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What field is the article from? | Title: The Innovation-to-Occupations Ontology: Linking Business Transformation Initiatives to Occupations and Skills
Abstract: The fast adoption of new technologies forces companies to continuously adapt
their operations making it harder to predict workforce requirements. Several
recent studies have attempted to predic... | Artificial Intelligence |
What field is the article from? | Title: A trainable manifold for accurate approximation with ReLU Networks
Abstract: We present a novel technique for exercising greater control of the weights of
ReLU activated neural networks to produce more accurate function
approximations. Many theoretical works encode complex operations into ReLU
networks using sma... | Machine Learning |
What field is the article from? | Title: Development of a Legal Document AI-Chatbot
Abstract: With the exponential growth of digital data and the increasing complexity of
legal documentation, there is a pressing need for efficient and intelligent
tools to streamline the handling of legal documents.With the recent
developments in the AI field, especiall... | Artificial Intelligence |
What field is the article from? | Title: NPCL: Neural Processes for Uncertainty-Aware Continual Learning
Abstract: Continual learning (CL) aims to train deep neural networks efficiently on
streaming data while limiting the forgetting caused by new tasks. However,
learning transferable knowledge with less interference between tasks is
difficult, and rea... | Machine Learning |
What field is the article from? | Title: Dense Retrieval as Indirect Supervision for Large-space Decision Making
Abstract: Many discriminative natural language understanding (NLU) tasks have large
label spaces. Learning such a process of large-space decision making is
particularly challenging due to the lack of training instances per label and
the diff... | Computational Linguistics |
What field is the article from? | Title: Input Reconstruction Attack against Vertical Federated Large Language Models
Abstract: Recently, large language models (LLMs) have drawn extensive attention from
academia and the public, due to the advent of the ChatGPT. While LLMs show
their astonishing ability in text generation for various tasks, privacy
conc... | Computational Linguistics |
What field is the article from? | Title: GlitchBench: Can large multimodal models detect video game glitches?
Abstract: Large multimodal models (LMMs) have evolved from large language models (LLMs)
to integrate multiple input modalities, such as visual inputs. This integration
augments the capacity of LLMs for tasks requiring visual comprehension and
r... | Computer Vision |
What field is the article from? | Title: Game Solving with Online Fine-Tuning
Abstract: Game solving is a similar, yet more difficult task than mastering a game.
Solving a game typically means to find the game-theoretic value (outcome given
optimal play), and optionally a full strategy to follow in order to achieve
that outcome. The AlphaZero algorithm... | Artificial Intelligence |
What field is the article from? | Title: Self-Evaluation Improves Selective Generation in Large Language Models
Abstract: Safe deployment of large language models (LLMs) may benefit from a reliable
method for assessing their generated content to determine when to abstain or to
selectively generate. While likelihood-based metrics such as perplexity are
... | Computational Linguistics |
What field is the article from? | Title: Fast ODE-based Sampling for Diffusion Models in Around 5 Steps
Abstract: Sampling from diffusion models can be treated as solving the corresponding
ordinary differential equations (ODEs), with the aim of obtaining an accurate
solution with as few number of function evaluations (NFE) as possible.
Recently, variou... | Computer Vision |
What field is the article from? | Title: A Review of Digital Twins and their Application in Cybersecurity based on Artificial Intelligence
Abstract: The potential of digital twin technology is yet to be fully realized due to
its diversity and untapped potential. Digital twins enable systems' analysis,
design, optimization, and evolution to be performed... | Cryptography and Security |
What field is the article from? | Title: Extending Neural Network Verification to a Larger Family of Piece-wise Linear Activation Functions
Abstract: In this paper, we extend an available neural network verification technique
to support a wider class of piece-wise linear activation functions.
Furthermore, we extend the algorithms, which provide in thei... | Machine Learning |
What field is the article from? | Title: FinBTech: Blockchain-Based Video and Voice Authentication System for Enhanced Security in Financial Transactions Utilizing FaceNet512 and Gaussian Mixture Models
Abstract: In the digital age, it is crucial to make sure that financial transactions
are as secure and reliable as possible. This abstract offers a gro... | Cryptography and Security |
What field is the article from? | Title: Dynamic Collaborative Filtering for Matrix- and Tensor-based Recommender Systems
Abstract: In production applications of recommender systems, a continuous data flow is
employed to update models in real-time. Many recommender models often require
complete retraining to adapt to new data. In this work, we introduc... | Information Retrieval |
What field is the article from? | Title: Personality of AI
Abstract: This research paper delves into the evolving landscape of fine-tuning large
language models (LLMs) to align with human users, extending beyond basic
alignment to propose "personality alignment" for language models in
organizational settings. Acknowledging the impact of training method... | Human-Computer Interaction |
What field is the article from? | Title: Ontology Revision based on Pre-trained Language Models
Abstract: Ontology revision aims to seamlessly incorporate new information into an
existing ontology and plays a crucial role in tasks such as ontology evolution,
ontology maintenance, and ontology alignment. Similar to repair single
ontologies, resolving lo... | Artificial Intelligence |
What field is the article from? | Title: Towards Adaptive RF Fingerprint-based Authentication of IIoT devices
Abstract: As IoT technologies mature, they are increasingly finding their way into more
sensitive domains, such as Medical and Industrial IoT, in which safety and
cyber-security are of great importance. While the number of deployed IoT
devices ... | Cryptography and Security |
What field is the article from? | Title: Shadows Don't Lie and Lines Can't Bend! Generative Models don't know Projective Geometry...for now
Abstract: Generative models can produce impressively realistic images. This paper
demonstrates that generated images have geometric features different from those
of real images. We build a set of collections of gen... | Computer Vision |
What field is the article from? | Title: Pragmatic Radiology Report Generation
Abstract: When pneumonia is not found on a chest X-ray, should the report describe this
negative observation or omit it? We argue that this question cannot be answered
from the X-ray alone and requires a pragmatic perspective, which captures the
communicative goal that radio... | Computational Linguistics |
What field is the article from? | Title: State-Wise Safe Reinforcement Learning With Pixel Observations
Abstract: In the context of safe exploration, Reinforcement Learning (RL) has long
grappled with the challenges of balancing the tradeoff between maximizing
rewards and minimizing safety violations, particularly in complex environments
with contact-r... | Machine Learning |
What field is the article from? | Title: SA-Attack: Improving Adversarial Transferability of Vision-Language Pre-training Models via Self-Augmentation
Abstract: Current Visual-Language Pre-training (VLP) models are vulnerable to
adversarial examples. These adversarial examples present substantial security
risks to VLP models, as they can leverage inher... | Computer Vision |
What field is the article from? | Title: Weaving Pathways for Justice with GPT: LLM-driven automated drafting of interactive legal applications
Abstract: Can generative AI help us speed up the authoring of tools to help
self-represented litigants?
In this paper, we describe 3 approaches to automating the completion of court
forms: a generative AI app... | Artificial Intelligence |
What field is the article from? | Title: Language Model-In-The-Loop: Data Optimal Approach to Learn-To-Recommend Actions in Text Games
Abstract: Large Language Models (LLMs) have demonstrated superior performance in
language understanding benchmarks. CALM, a popular approach, leverages
linguistic priors of LLMs -- GPT-2 -- for action candidate recommen... | Computational Linguistics |
What field is the article from? | Title: Interpretable Knowledge Tracing via Response Influence-based Counterfactual Reasoning
Abstract: Knowledge tracing (KT) plays a crucial role in computer-aided education and
intelligent tutoring systems, aiming to assess students' knowledge proficiency
by predicting their future performance on new questions based ... | Computers and Society |
What field is the article from? | Title: Generalizable Imitation Learning Through Pre-Trained Representations
Abstract: In this paper we leverage self-supervised vision transformer models and their
emergent semantic abilities to improve the generalization abilities of
imitation learning policies. We introduce BC-ViT, an imitation learning
algorithm tha... | Robotics |
What field is the article from? | Title: MFTCoder: Boosting Code LLMs with Multitask Fine-Tuning
Abstract: Code LLMs have emerged as a specialized research field, with remarkable
studies dedicated to enhancing model's coding capabilities through fine-tuning
on pre-trained models. Previous fine-tuning approaches were typically tailored
to specific downs... | Machine Learning |
What field is the article from? | Title: XFEVER: Exploring Fact Verification across Languages
Abstract: This paper introduces the Cross-lingual Fact Extraction and VERification
(XFEVER) dataset designed for benchmarking the fact verification models across
different languages. We constructed it by translating the claim and evidence
texts of the Fact Ext... | Computational Linguistics |
What field is the article from? | Title: From Knowledge Representation to Knowledge Organization and Back
Abstract: Knowledge Representation (KR) and facet-analytical Knowledge Organization
(KO) have been the two most prominent methodologies of data and knowledge
modelling in the Artificial Intelligence community and the Information Science
community, ... | Artificial Intelligence |
What field is the article from? | Title: Adversarial Attacks to Reward Machine-based Reinforcement Learning
Abstract: In recent years, Reward Machines (RMs) have stood out as a simple yet
effective automata-based formalism for exposing and exploiting task structure
in reinforcement learning settings. Despite their relevance, little to no
attention has ... | Machine Learning |
What field is the article from? | Title: HKTGNN: Hierarchical Knowledge Transferable Graph Neural Network-based Supply Chain Risk Assessment
Abstract: The strength of a supply chain is an important measure of a country's or
region's technical advancement and overall competitiveness. Establishing supply
chain risk assessment models for effective managem... | Machine Learning |
What field is the article from? | Title: Multi Loss-based Feature Fusion and Top Two Voting Ensemble Decision Strategy for Facial Expression Recognition in the Wild
Abstract: Facial expression recognition (FER) in the wild is a challenging task
affected by the image quality and has attracted broad interest in computer
vision. There is no research using... | Computer Vision |
What field is the article from? | Title: From Heuristic to Analytic: Cognitively Motivated Strategies for Coherent Physical Commonsense Reasoning
Abstract: Pre-trained language models (PLMs) have shown impressive performance in
various language tasks. However, they are prone to spurious correlations, and
often generate illusory information. In real-wor... | Computational Linguistics |
What field is the article from? | Title: Exploring Causal Learning through Graph Neural Networks: An In-depth Review
Abstract: In machine learning, exploring data correlations to predict outcomes is a
fundamental task. Recognizing causal relationships embedded within data is
pivotal for a comprehensive understanding of system dynamics, the significance... | Machine Learning |
What field is the article from? | Title: Bias in Evaluation Processes: An Optimization-Based Model
Abstract: Biases with respect to socially-salient attributes of individuals have been
well documented in evaluation processes used in settings such as admissions and
hiring. We view such an evaluation process as a transformation of a
distribution of the t... | Computers and Society |
What field is the article from? | Title: Vision-Language Integration in Multimodal Video Transformers (Partially) Aligns with the Brain
Abstract: Integrating information from multiple modalities is arguably one of the
essential prerequisites for grounding artificial intelligence systems with an
understanding of the real world. Recent advances in video ... | Computer Vision |
What field is the article from? | Title: Large Knowledge Model: Perspectives and Challenges
Abstract: Humankind's understanding of the world is fundamentally linked to our
perception and cognition, with \emph{human languages} serving as one of the
major carriers of \emph{world knowledge}. In this vein, \emph{Large Language
Models} (LLMs) like ChatGPT e... | Artificial Intelligence |
What field is the article from? | Title: Compensation Sampling for Improved Convergence in Diffusion Models
Abstract: Diffusion models achieve remarkable quality in image generation, but at a
cost. Iterative denoising requires many time steps to produce high fidelity
images. We argue that the denoising process is crucially limited by an
accumulation of... | Computer Vision |
What field is the article from? | Title: Fingerprint Matching with Localized Deep Representation
Abstract: Compared to minutia-based fingerprint representations, fixed-length
representations are attractive due to simple and efficient matching. However,
fixed-length fingerprint representations are limited in accuracy when matching
fingerprints with diff... | Computer Vision |
What field is the article from? | Title: Neural Lattice Reduction: A Self-Supervised Geometric Deep Learning Approach
Abstract: Lattice reduction is a combinatorial optimization problem aimed at finding
the most orthogonal basis in a given lattice. In this work, we address lattice
reduction via deep learning methods. We design a deep neural model outpu... | Machine Learning |
What field is the article from? | Title: An Evaluation Framework for Mapping News Headlines to Event Classes in a Knowledge Graph
Abstract: Mapping ongoing news headlines to event-related classes in a rich knowledge
base can be an important component in a knowledge-based event analysis and
forecasting solution. In this paper, we present a methodology f... | Computational Linguistics |
What field is the article from? | Title: Artificial Intelligence Studies in Cartography: A Review and Synthesis of Methods, Applications, and Ethics
Abstract: The past decade has witnessed the rapid development of geospatial artificial
intelligence (GeoAI) primarily due to the ground-breaking achievements in deep
learning and machine learning. A growin... | Human-Computer Interaction |
What field is the article from? | Title: Towards Sample-specific Backdoor Attack with Clean Labels via Attribute Trigger
Abstract: Currently, sample-specific backdoor attacks (SSBAs) are the most advanced and
malicious methods since they can easily circumvent most of the current backdoor
defenses. In this paper, we reveal that SSBAs are not sufficientl... | Cryptography and Security |
What field is the article from? | Title: Castor: Causal Temporal Regime Structure Learning
Abstract: The task of uncovering causal relationships among multivariate time series
data stands as an essential and challenging objective that cuts across a broad
array of disciplines ranging from climate science to healthcare. Such data
entails linear or non-li... | Machine Learning |
What field is the article from? | Title: HetGPT: Harnessing the Power of Prompt Tuning in Pre-Trained Heterogeneous Graph Neural Networks
Abstract: Graphs have emerged as a natural choice to represent and analyze the
intricate patterns and rich information of the Web, enabling applications such
as online page classification and social recommendation. T... | Machine Learning |
What field is the article from? | Title: Cooperative AI via Decentralized Commitment Devices
Abstract: Credible commitment devices have been a popular approach for robust
multi-agent coordination. However, existing commitment mechanisms face
limitations like privacy, integrity, and susceptibility to mediator or user
strategic behavior. It is unclear if... | Artificial Intelligence |
What field is the article from? | Title: Variational Autoencoders for Feature Exploration and Malignancy Prediction of Lung Lesions
Abstract: Lung cancer is responsible for 21% of cancer deaths in the UK and five-year
survival rates are heavily influenced by the stage the cancer was identified
at. Recent studies have demonstrated the capability of AI m... | Computer Vision |
What field is the article from? | Title: Non-Autoregressive Diffusion-based Temporal Point Processes for Continuous-Time Long-Term Event Prediction
Abstract: Continuous-time long-term event prediction plays an important role in many
application scenarios. Most existing works rely on autoregressive frameworks to
predict event sequences, which suffer fro... | Machine Learning |
What field is the article from? | Title: Diversify, Don't Fine-Tune: Scaling Up Visual Recognition Training with Synthetic Images
Abstract: Recent advances in generative deep learning have enabled the creation of
high-quality synthetic images in text-to-image generation. Prior work shows
that fine-tuning a pretrained diffusion model on ImageNet and gen... | Computer Vision |
What field is the article from? | Title: Can Large Language Models Serve as Rational Players in Game Theory? A Systematic Analysis
Abstract: Game theory, as an analytical tool, is frequently utilized to analyze human
behavior in social science research. With the high alignment between the
behavior of Large Language Models (LLMs) and humans, a promising... | Artificial Intelligence |
What field is the article from? | Title: Cone Ranking for Multi-Criteria Decision Making
Abstract: Recently introduced cone distribution functions from statistics are turned
into multi-criteria decision making (MCDM) tools. It is demonstrated that this
procedure can be considered as an upgrade of the weighted sum scalarization
insofar as it absorbs a w... | Artificial Intelligence |
What field is the article from? | Title: Wired Perspectives: Multi-View Wire Art Embraces Generative AI
Abstract: Creating multi-view wire art (MVWA), a static 3D sculpture with diverse
interpretations from different viewpoints, is a complex task even for skilled
artists. In response, we present DreamWire, an AI system enabling everyone to
craft MVWA e... | Computer Vision |
What field is the article from? | Title: Deep Learning-Based Object Detection in Maritime Unmanned Aerial Vehicle Imagery: Review and Experimental Comparisons
Abstract: With the advancement of maritime unmanned aerial vehicles (UAVs) and deep
learning technologies, the application of UAV-based object detection has become
increasingly significant in the... | Computer Vision |
What field is the article from? | Title: Coherent Entity Disambiguation via Modeling Topic and Categorical Dependency
Abstract: Previous entity disambiguation (ED) methods adopt a discriminative paradigm,
where prediction is made based on matching scores between mention context and
candidate entities using length-limited encoders. However, these method... | Computational Linguistics |
What field is the article from? | Title: Graph-based Prediction and Planning Policy Network (GP3Net) for scalable self-driving in dynamic environments using Deep Reinforcement Learning
Abstract: Recent advancements in motion planning for Autonomous Vehicles (AVs) show
great promise in using expert driver behaviors in non-stationary driving
environments... | Artificial Intelligence |
What field is the article from? | Title: DeepLearningBrasil@LT-EDI-2023: Exploring Deep Learning Techniques for Detecting Depression in Social Media Text
Abstract: In this paper, we delineate the strategy employed by our team,
DeepLearningBrasil, which secured us the first place in the shared task
DepSign-LT-EDI@RANLP-2023, achieving a 47.0% Macro F1-S... | Computational Linguistics |
What field is the article from? | Title: UniTeam: Open Vocabulary Mobile Manipulation Challenge
Abstract: This report introduces our UniTeam agent - an improved baseline for the
"HomeRobot: Open Vocabulary Mobile Manipulation" challenge. The challenge poses
problems of navigation in unfamiliar environments, manipulation of novel
objects, and recognitio... | Robotics |
What field is the article from? | Title: IG Captioner: Information Gain Captioners are Strong Zero-shot Classifiers
Abstract: Generative training has been demonstrated to be powerful for building
visual-language models. However, on zero-shot discriminative benchmarks, there
is still a performance gap between models trained with generative and
discrimin... | Computer Vision |
What field is the article from? | Title: WAVER: Writing-style Agnostic Video Retrieval via Distilling Vision-Language Models Through Open-Vocabulary Knowledge
Abstract: Text-video retrieval, a prominent sub-field within the broader domain of
multimedia content management, has witnessed remarkable growth and innovation
over the past decade. However, exi... | Computer Vision |
What field is the article from? | Title: Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models
Abstract: Language models have shown promise in various tasks but can be affected by
undesired data during training, fine-tuning, or alignment. For example, if some
unsafe conversations are wrongly annotated as ... | Machine Learning |
What field is the article from? | Title: The Case for Scalable, Data-Driven Theory: A Paradigm for Scientific Progress in NLP
Abstract: I propose a paradigm for scientific progress in NLP centered around
developing scalable, data-driven theories of linguistic structure. The idea is
to collect data in tightly scoped, carefully defined ways which allow f... | Computational Linguistics |
What field is the article from? | Title: The Hidden Linear Structure in Score-Based Models and its Application
Abstract: Score-based models have achieved remarkable results in the generative
modeling of many domains. By learning the gradient of smoothed data
distribution, they can iteratively generate samples from complex distribution
e.g. natural imag... | Artificial Intelligence |
What field is the article from? | Title: Multi Time Scale World Models
Abstract: Intelligent agents use internal world models to reason and make predictions
about different courses of their actions at many scales. Devising learning
paradigms and architectures that allow machines to learn world models that
operate at multiple levels of temporal abstract... | Machine Learning |
What field is the article from? | Title: An Improved Transformer-based Model for Detecting Phishing, Spam, and Ham: A Large Language Model Approach
Abstract: Phishing and spam detection is long standing challenge that has been the
subject of much academic research. Large Language Models (LLM) have vast
potential to transform society and provide new and... | Computational Linguistics |
What field is the article from? | Title: SimPSI: A Simple Strategy to Preserve Spectral Information in Time Series Data Augmentation
Abstract: Data augmentation is a crucial component in training neural networks to
overcome the limitation imposed by data size, and several techniques have been
studied for time series. Although these techniques are effec... | Machine Learning |
What field is the article from? | Title: Sequential Planning in Large Partially Observable Environments guided by LLMs
Abstract: Sequential planning in large state space and action space quickly becomes
intractable due to combinatorial explosion of the search space. Heuristic
methods, like monte-carlo tree search, though effective for large state space... | Artificial Intelligence |
What field is the article from? | Title: Quantum learning and essential cognition under the traction of meta-characteristics in an open world
Abstract: Artificial intelligence has made significant progress in the Close World
problem, being able to accurately recognize old knowledge through training and
classification. However, AI faces significant chal... | Artificial Intelligence |
What field is the article from? | Title: Evaluative Item-Contrastive Explanations in Rankings
Abstract: The remarkable success of Artificial Intelligence in advancing automated
decision-making is evident both in academia and industry. Within the plethora
of applications, ranking systems hold significant importance in various
domains. This paper advocat... | Information Retrieval |
What field is the article from? | Title: SAGE: Smart home Agent with Grounded Execution
Abstract: This article introduces SAGE (Smart home Agent with Grounded Execution), a
framework designed to maximize the flexibility of smart home assistants by
replacing manually-defined inference logic with an LLM-powered autonomous agent
system. SAGE integrates in... | Artificial Intelligence |
What field is the article from? | Title: Performance Trade-offs of Watermarking Large Language Models
Abstract: Amidst growing concerns of large language models (LLMs) being misused for
generating misinformation or completing homework assignments, watermarking has
emerged as an effective solution for distinguishing human-written and
LLM-generated text.... | Computational Linguistics |
What field is the article from? | Title: VideoLCM: Video Latent Consistency Model
Abstract: Consistency models have demonstrated powerful capability in efficient image
generation and allowed synthesis within a few sampling steps, alleviating the
high computational cost in diffusion models. However, the consistency model in
the more challenging and reso... | Computer Vision |
What field is the article from? | Title: Transforming organic chemistry research paradigms: moving from manual efforts to the intersection of automation and artificial intelligence
Abstract: Organic chemistry is undergoing a major paradigm shift, moving from a
labor-intensive approach to a new era dominated by automation and artificial
intelligence (AI... | Artificial Intelligence |
What field is the article from? | Title: Career Path Prediction using Resume Representation Learning and Skill-based Matching
Abstract: The impact of person-job fit on job satisfaction and performance is widely
acknowledged, which highlights the importance of providing workers with next
steps at the right time in their career. This task of predicting t... | Computational Linguistics |
What field is the article from? | Title: A Foundational Framework and Methodology for Personalized Early and Timely Diagnosis
Abstract: Early diagnosis of diseases holds the potential for deep transformation in
healthcare by enabling better treatment options, improving long-term survival
and quality of life, and reducing overall cost. With the advent o... | Machine Learning |
What field is the article from? | Title: MuST: Multimodal Spatiotemporal Graph-Transformer for Hospital Readmission Prediction
Abstract: Hospital readmission prediction is considered an essential approach to
decreasing readmission rates, which is a key factor in assessing the quality
and efficacy of a healthcare system. Previous studies have extensivel... | Machine Learning |
What field is the article from? | Title: MetaSymNet: A Dynamic Symbolic Regression Network Capable of Evolving into Arbitrary Formulations
Abstract: Mathematical formulas serve as the means of communication between humans and
nature, encapsulating the operational laws governing natural phenomena. The
concise formulation of these laws is a crucial objec... | Machine Learning |
What field is the article from? | Title: Aggregate, Decompose, and Fine-Tune: A Simple Yet Effective Factor-Tuning Method for Vision Transformer
Abstract: Recent advancements have illuminated the efficacy of some
tensorization-decomposition Parameter-Efficient Fine-Tuning methods like LoRA
and FacT in the context of Vision Transformers (ViT). However, ... | Computer Vision |
What field is the article from? | Title: Privacy-Aware Document Visual Question Answering
Abstract: Document Visual Question Answering (DocVQA) is a fast growing branch of
document understanding. Despite the fact that documents contain sensitive or
copyrighted information, none of the current DocVQA methods offers strong
privacy guarantees.
In this w... | Computer Vision |
What field is the article from? | Title: New Epochs in AI Supervision: Design and Implementation of an Autonomous Radiology AI Monitoring System
Abstract: With the increasingly widespread adoption of AI in healthcare, maintaining
the accuracy and reliability of AI models in clinical practice has become
crucial. In this context, we introduce novel metho... | Artificial Intelligence |
What field is the article from? | Title: Linear Mode Connectivity in Sparse Neural Networks
Abstract: With the rise in interest of sparse neural networks, we study how neural
network pruning with synthetic data leads to sparse networks with unique
training properties. We find that distilled data, a synthetic summarization of
the real data, paired with ... | Machine Learning |
What field is the article from? | Title: Bridging the Gap: A Unified Video Comprehension Framework for Moment Retrieval and Highlight Detection
Abstract: Video Moment Retrieval (MR) and Highlight Detection (HD) have attracted
significant attention due to the growing demand for video analysis. Recent
approaches treat MR and HD as similar video grounding... | Computer Vision |
What field is the article from? | Title: User Persona Identification and New Service Adaptation Recommendation
Abstract: Providing a personalized user experience on information dense webpages helps
users in reaching their end-goals sooner. We explore an automated approach to
identifying user personas by leveraging high dimensional trajectory informatio... | Information Retrieval |
What field is the article from? | Title: Towards Learning a Generalist Model for Embodied Navigation
Abstract: Building a generalist agent that can interact with the world is the
intriguing target of AI systems, thus spurring the research for embodied
navigation, where an agent is required to navigate according to instructions or
respond to queries. De... | Computer Vision |
What field is the article from? | Title: Automated Process Planning Based on a Semantic Capability Model and SMT
Abstract: In research of manufacturing systems and autonomous robots, the term
capability is used for a machine-interpretable specification of a system
function. Approaches in this research area develop information models that
capture all in... | Artificial Intelligence |
What field is the article from? | Title: Ball Mill Fault Prediction Based on Deep Convolutional Auto-Encoding Network
Abstract: Ball mills play a critical role in modern mining operations, making their
bearing failures a significant concern due to the potential loss of production
efficiency and economic consequences. This paper presents an anomaly dete... | Machine Learning |
What field is the article from? | Title: A density estimation perspective on learning from pairwise human preferences
Abstract: Learning from human feedback (LHF) -- and in particular learning from
pairwise preferences -- has recently become a crucial ingredient in training
large language models (LLMs), and has been the subject of much research. Most
r... | Machine Learning |
What field is the article from? | Title: Deep Tensor Network
Abstract: In this paper, we delve into the foundational principles of tensor
categories, harnessing the universal property of the tensor product to pioneer
novel methodologies in deep network architectures. Our primary contribution is
the introduction of the Tensor Attention and Tensor Intera... | Machine Learning |
What field is the article from? | Title: On The Relationship Between Universal Adversarial Attacks And Sparse Representations
Abstract: The prominent success of neural networks, mainly in computer vision tasks, is
increasingly shadowed by their sensitivity to small, barely perceivable
adversarial perturbations in image input.
In this work, we aim at ... | Computer Vision |
What field is the article from? | Title: Multicoated and Folded Graph Neural Networks with Strong Lottery Tickets
Abstract: The Strong Lottery Ticket Hypothesis (SLTH) demonstrates the existence of
high-performing subnetworks within a randomly initialized model, discoverable
through pruning a convolutional neural network (CNN) without any weight
traini... | Machine Learning |
What field is the article from? | Title: MultiIoT: Towards Large-scale Multisensory Learning for the Internet of Things
Abstract: The Internet of Things (IoT), the network integrating billions of smart
physical devices embedded with sensors, software, and communication
technologies for the purpose of connecting and exchanging data with other
devices an... | Machine Learning |
What field is the article from? | Title: Sparse Training of Discrete Diffusion Models for Graph Generation
Abstract: Generative models for graphs often encounter scalability challenges due to
the inherent need to predict interactions for every node pair. Despite the
sparsity often exhibited by real-world graphs, the unpredictable sparsity
patterns of t... | Machine Learning |
What field is the article from? | Title: Workflow-Guided Response Generation for Task-Oriented Dialogue
Abstract: Task-oriented dialogue (TOD) systems aim to achieve specific goals through
interactive dialogue. Such tasks usually involve following specific workflows,
i.e. executing a sequence of actions in a particular order. While prior work
has focus... | Computational Linguistics |
What field is the article from? | Title: Calibration-free online test-time adaptation for electroencephalography motor imagery decoding
Abstract: Providing a promising pathway to link the human brain with external devices,
Brain-Computer Interfaces (BCIs) have seen notable advancements in decoding
capabilities, primarily driven by increasingly sophisti... | Human-Computer Interaction |
What field is the article from? | Title: AI Alignment and Social Choice: Fundamental Limitations and Policy Implications
Abstract: Aligning AI agents to human intentions and values is a key bottleneck in
building safe and deployable AI applications. But whose values should AI agents
be aligned with? Reinforcement learning with human feedback (RLHF) has... | Artificial Intelligence |
What field is the article from? | Title: Assessing Upper Limb Motor Function in the Immediate Post-Stroke Perioud Using Accelerometry
Abstract: Accelerometry has been extensively studied as an objective means of measuring
upper limb function in patients post-stroke. The objective of this paper is to
determine whether the accelerometry-derived measureme... | Machine Learning |
What field is the article from? | Title: EtiCor: Corpus for Analyzing LLMs for Etiquettes
Abstract: Etiquettes are an essential ingredient of day-to-day interactions among
people. Moreover, etiquettes are region-specific, and etiquettes in one region
might contradict those in other regions. In this paper, we propose EtiCor, an
Etiquettes Corpus, having... | Computational Linguistics |
What field is the article from? | Title: VaQuitA: Enhancing Alignment in LLM-Assisted Video Understanding
Abstract: Recent advancements in language-model-based video understanding have been
progressing at a remarkable pace, spurred by the introduction of Large Language
Models (LLMs). However, the focus of prior research has been predominantly on
devisi... | Computer Vision |
What field is the article from? | Title: Zero-shot Translation of Attention Patterns in VQA Models to Natural Language
Abstract: Converting a model's internals to text can yield human-understandable
insights about the model. Inspired by the recent success of training-free
approaches for image captioning, we propose ZS-A2T, a zero-shot framework that
tr... | Computer Vision |
What field is the article from? | Title: MLLMs-Augmented Visual-Language Representation Learning
Abstract: Visual-language pre-training (VLP) has achieved remarkable success in
multi-modal tasks, largely attributed to the availability of large-scale
image-text datasets. In this work, we demonstrate that multi-modal large
language models (MLLMs) can enh... | Computer Vision |
What field is the article from? | Title: GPT Struct Me: Probing GPT Models on Narrative Entity Extraction
Abstract: The importance of systems that can extract structured information from
textual data becomes increasingly pronounced given the ever-increasing volume
of text produced on a daily basis. Having a system that can effectively extract
such info... | Computational Linguistics |
What field is the article from? | Title: Forbidden Facts: An Investigation of Competing Objectives in Llama-2
Abstract: LLMs often face competing pressures (for example helpfulness vs.
harmlessness). To understand how models resolve such conflicts, we study
Llama-2-chat models on the forbidden fact task. Specifically, we instruct
Llama-2 to truthfully ... | Machine Learning |
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