract: In this work, we develop and release Yuan 2.0, a series of large language
models with parameters ranging from 2.1 billion to 102.6 billion. The Localized
Filtering-based Attention (LFA) is introduced to incorporate prior knowledg... | Computational Linguistics |
What field is the article from? | Title: A Simple Framework to Enhance the Adversarial Robustness of Deep Learning-based Intrusion Detection System
Abstract: Deep learning based intrusion detection systems (DL-based IDS) have emerged
as one of the best choices for providing security solutions against various
network intrusion attacks. However, due to t... | Cryptography and Security |
What field is the article from? | Title: CNL2ASP: converting controlled natural language sentences into ASP
Abstract: Answer Set Programming (ASP) is a popular declarative programming language
for solving hard combinatorial problems. Although ASP has gained widespread
acceptance in academic and industrial contexts, there are certain user groups
who may... | Artificial Intelligence |
What field is the article from? | Title: Combining EEG and NLP Features for Predicting Students' Lecture Comprehension using Ensemble Classification
Abstract: Electroencephalography (EEG) and Natural Language Processing (NLP) can be
applied for education to measure students' comprehension in classroom lectures;
currently, the two measures have been use... | Computational Linguistics |
What field is the article from? | Title: Spoken Word2Vec: A Perspective And Some Techniques
Abstract: Text word embeddings that encode distributional semantic features work by
modeling contextual similarities of frequently occurring words. Acoustic word
embeddings, on the other hand, typically encode low-level phonetic
similarities. Semantic embeddings... | Computational Linguistics |
What field is the article from? | Title: Learning Machine Morality through Experience and Interaction
Abstract: Increasing interest in ensuring safety of next-generation Artificial
Intelligence (AI) systems calls for novel approaches to embedding morality into
autonomous agents. Traditionally, this has been done by imposing explicit
top-down rules or h... | Artificial Intelligence |
What field is the article from? | Title: A Preference Learning Approach to Develop Safe and Personalizable Autonomous Vehicles
Abstract: This work introduces a preference learning method that ensures adherence to
traffic rules for autonomous vehicles. Our approach incorporates priority
ordering of signal temporal logic (STL) formulas, describing traffi... | Artificial Intelligence |
What field is the article from? | Title: Using General Value Functions to Learn Domain-Backed Inventory Management Policies
Abstract: We consider the inventory management problem, where the goal is to balance
conflicting objectives such as availability and wastage of a large range of
products in a store. We propose a reinforcement learning (RL) approac... | Machine Learning |
What field is the article from? | Title: A knowledge-driven AutoML architecture
Abstract: This paper proposes a knowledge-driven AutoML architecture for pipeline and
deep feature synthesis. The main goal is to render the AutoML process
explainable and to leverage domain knowledge in the synthesis of pipelines and
features. The architecture explores sev... | Machine Learning |
What field is the article from? | Title: Visual Hindsight Self-Imitation Learning for Interactive Navigation
Abstract: Interactive visual navigation tasks, which involve following instructions to
reach and interact with specific targets, are challenging not only because
successful experiences are very rare but also because the complex visual inputs
req... | Artificial Intelligence |
What field is the article from? | Title: Robust Few-Shot Named Entity Recognition with Boundary Discrimination and Correlation Purification
Abstract: Few-shot named entity recognition (NER) aims to recognize novel named
entities in low-resource domains utilizing existing knowledge. However, the
present few-shot NER models assume that the labeled data a... | Computational Linguistics |
What field is the article from? | Title: VMC: Video Motion Customization using Temporal Attention Adaption for Text-to-Video Diffusion Models
Abstract: Text-to-video diffusion models have advanced video generation significantly.
However, customizing these models to generate videos with tailored motions
presents a substantial challenge. In specific, the... | Computer Vision |
What field is the article from? | Title: Formal concept analysis for evaluating intrinsic dimension of a natural language
Abstract: Some results of a computational experiment for determining the intrinsic
dimension of linguistic varieties for the Bengali and Russian languages are
presented. At the same time, both sets of words and sets of bigrams in th... | Computational Linguistics |
What field is the article from? | Title: Learn to Categorize or Categorize to Learn? Self-Coding for Generalized Category Discovery
Abstract: In the quest for unveiling novel categories at test time, we confront the
inherent limitations of traditional supervised recognition models that are
restricted by a predefined category set. While strides have bee... | Computer Vision |
What field is the article from? | Title: Deep Bayesian Reinforcement Learning for Spacecraft Proximity Maneuvers and Docking
Abstract: In the pursuit of autonomous spacecraft proximity maneuvers and docking(PMD),
we introduce a novel Bayesian actor-critic reinforcement learning algorithm to
learn a control policy with the stability guarantee. The PMD t... | Robotics |
What field is the article from? | Title: Small Dataset, Big Gains: Enhancing Reinforcement Learning by Offline Pre-Training with Model Based Augmentation
Abstract: Offline reinforcement learning leverages pre-collected datasets of
transitions to train policies. It can serve as effective initialization for
online algorithms, enhancing sample efficiency ... | Machine Learning |
What field is the article from? | Title: Causal Interpretation of Self-Attention in Pre-Trained Transformers
Abstract: We propose a causal interpretation of self-attention in the Transformer
neural network architecture. We interpret self-attention as a mechanism that
estimates a structural equation model for a given input sequence of symbols
(tokens). ... | Artificial Intelligence |
What field is the article from? | Title: Multitask Kernel-based Learning with First-Order Logic Constraints
Abstract: In this paper we propose a general framework to integrate supervised and
unsupervised examples with background knowledge expressed by a collection of
first-order logic clauses into kernel machines. In particular, we consider a
multi-tas... | Machine Learning |
What field is the article from? | Title: Classifying patient voice in social media data using neural networks: A comparison of AI models on different data sources and therapeutic domains
Abstract: It is essential that healthcare professionals and members of the healthcare
community can access and easily understand patient experiences in the real
world,... | Computational Linguistics |
What field is the article from? | Title: Towards a Gateway for Knowledge Graph Schemas Collection, Analysis, and Embedding
Abstract: One of the significant barriers to the training of statistical models on
knowledge graphs is the difficulty that scientists have in finding the best
input data to address their prediction goal. In addition to this, a key
... | Artificial Intelligence |
What field is the article from? | Title: DreamComposer: Controllable 3D Object Generation via Multi-View Conditions
Abstract: Utilizing pre-trained 2D large-scale generative models, recent works are
capable of generating high-quality novel views from a single in-the-wild image.
However, due to the lack of information from multiple views, these works
en... | Computer Vision |
What field is the article from? | Title: Advancing AI Audits for Enhanced AI Governance
Abstract: As artificial intelligence (AI) is integrated into various services and
systems in society, many companies and organizations have proposed AI
principles, policies, and made the related commitments. Conversely, some have
proposed the need for independent au... | Computers and Society |
What field is the article from? | Title: Robust Offline Policy Evaluation and Optimization with Heavy-Tailed Rewards
Abstract: This paper endeavors to augment the robustness of offline reinforcement
learning (RL) in scenarios laden with heavy-tailed rewards, a prevalent
circumstance in real-world applications. We propose two algorithmic frameworks,
ROA... | Machine Learning |
What field is the article from? | Title: Prompt Engineering-assisted Malware Dynamic Analysis Using GPT-4
Abstract: Dynamic analysis methods effectively identify shelled, wrapped, or obfuscated
malware, thereby preventing them from invading computers. As a significant
representation of dynamic malware behavior, the API (Application Programming
Interfac... | Cryptography and Security |
What field is the article from? | Title: Practical Estimation of Ensemble Accuracy
Abstract: Ensemble learning combines several individual models to obtain better
generalization performance. In this work we present a practical method for
estimating the joint power of several classifiers which differs from existing
approaches by {\em not relying on labe... | Artificial Intelligence |
What field is the article from? | Title: The Hyperdimensional Transform for Distributional Modelling, Regression and Classification
Abstract: Hyperdimensional computing (HDC) is an increasingly popular computing
paradigm with immense potential for future intelligent applications. Although
the main ideas already took form in the 1990s, HDC recently gain... | Machine Learning |
What field is the article from? | Title: Are We Falling in a Middle-Intelligence Trap? An Analysis and Mitigation of the Reversal Curse
Abstract: Recent studies have highlighted a phenomenon in large language models (LLMs)
known as "the reversal curse," in which the order of knowledge entities in the
training data biases the models' comprehension. For ... | Computational Linguistics |
What field is the article from? | Title: The Potential of Wearable Sensors for Assessing Patient Acuity in Intensive Care Unit (ICU)
Abstract: Acuity assessments are vital in critical care settings to provide timely
interventions and fair resource allocation. Traditional acuity scores rely on
manual assessments and documentation of physiological states... | Machine Learning |
What field is the article from? | Title: Task-Distributionally Robust Data-Free Meta-Learning
Abstract: Data-Free Meta-Learning (DFML) aims to efficiently learn new tasks by
leveraging multiple pre-trained models without requiring their original
training data. Existing inversion-based DFML methods construct pseudo tasks
from a learnable dataset, which ... | Machine Learning |
What field is the article from? | Title: LongBoX: Evaluating Transformers on Long-Sequence Clinical Tasks
Abstract: Many large language models (LLMs) for medicine have largely been evaluated on
short texts, and their ability to handle longer sequences such as a complete
electronic health record (EHR) has not been systematically explored. Assessing
thes... | Computational Linguistics |
What field is the article from? | Title: The Impact of Preference Agreement in Reinforcement Learning from Human Feedback: A Case Study in Summarization
Abstract: Reinforcement Learning from Human Feedback (RLHF) can be used to capture
complex and nuanced properties of text generation quality. As a result, the
task of text summarization has been identi... | Computational Linguistics |
What field is the article from? | Title: From Indeterminacy to Determinacy: Augmenting Logical Reasoning Capabilities with Large Language Models
Abstract: Recent advances in LLMs have revolutionized the landscape of reasoning tasks.
To enhance the capabilities of LLMs to emulate human reasoning, prior works
focus on modeling reasoning steps using speci... | Artificial Intelligence |
What field is the article from? | Title: Prompt-based Logical Semantics Enhancement for Implicit Discourse Relation Recognition
Abstract: Implicit Discourse Relation Recognition (IDRR), which infers discourse
relations without the help of explicit connectives, is still a crucial and
challenging task for discourse parsing. Recent works tend to exploit t... | Computational Linguistics |
What field is the article from? | Title: Exploring the Robustness of Model-Graded Evaluations and Automated Interpretability
Abstract: There has been increasing interest in evaluations of language models for a
variety of risks and characteristics. Evaluations relying on natural language
understanding for grading can often be performed at scale by using... | Computational Linguistics |
What field is the article from? | Title: Addressing Membership Inference Attack in Federated Learning with Model Compression
Abstract: Federated Learning (FL) has been proposed as a privacy-preserving solution
for machine learning. However, recent works have shown that Federated Learning
can leak private client data through membership attacks. In this ... | Machine Learning |
What field is the article from? | Title: A Graph-to-Text Approach to Knowledge-Grounded Response Generation in Human-Robot Interaction
Abstract: Knowledge graphs are often used to represent structured information in a
flexible and efficient manner, but their use in situated dialogue remains
under-explored. This paper presents a novel conversational mod... | Robotics |
What field is the article from? | Title: Kandinsky Conformal Prediction: Efficient Calibration of Image Segmentation Algorithms
Abstract: Image segmentation algorithms can be understood as a collection of pixel
classifiers, for which the outcomes of nearby pixels are correlated. Classifier
models can be calibrated using Inductive Conformal Prediction, ... | Computer Vision |
What field is the article from? | Title: CZL-CIAE: CLIP-driven Zero-shot Learning for Correcting Inverse Age Estimation
Abstract: Zero-shot age estimation aims to learn feature information about age from
input images and make inferences about a given person's image or video frame
without specific sample data. The development of zero-shot age estimation... | Computer Vision |
What field is the article from? | Title: Labels Need Prompts Too: Mask Matching for Natural Language Understanding Tasks
Abstract: Textual label names (descriptions) are typically semantically rich in many
natural language understanding (NLU) tasks. In this paper, we incorporate the
prompting methodology, which is widely used to enrich model input, int... | Computational Linguistics |
What field is the article from? | Title: Boosting LLM Reasoning: Push the Limits of Few-shot Learning with Reinforced In-Context Pruning
Abstract: Large language models (LLMs) have shown impressive capabilities in various
tasks, yet they still struggle with math reasoning. Despite efforts to optimize
Chain-of-Thoughts (CoT) prompts and fine-tune LLMs, ... | Computational Linguistics |
What field is the article from? | Title: Temporal Supervised Contrastive Learning for Modeling Patient Risk Progression
Abstract: We consider the problem of predicting how the likelihood of an outcome of
interest for a patient changes over time as we observe more of the patient
data. To solve this problem, we propose a supervised contrastive learning
f... | Machine Learning |
What field is the article from? | Title: Introducing NCL-SM: A Fully Annotated Dataset of Images from Human Skeletal Muscle Biopsies
Abstract: Single cell analysis of skeletal muscle (SM) tissue is a fundamental tool for
understanding many neuromuscular disorders. For this analysis to be reliable
and reproducible, identification of individual fibres wi... | Computer Vision |
What field is the article from? | Title: No Prior Mask: Eliminate Redundant Action for Deep Reinforcement Learning
Abstract: The large action space is one fundamental obstacle to deploying Reinforcement
Learning methods in the real world. The numerous redundant actions will cause
the agents to make repeated or invalid attempts, even leading to task fai... | Machine Learning |
What field is the article from? | Title: GLOP: Learning Global Partition and Local Construction for Solving Large-scale Routing Problems in Real-time
Abstract: The recent end-to-end neural solvers have shown promise for small-scale
routing problems but suffered from limited real-time scaling-up performance.
This paper proposes GLOP (Global and Local Op... | Artificial Intelligence |
What field is the article from? | Title: Classification of Human- and AI-Generated Texts for English, French, German, and Spanish
Abstract: In this paper we analyze features to classify human- and AI-generated text
for English, French, German and Spanish and compare them across languages. We
investigate two scenarios: (1) The detection of text generate... | Computational Linguistics |
What field is the article from? | Title: Amodal Optical Flow
Abstract: Optical flow estimation is very challenging in situations with transparent or
occluded objects. In this work, we address these challenges at the task level
by introducing Amodal Optical Flow, which integrates optical flow with amodal
perception. Instead of only representing the visi... | Computer Vision |
What field is the article from? | Title: ViR: Vision Retention Networks
Abstract: Vision Transformers (ViTs) have attracted a lot of popularity in recent
years, due to their exceptional capabilities in modeling long-range spatial
dependencies and scalability for large scale training. Although the training
parallelism of self-attention mechanism plays a... | Computer Vision |
What field is the article from? | Title: Attention Lens: A Tool for Mechanistically Interpreting the Attention Head Information Retrieval Mechanism
Abstract: Transformer-based Large Language Models (LLMs) are the state-of-the-art for
natural language tasks. Recent work has attempted to decode, by reverse
engineering the role of linear layers, the inter... | Computational Linguistics |
What field is the article from? | Title: Uncertainty in Additive Feature Attribution methods
Abstract: In this work, we explore various topics that fall under the umbrella of
Uncertainty in post-hoc Explainable AI (XAI) methods. We in particular focus on
the class of additive feature attribution explanation methods. We first
describe our specifications... | Machine Learning |
What field is the article from? | Title: Towards Autonomous Hypothesis Verification via Language Models with Minimal Guidance
Abstract: Research automation efforts usually employ AI as a tool to automate specific
tasks within the research process. To create an AI that truly conduct research
themselves, it must independently generate hypotheses, design ... | Artificial Intelligence |
What field is the article from? | Title: Score Normalization for a Faster Diffusion Exponential Integrator Sampler
Abstract: Recently, Zhang et al. have proposed the Diffusion Exponential Integrator
Sampler (DEIS) for fast generation of samples from Diffusion Models. It
leverages the semi-linear nature of the probability flow ordinary differential
equa... | Machine Learning |
What field is the article from? | Title: Multitask Multimodal Prompted Training for Interactive Embodied Task Completion
Abstract: Interactive and embodied tasks pose at least two fundamental challenges to
existing Vision & Language (VL) models, including 1) grounding language in
trajectories of actions and observations, and 2) referential disambiguati... | Machine Learning |
What field is the article from? | Title: Fine-tuning Language Models for Factuality
Abstract: The fluency and creativity of large pre-trained language models (LLMs) have
led to their widespread use, sometimes even as a replacement for traditional
search engines. Yet language models are prone to making convincing but
factually inaccurate claims, often r... | Computational Linguistics |
What field is the article from? | Title: Towards Few-Annotation Learning in Computer Vision: Application to Image Classification and Object Detection tasks
Abstract: In this thesis, we develop theoretical, algorithmic and experimental
contributions for Machine Learning with limited labels, and more specifically
for the tasks of Image Classification and... | Computer Vision |
What field is the article from? | Title: Unnatural Error Correction: GPT-4 Can Almost Perfectly Handle Unnatural Scrambled Text
Abstract: While Large Language Models (LLMs) have achieved remarkable performance in
many tasks, much about their inner workings remains unclear. In this study, we
present novel experimental insights into the resilience of LLM... | Computational Linguistics |
What field is the article from? | Title: E-CORE: Emotion Correlation Enhanced Empathetic Dialogue Generation
Abstract: Achieving empathy is a crucial step toward humanized dialogue systems.
Current approaches for empathetic dialogue generation mainly perceive an
emotional label to generate an empathetic response conditioned on it, which
simply treat em... | Computational Linguistics |
What field is the article from? | Title: Towards More Likely Models for AI Planning
Abstract: This is the first work to look at the application of large language models
(LLMs) for the purpose of model space edits in automated planning tasks. To set
the stage for this sangam, we explore two different flavors of model space
problems that have been studie... | Artificial Intelligence |
What field is the article from? | Title: BoschAI @ Causal News Corpus 2023: Robust Cause-Effect Span Extraction using Multi-Layer Sequence Tagging and Data Augmentation
Abstract: Understanding causality is a core aspect of intelligence. The Event Causality
Identification with Causal News Corpus Shared Task addresses two aspects of
this challenge: Subta... | Computational Linguistics |
What field is the article from? | Title: Hybrid Minimax-MCTS and Difficulty Adjustment for General Game Playing
Abstract: Board games are a great source of entertainment for all ages, as they create
a competitive and engaging environment, as well as stimulating learning and
strategic thinking. It is common for digital versions of board games, as any
ot... | Artificial Intelligence |
What field is the article from? | Title: Fine-Tuning Language Models Using Formal Methods Feedback
Abstract: Although pre-trained language models encode generic knowledge beneficial for
planning and control, they may fail to generate appropriate control policies
for domain-specific tasks. Existing fine-tuning methods use human feedback to
address this ... | Artificial Intelligence |
What field is the article from? | Title: Adversarial Preference Optimization
Abstract: Human preference alignment is a crucial training step to improve the
interaction quality of large language models (LLMs). Existing aligning methods
depend on manually annotated preference data to guide the LLM optimization
directions. However, in practice, continuous... | Computational Linguistics |
What field is the article from? | Title: FakeWatch ElectionShield: A Benchmarking Framework to Detect Fake News for Credible US Elections
Abstract: In today's technologically driven world, the spread of fake news,
particularly during crucial events such as elections, presents an increasing
challenge to the integrity of information. To address this chal... | Computational Linguistics |
What field is the article from? | Title: Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy
Abstract: Entropy and mutual information in neural networks provide rich information on
the learning process, but they have proven difficult to compute reliably in
high dimensions. Indeed, in noisy and high-... | Computer Vision |
What field is the article from? | Title: Unveiling Safety Vulnerabilities of Large Language Models
Abstract: As large language models become more prevalent, their possible harmful or
inappropriate responses are a cause for concern. This paper introduces a unique
dataset containing adversarial examples in the form of questions, which we call
AttaQ, desi... | Computational Linguistics |
What field is the article from? | Title: TencentLLMEval: A Hierarchical Evaluation of Real-World Capabilities for Human-Aligned LLMs
Abstract: Large language models (LLMs) have shown impressive capabilities across
various natural language tasks. However, evaluating their alignment with human
preferences remains a challenge. To this end, we propose a co... | Computational Linguistics |
What field is the article from? | Title: FRAD: Front-Running Attacks Detection on Ethereum using Ternary Classification Model
Abstract: With the evolution of blockchain technology, the issue of transaction
security, particularly on platforms like Ethereum, has become increasingly
critical. Front-running attacks, a unique form of security threat, pose
s... | Cryptography and Security |
What field is the article from? | Title: Analyzing and Improving the Training Dynamics of Diffusion Models
Abstract: Diffusion models currently dominate the field of data-driven image synthesis
with their unparalleled scaling to large datasets. In this paper, we identify
and rectify several causes for uneven and ineffective training in the popular
ADM ... | Computer Vision |
What field is the article from? | Title: Converting and Smoothing False Negatives for Vision-Language Pre-training
Abstract: We consider the critical issue of false negatives in Vision-Language
Pre-training (VLP), a challenge that arises from the inherent many-to-many
correspondence of image-text pairs in large-scale web-crawled datasets. The
presence ... | Computer Vision |
What field is the article from? | Title: Prompt Engineering a Prompt Engineer
Abstract: Prompt engineering is a challenging yet crucial task for optimizing the
performance of large language models (LLMs). It requires complex reasoning to
examine the model's errors, hypothesize what is missing or misleading in the
current prompt, and communicate the tas... | Computational Linguistics |
What field is the article from? | Title: Characterizing Large Language Model Geometry Solves Toxicity Detection and Generation
Abstract: Large Language Models~(LLMs) drive current AI breakthroughs despite very
little being known about their internal representations, e.g., how to extract a
few informative features to solve various downstream tasks. To p... | Artificial Intelligence |
What field is the article from? | Title: BaRDa: A Belief and Reasoning Dataset that Separates Factual Accuracy and Reasoning Ability
Abstract: While there are numerous benchmarks comparing the performance of modern
language models (LMs), end-task evaluations often conflate notions of *factual
accuracy* ("truth") and *reasoning ability* ("rationality", ... | Computational Linguistics |
What field is the article from? | Title: Generalization in medical AI: a perspective on developing scalable models
Abstract: Over the past few years, research has witnessed the advancement of deep
learning models trained on large datasets, some even encompassing millions of
examples. While these impressive performance on their hidden test sets, they
of... | Machine Learning |
What field is the article from? | Title: PatchBMI-Net: Lightweight Facial Patch-based Ensemble for BMI Prediction
Abstract: Due to an alarming trend related to obesity affecting 93.3 million adults in
the United States alone, body mass index (BMI) and body weight have drawn
significant interest in various health monitoring applications. Consequently,
s... | Computer Vision |
What field is the article from? | Title: Enhancing Medical Task Performance in GPT-4V: A Comprehensive Study on Prompt Engineering Strategies
Abstract: OpenAI's latest large vision-language model (LVLM), GPT-4V(ision), has piqued
considerable interest for its potential in medical applications. Despite its
promise, recent studies and internal reviews hi... | Computational Linguistics |
What field is the article from? | Title: Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback
Abstract: In this work, we study the low-rank MDPs with adversarially changed losses in
the full-information feedback setting. In particular, the unknown transition
probability kernel admits a low-rank m... | Machine Learning |
What field is the article from? | Title: MONET: Modality-Embracing Graph Convolutional Network and Target-Aware Attention for Multimedia Recommendation
Abstract: In this paper, we focus on multimedia recommender systems using graph
convolutional networks (GCNs) where the multimodal features as well as
user-item interactions are employed together. Our s... | Information Retrieval |
What field is the article from? | Title: Bias-Variance Trade-off in Physics-Informed Neural Networks with Randomized Smoothing for High-Dimensional PDEs
Abstract: While physics-informed neural networks (PINNs) have been proven effective for
low-dimensional partial differential equations (PDEs), the computational cost
remains a hurdle in high-dimensiona... | Machine Learning |
What field is the article from? | Title: Kindness in Multi-Agent Reinforcement Learning
Abstract: In human societies, people often incorporate fairness in their decisions and
treat reciprocally by being kind to those who act kindly. They evaluate the
kindness of others' actions not only by monitoring the outcomes but also by
considering the intentions.... | Artificial Intelligence |
What field is the article from? | Title: Two-Stage Predict+Optimize for Mixed Integer Linear Programs with Unknown Parameters in Constraints
Abstract: Consider the setting of constrained optimization, with some parameters
unknown at solving time and requiring prediction from relevant features.
Predict+Optimize is a recent framework for end-to-end train... | Artificial Intelligence |
What field is the article from? | Title: Improved Anonymous Multi-Agent Path Finding Algorithm
Abstract: We consider an Anonymous Multi-Agent Path-Finding (AMAPF) problem where the
set of agents is confined to a graph, a set of goal vertices is given and each
of these vertices has to be reached by some agent. The problem is to find an
assignment of the... | Artificial Intelligence |
What field is the article from? | Title: On the stability, correctness and plausibility of visual explanation methods based on feature importance
Abstract: In the field of Explainable AI, multiples evaluation metrics have been
proposed in order to assess the quality of explanation methods w.r.t. a set of
desired properties. In this work, we study the a... | Computer Vision |
What field is the article from? | Title: JudgeLM: Fine-tuned Large Language Models are Scalable Judges
Abstract: Evaluating Large Language Models (LLMs) in open-ended scenarios is
challenging because existing benchmarks and metrics can not measure them
comprehensively. To address this problem, we propose to fine-tune LLMs as
scalable judges (JudgeLM) t... | Computational Linguistics |
What field is the article from? | Title: Positional Description Matters for Transformers Arithmetic
Abstract: Transformers, central to the successes in modern Natural Language Processing,
often falter on arithmetic tasks despite their vast capabilities --which
paradoxically include remarkable coding abilities. We observe that a crucial
challenge is the... | Computational Linguistics |
What field is the article from? | Title: Rethinking and Improving Multi-task Learning for End-to-end Speech Translation
Abstract: Significant improvements in end-to-end speech translation (ST) have been
achieved through the application of multi-task learning. However, the extent to
which auxiliary tasks are highly consistent with the ST task, and how m... | Computational Linguistics |
What field is the article from? | Title: Image Transformation for IoT Time-Series Data: A Review
Abstract: In the era of the Internet of Things (IoT), where smartphones, built-in
systems, wireless sensors, and nearly every smart device connect through local
networks or the internet, billions of smart things communicate with each other
and generate vast... | Machine Learning |
What field is the article from? | Title: When does In-context Learning Fall Short and Why? A Study on Specification-Heavy Tasks
Abstract: In-context learning (ICL) has become the default method for using large
language models (LLMs), making the exploration of its limitations and
understanding the underlying causes crucial. In this paper, we find that I... | Computational Linguistics |
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