instruction stringclasses 1
value | input stringlengths 260 2.07k | output stringclasses 10
values |
|---|---|---|
What field is the article from? | Title: Instant3D: Instant Text-to-3D Generation
Abstract: Text-to-3D generation, which aims to synthesize vivid 3D objects from text
prompts, has attracted much attention from the computer vision community. While
several existing works have achieved impressive results for this task, they
mainly rely on a time-consuming... | Computer Vision |
What field is the article from? | Title: Two-Stage Classifier for Campaign Negativity Detection using Axis Embeddings: A Case Study on Tweets of Political Users during 2021 Presidential Election in Iran
Abstract: In elections around the world, the candidates may turn their campaigns toward
negativity due to the prospect of failure and time pressure. In... | Machine Learning |
What field is the article from? | Title: SteloCoder: a Decoder-Only LLM for Multi-Language to Python Code Translation
Abstract: With the recent focus on Large Language Models (LLMs), both StarCoder (Li et
al., 2023) and Code Llama (Rozi\`ere et al., 2023) have demonstrated remarkable
performance in code generation. However, there is still a need for im... | Computational Linguistics |
What field is the article from? | Title: Towards Transferable Multi-modal Perception Representation Learning for Autonomy: NeRF-Supervised Masked AutoEncoder
Abstract: This work proposes a unified self-supervised pre-training framework for
transferable multi-modal perception representation learning via masked
multi-modal reconstruction in Neural Radian... | Computer Vision |
What field is the article from? | Title: Less is More: Learning Reference Knowledge Using No-Reference Image Quality Assessment
Abstract: Image Quality Assessment (IQA) with reference images have achieved great
success by imitating the human vision system, in which the image quality is
effectively assessed by comparing the query image with its pristine... | Computer Vision |
What field is the article from? | Title: Data-Efficient Multimodal Fusion on a Single GPU
Abstract: The goal of multimodal alignment is to learn a single latent space that is
shared between multimodal inputs. The most powerful models in this space have
been trained using massive datasets of paired inputs and large-scale
computational resources, making ... | Machine Learning |
What field is the article from? | Title: SoloPose: One-Shot Kinematic 3D Human Pose Estimation with Video Data Augmentation
Abstract: While recent two-stage many-to-one deep learning models have demonstrated
great success in 3D human pose estimation, such models are inefficient ways to
detect 3D key points in a sequential video relative to one-shot and... | Computer Vision |
What field is the article from? | Title: AVA: Towards Autonomous Visualization Agents through Visual Perception-Driven Decision-Making
Abstract: With recent advances in multi-modal foundation models, the previously
text-only large language models (LLM) have evolved to incorporate visual input,
opening up unprecedented opportunities for various applicat... | Human-Computer Interaction |
What field is the article from? | Title: GeoChat: Grounded Large Vision-Language Model for Remote Sensing
Abstract: Recent advancements in Large Vision-Language Models (VLMs) have shown great
promise in natural image domains, allowing users to hold a dialogue about given
visual content. However, such general-domain VLMs perform poorly for Remote
Sensin... | Computer Vision |
What field is the article from? | Title: Preserving Patient Privacy in MRI Scans: A Comprehensive Approach with 3D Masked Autoencoders
Abstract: MRI scans provide valuable medical information, however they also contain
sensitive and personally identifiable information (PII) that needs to be
protected. Whereas MRI metadata is easily sanitized, MRI image... | Computer Vision |
What field is the article from? | Title: Intelligent Virtual Assistants with LLM-based Process Automation
Abstract: While intelligent virtual assistants like Siri, Alexa, and Google Assistant
have become ubiquitous in modern life, they still face limitations in their
ability to follow multi-step instructions and accomplish complex goals
articulated in ... | Machine Learning |
What field is the article from? | Title: Charting New Territories: Exploring the Geographic and Geospatial Capabilities of Multimodal LLMs
Abstract: Multimodal large language models (MLLMs) have shown remarkable capabilities
across a broad range of tasks but their knowledge and abilities in the
geographic and geospatial domains are yet to be explored, ... | Computer Vision |
What field is the article from? | Title: Interpretable Neural PDE Solvers using Symbolic Frameworks
Abstract: Partial differential equations (PDEs) are ubiquitous in the world around us,
modelling phenomena from heat and sound to quantum systems. Recent advances in
deep learning have resulted in the development of powerful neural solvers;
however, whil... | Artificial Intelligence |
What field is the article from? | Title: Score Models for Offline Goal-Conditioned Reinforcement Learning
Abstract: Offline Goal-Conditioned Reinforcement Learning (GCRL) is tasked with
learning to achieve multiple goals in an environment purely from offline
datasets using sparse reward functions. Offline GCRL is pivotal for developing
generalist agent... | Machine Learning |
What field is the article from? | Title: Dynamics Generalisation in Reinforcement Learning via Adaptive Context-Aware Policies
Abstract: While reinforcement learning has achieved remarkable successes in several
domains, its real-world application is limited due to many methods failing to
generalise to unfamiliar conditions. In this work, we consider th... | Artificial Intelligence |
What field is the article from? | Title: An Intelligent Social Learning-based Optimization Strategy for Black-box Robotic Control with Reinforcement Learning
Abstract: Implementing intelligent control of robots is a difficult task, especially
when dealing with complex black-box systems, because of the lack of visibility
and understanding of how these r... | Artificial Intelligence |
What field is the article from? | Title: Legal-HNet: Mixing Legal Long-Context Tokens with Hartley Transform
Abstract: Since its introduction, the transformers architecture has seen great adoption
in NLP applications, but it also has limitations. Although the self-attention
mechanism allows for generating very rich representations of the input text,
it... | Computational Linguistics |
What field is the article from? | Title: Reconciling AI Performance and Data Reconstruction Resilience for Medical Imaging
Abstract: Artificial Intelligence (AI) models are vulnerable to information leakage of
their training data, which can be highly sensitive, for example in medical
imaging. Privacy Enhancing Technologies (PETs), such as Differential ... | Cryptography and Security |
What field is the article from? | Title: Controlling Large Language Model-based Agents for Large-Scale Decision-Making: An Actor-Critic Approach
Abstract: The significant advancements in large language models (LLMs) have presented
novel opportunities for tackling planning and decision-making within
multi-agent systems. However, as the number of agents ... | Artificial Intelligence |
What field is the article from? | Title: Adversarial Learning for Feature Shift Detection and Correction
Abstract: Data shift is a phenomenon present in many real-world applications, and while
there are multiple methods attempting to detect shifts, the task of localizing
and correcting the features originating such shifts has not been studied in
depth.... | Machine Learning |
What field is the article from? | Title: Redefining the Laparoscopic Spatial Sense: AI-based Intra- and Postoperative Measurement from Stereoimages
Abstract: A significant challenge in image-guided surgery is the accurate measurement
task of relevant structures such as vessel segments, resection margins, or
bowel lengths. While this task is an essentia... | Computer Vision |
What field is the article from? | Title: Calibrated Language Models Must Hallucinate
Abstract: Recent language models generate false but plausible-sounding text with
surprising frequency. Such "hallucinations" are an obstacle to the usability of
language-based AI systems and can harm people who rely upon their outputs. This
work shows shows that there ... | Computational Linguistics |
What field is the article from? | Title: HI-TOM: A Benchmark for Evaluating Higher-Order Theory of Mind Reasoning in Large Language Models
Abstract: Theory of Mind (ToM) is the ability to reason about one's own and others'
mental states. ToM plays a critical role in the development of intelligence,
language understanding, and cognitive processes. While... | Computational Linguistics |
What field is the article from? | Title: A Contrastive Compositional Benchmark for Text-to-Image Synthesis: A Study with Unified Text-to-Image Fidelity Metrics
Abstract: Text-to-image (T2I) synthesis has recently achieved significant advancements.
However, challenges remain in the model's compositionality, which is the
ability to create new combination... | Computer Vision |
What field is the article from? | Title: Geometric Data Augmentations to Mitigate Distribution Shifts in Pollen Classification from Microscopic Images
Abstract: Distribution shifts are characterized by differences between the training and
test data distributions. They can significantly reduce the accuracy of machine
learning models deployed in real-wor... | Computer Vision |
What field is the article from? | Title: An Efficient Self-Supervised Cross-View Training For Sentence Embedding
Abstract: Self-supervised sentence representation learning is the task of constructing
an embedding space for sentences without relying on human annotation efforts.
One straightforward approach is to finetune a pretrained language model (PLM... | Computational Linguistics |
What field is the article from? | Title: Will Code Remain a Relevant User Interface for End-User Programming with Generative AI Models?
Abstract: The research field of end-user programming has largely been concerned with
helping non-experts learn to code sufficiently well in order to achieve their
tasks. Generative AI stands to obviate this entirely by... | Human-Computer Interaction |
What field is the article from? | Title: ALYMPICS: Language Agents Meet Game Theory
Abstract: This paper introduces Alympics, a platform that leverages Large Language
Model (LLM) agents to facilitate investigations in game theory. By employing
LLMs and autonomous agents to simulate human behavior and enable multi-agent
collaborations, we can construct ... | Computational Linguistics |
What field is the article from? | Title: MUFFIN: Curating Multi-Faceted Instructions for Improving Instruction-Following
Abstract: In the realm of large language models (LLMs), enhancing instruction-following
capability often involves curating expansive training data. This is achieved
through two primary schemes: i) Scaling-Inputs: Amplifying (input, o... | Computational Linguistics |
What field is the article from? | Title: Retrieving Conditions from Reference Images for Diffusion Models
Abstract: Recent diffusion-based subject driven generative methods have enabled image
generations with good fidelity for specific objects or human portraits.
However, to achieve better versatility for applications, we argue that not only
improved d... | Computer Vision |
What field is the article from? | Title: SelfOcc: Self-Supervised Vision-Based 3D Occupancy Prediction
Abstract: 3D occupancy prediction is an important task for the robustness of
vision-centric autonomous driving, which aims to predict whether each point is
occupied in the surrounding 3D space. Existing methods usually require 3D
occupancy labels to p... | Computer Vision |
What field is the article from? | Title: A Local Appearance Model for Volumetric Capture of Diverse Hairstyle
Abstract: Hair plays a significant role in personal identity and appearance, making it
an essential component of high-quality, photorealistic avatars. Existing
approaches either focus on modeling the facial region only or rely on
personalized m... | Computer Vision |
What field is the article from? | Title: Grow Your Limits: Continuous Improvement with Real-World RL for Robotic Locomotion
Abstract: Deep reinforcement learning (RL) can enable robots to autonomously acquire
complex behaviors, such as legged locomotion. However, RL in the real world is
complicated by constraints on efficiency, safety, and overall trai... | Robotics |
What field is the article from? | Title: NeuroFlow: Development of lightweight and efficient model integration scheduling strategy for autonomous driving system
Abstract: This paper proposes a specialized autonomous driving system that takes into
account the unique constraints and characteristics of automotive systems,
aiming for innovative advancement... | Robotics |
What field is the article from? | Title: Modyn: A Platform for Model Training on Dynamic Datasets With Sample-Level Data Selection
Abstract: Machine learning training data is often dynamic in real-world use cases,
i.e., data is added or removed and may experience distribution shifts over
time. Models must incorporate this evolving training data to impr... | Machine Learning |
What field is the article from? | Title: Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents
Abstract: Text embedding models have emerged as powerful tools for transforming
sentences into fixed-sized feature vectors that encapsulate semantic
information. While these models are essential for tasks like information
retrieval,... | Computational Linguistics |
What field is the article from? | Title: Explained anomaly detection in text reviews: Can subjective scenarios be correctly evaluated?
Abstract: This paper presents a pipeline to detect and explain anomalous reviews in
online platforms. The pipeline is made up of three modules and allows the
detection of reviews that do not generate value for users due... | Computational Linguistics |
What field is the article from? | Title: InteRACT: Transformer Models for Human Intent Prediction Conditioned on Robot Actions
Abstract: In collaborative human-robot manipulation, a robot must predict human intents
and adapt its actions accordingly to smoothly execute tasks. However, the
human's intent in turn depends on actions the robot takes, creati... | Robotics |
What field is the article from? | Title: Class-Discriminative Attention Maps for Vision Transformers
Abstract: Interpretability methods are critical components for examining and exploring
deep neural networks (DNN), as well as increasing our understanding of and
trust in them. Vision transformers (ViT), which can be trained to
state-of-the-art performa... | Computer Vision |
What field is the article from? | Title: KnowGPT: Black-Box Knowledge Injection for Large Language Models
Abstract: Generative Large Language Models (LLMs), such as ChatGPT, offer interactive
APIs that can answer common questions at a human-expert level. However, these
models often give inaccurate or incorrect responses when faced with questions
requir... | Computational Linguistics |
What field is the article from? | Title: Using Large Language Models to Support Thematic Analysis in Empirical Legal Studies
Abstract: Thematic analysis and other variants of inductive coding are widely used
qualitative analytic methods within empirical legal studies (ELS). We propose a
novel framework facilitating effective collaboration of a legal ex... | Artificial Intelligence |
What field is the article from? | Title: Optimal Cost Constrained Adversarial Attacks For Multiple Agent Systems
Abstract: Finding optimal adversarial attack strategies is an important topic in
reinforcement learning and the Markov decision process. Previous studies
usually assume one all-knowing coordinator (attacker) for whom attacking
different reci... | Machine Learning |
What field is the article from? | Title: Function Space Bayesian Pseudocoreset for Bayesian Neural Networks
Abstract: A Bayesian pseudocoreset is a compact synthetic dataset summarizing essential
information of a large-scale dataset and thus can be used as a proxy dataset
for scalable Bayesian inference. Typically, a Bayesian pseudocoreset is
construct... | Machine Learning |
What field is the article from? | Title: AI for Open Science: A Multi-Agent Perspective for Ethically Translating Data to Knowledge
Abstract: AI for Science (AI4Science), particularly in the form of self-driving labs,
has the potential to sideline human involvement and hinder scientific discovery
within the broader community. While prior research has f... | Artificial Intelligence |
What field is the article from? | Title: Machine learning-based malware detection for IoT devices using control-flow data
Abstract: Embedded devices are specialised devices designed for one or only a few
purposes. They are often part of a larger system, through wired or wireless
connection. Those embedded devices that are connected to other computers o... | Artificial Intelligence |
What field is the article from? | Title: Simple Weak Coresets for Non-Decomposable Classification Measures
Abstract: While coresets have been growing in terms of their application, barring few
exceptions, they have mostly been limited to unsupervised settings. We consider
supervised classification problems, and non-decomposable evaluation measures in
s... | Machine Learning |
What field is the article from? | Title: Forecasting Lithium-Ion Battery Longevity with Limited Data Availability: Benchmarking Different Machine Learning Algorithms
Abstract: As the use of Lithium-ion batteries continues to grow, it becomes
increasingly important to be able to predict their remaining useful life. This
work aims to compare the relative... | Machine Learning |
What field is the article from? | Title: Contrastive Denoising Score for Text-guided Latent Diffusion Image Editing
Abstract: With the remarkable advent of text-to-image diffusion models, image editing
methods have become more diverse and continue to evolve. A promising recent
approach in this realm is Delta Denoising Score (DDS) - an image editing
tec... | Computer Vision |
What field is the article from? | Title: On Functional Activations in Deep Neural Networks
Abstract: Background: Deep neural networks have proven to be powerful computational
tools for modeling, prediction, and generation. However, the workings of these
models have generally been opaque. Recent work has shown that the performance
of some models are mod... | Artificial Intelligence |
What field is the article from? | Title: Localizing Lying in Llama: Understanding Instructed Dishonesty on True-False Questions Through Prompting, Probing, and Patching
Abstract: Large language models (LLMs) demonstrate significant knowledge through their
outputs, though it is often unclear whether false outputs are due to a lack of
knowledge or dishon... | Machine Learning |
What field is the article from? | Title: DIRECT: Deep Active Learning under Imbalance and Label Noise
Abstract: Class imbalance is a prevalent issue in real world machine learning
applications, often leading to poor performance in rare and minority classes.
With an abundance of wild unlabeled data, active learning is perhaps the most
effective techniqu... | Machine Learning |
What field is the article from? | Title: CustomNet: Zero-shot Object Customization with Variable-Viewpoints in Text-to-Image Diffusion Models
Abstract: Incorporating a customized object into image generation presents an
attractive feature in text-to-image generation. However, existing
optimization-based and encoder-based methods are hindered by drawbac... | Computer Vision |
What field is the article from? | Title: Energy-based Potential Games for Joint Motion Forecasting and Control
Abstract: This work uses game theory as a mathematical framework to address interaction
modeling in multi-agent motion forecasting and control. Despite its
interpretability, applying game theory to real-world robotics, like automated
driving, ... | Machine Learning |
What field is the article from? | Title: Two Complementary Perspectives to Continual Learning: Ask Not Only What to Optimize, But Also How
Abstract: Recent years have seen considerable progress in the continual training of
deep neural networks, predominantly thanks to approaches that add replay or
regularization terms to the loss function to approximat... | Machine Learning |
What field is the article from? | Title: Human-Guided Complexity-Controlled Abstractions
Abstract: Neural networks often learn task-specific latent representations that fail to
generalize to novel settings or tasks. Conversely, humans learn discrete
representations (i.e., concepts or words) at a variety of abstraction levels
(e.g., "bird" vs. "sparrow"... | Machine Learning |
What field is the article from? | Title: Object-Centric Learning with Slot Mixture Module
Abstract: Object-centric architectures usually apply a differentiable module to the
entire feature map to decompose it into sets of entity representations called
slots. Some of these methods structurally resemble clustering algorithms, where
the cluster's center i... | Machine Learning |
What field is the article from? | Title: INSPECT: A Multimodal Dataset for Pulmonary Embolism Diagnosis and Prognosis
Abstract: Synthesizing information from multiple data sources plays a crucial role in
the practice of modern medicine. Current applications of artificial
intelligence in medicine often focus on single-modality data due to a lack of
publ... | Machine Learning |
What field is the article from? | Title: Automated Camera Calibration via Homography Estimation with GNNs
Abstract: Over the past few decades, a significant rise of camera-based applications
for traffic monitoring has occurred. Governments and local administrations are
increasingly relying on the data collected from these cameras to enhance road
safety... | Computer Vision |
What field is the article from? | Title: MultiLoRA: Democratizing LoRA for Better Multi-Task Learning
Abstract: LoRA achieves remarkable resource efficiency and comparable performance when
adapting LLMs for specific tasks. Since ChatGPT demonstrated superior
performance on various tasks, there has been a growing desire to adapt one
model for all tasks.... | Machine Learning |
What field is the article from? | Title: Understanding Tool Discovery and Tool Innovation Using Active Inference
Abstract: The ability to invent new tools has been identified as an important facet of
our ability as a species to problem solve in dynamic and novel environments.
While the use of tools by artificial agents presents a challenging task and h... | Artificial Intelligence |
What field is the article from? | Title: Control Risk for Potential Misuse of Artificial Intelligence in Science
Abstract: The expanding application of Artificial Intelligence (AI) in scientific
fields presents unprecedented opportunities for discovery and innovation.
However, this growth is not without risks. AI models in science, if misused,
can ampl... | Artificial Intelligence |
What field is the article from? | Title: Symptom-based Machine Learning Models for the Early Detection of COVID-19: A Narrative Review
Abstract: Despite the widespread testing protocols for COVID-19, there are still
significant challenges in early detection of the disease, which is crucial for
preventing its spread and optimizing patient outcomes. Owin... | Machine Learning |
What field is the article from? | Title: Using a Large Language Model to generate a Design Structure Matrix
Abstract: The Design Structure Matrix (DSM) is an established method used in dependency
modelling, especially in the design of complex engineering systems. The
generation of DSM is traditionally carried out through manual means and can
involve in... | Artificial Intelligence |
What field is the article from? | Title: Revisiting Non-separable Binary Classification and its Applications in Anomaly Detection
Abstract: The inability to linearly classify XOR has motivated much of deep learning.
We revisit this age-old problem and show that linear classification of XOR is
indeed possible. Instead of separating data between halfspac... | Machine Learning |
What field is the article from? | Title: Can language agents be alternatives to PPO? A Preliminary Empirical Study On OpenAI Gym
Abstract: The formidable capacity for zero- or few-shot decision-making in language
agents encourages us to pose a compelling question: Can language agents be
alternatives to PPO agents in traditional sequential decision-maki... | Artificial Intelligence |
What field is the article from? | Title: DPR: An Algorithm Mitigate Bias Accumulation in Recommendation feedback loops
Abstract: Recommendation models trained on the user feedback collected from deployed
recommendation systems are commonly biased. User feedback is considerably
affected by the exposure mechanism, as users only provide feedback on the it... | Information Retrieval |
What field is the article from? | Title: Optimally Teaching a Linear Behavior Cloning Agent
Abstract: We study optimal teaching of Linear Behavior Cloning (LBC) learners. In this
setup, the teacher can select which states to demonstrate to an LBC learner.
The learner maintains a version space of infinite linear hypotheses consistent
with the demonstrat... | Machine Learning |
What field is the article from? | Title: Dual-Branch Reconstruction Network for Industrial Anomaly Detection with RGB-D Data
Abstract: Unsupervised anomaly detection methods are at the forefront of industrial
anomaly detection efforts and have made notable progress. Previous work
primarily used 2D information as input, but multi-modal industrial anomal... | Computer Vision |
What field is the article from? | Title: MCAD: Multi-teacher Cross-modal Alignment Distillation for efficient image-text retrieval
Abstract: With the success of large-scale visual-language pretraining models and the
wide application of image-text retrieval in industry areas, reducing the model
size and streamlining their terminal-device deployment have... | Computer Vision |
What field is the article from? | Title: ID-like Prompt Learning for Few-Shot Out-of-Distribution Detection
Abstract: Out-of-distribution (OOD) detection methods often exploit auxiliary outliers
to train model identifying OOD samples, especially discovering challenging
outliers from auxiliary outliers dataset to improve OOD detection. However,
they may... | Computer Vision |
What field is the article from? | Title: TOD-Flow: Modeling the Structure of Task-Oriented Dialogues
Abstract: Task-Oriented Dialogue (TOD) systems have become crucial components in
interactive artificial intelligence applications. While recent advances have
capitalized on pre-trained language models (PLMs), they exhibit limitations
regarding transpare... | Computational Linguistics |
What field is the article from? | Title: Goals are Enough: Inducing AdHoc cooperation among unseen Multi-Agent systems in IMFs
Abstract: Intent-based management will play a critical role in achieving customers'
expectations in the next-generation mobile networks. Traditional methods cannot
perform efficient resource management since they tend to handle... | Artificial Intelligence |
What field is the article from? | Title: Architecture of Smart Certificates for Web3 Applications Against Cyberthreats in Financial Industry
Abstract: This study addresses the security challenges associated with the current
internet transformations, specifically focusing on emerging technologies such
as blockchain and decentralized storage. It also inv... | Cryptography and Security |
What field is the article from? | Title: Recent Advances in Multi-modal 3D Scene Understanding: A Comprehensive Survey and Evaluation
Abstract: Multi-modal 3D scene understanding has gained considerable attention due to
its wide applications in many areas, such as autonomous driving and
human-computer interaction. Compared to conventional single-modal ... | Computer Vision |
What field is the article from? | Title: Towards Improving Robustness Against Common Corruptions using Mixture of Class Specific Experts
Abstract: Neural networks have demonstrated significant accuracy across various
domains, yet their vulnerability to subtle input alterations remains a
persistent challenge. Conventional methods like data augmentation,... | Machine Learning |
What field is the article from? | Title: FERGI: Automatic Annotation of User Preferences for Text-to-Image Generation from Spontaneous Facial Expression Reaction
Abstract: Researchers have proposed to use data of human preference feedback to
fine-tune text-to-image generative models. However, the scalability of human
feedback collection has been limite... | Computer Vision |
What field is the article from? | Title: Deep Reinforcement Learning for Weapons to Targets Assignment in a Hypersonic strike
Abstract: We use deep reinforcement learning (RL) to optimize a weapons to target
assignment (WTA) policy for multi-vehicle hypersonic strike against multiple
targets. The objective is to maximize the total value of destroyed ta... | Artificial Intelligence |
What field is the article from? | Title: Fusion of Deep and Shallow Features for Face Kinship Verification
Abstract: Kinship verification from face images is a novel and formidable challenge in
the realms of pattern recognition and computer vision. This work makes notable
contributions by incorporating a preprocessing technique known as Multiscale
Reti... | Computer Vision |
What field is the article from? | Title: AI Chatbot for Generating Episodic Future Thinking (EFT) Cue Texts for Health
Abstract: We describe an AI-powered chatbot to aid with health improvement by
generating Episodic Future Thinking (EFT) cue texts that should reduce delay
discounting. In prior studies, EFT has been shown to address maladaptive health
... | Human-Computer Interaction |
What field is the article from? | Title: AWEQ: Post-Training Quantization with Activation-Weight Equalization for Large Language Models
Abstract: Large language models(LLMs) exhibit excellent performance across a variety of
tasks, but they come with significant computational and storage costs.
Quantizing these models is an effective way to alleviate th... | Machine Learning |
What field is the article from? | Title: ChatGPT Application In Summarizing An Evolution Of Deep Learning Techniques In Imaging: A Qualitative Study
Abstract: The pursuit of article or text summarization has captured the attention of
natural language processing (NLP) practitioners, presenting itself as a
formidable challenge. ChatGPT 3.5 exhibits the c... | Computational Linguistics |
What field is the article from? | Title: Advances in 3D Neural Stylization: A Survey
Abstract: Modern artificial intelligence provides a novel way of producing digital art
in styles. The expressive power of neural networks enables the realm of visual
style transfer methods, which can be used to edit images, videos, and 3D data
to make them more artisti... | Computer Vision |
What field is the article from? | Title: Transformers as Graph-to-Graph Models
Abstract: We argue that Transformers are essentially graph-to-graph models, with
sequences just being a special case. Attention weights are functionally
equivalent to graph edges. Our Graph-to-Graph Transformer architecture makes
this ability explicit, by inputting graph edg... | Computational Linguistics |
What field is the article from? | Title: Explainable Fraud Detection with Deep Symbolic Classification
Abstract: There is a growing demand for explainable, transparent, and data-driven
models within the domain of fraud detection. Decisions made by fraud detection
models need to be explainable in the event of a customer dispute. Additionally,
the decisi... | Machine Learning |
What field is the article from? | Title: Evaluating the Effectiveness of Retrieval-Augmented Large Language Models in Scientific Document Reasoning
Abstract: Despite the dramatic progress in Large Language Model (LLM) development, LLMs
often provide seemingly plausible but not factual information, often referred
to as hallucinations. Retrieval-augmente... | Computational Linguistics |
What field is the article from? | Title: Frequency-domain MLPs are More Effective Learners in Time Series Forecasting
Abstract: Time series forecasting has played the key role in different industrial,
including finance, traffic, energy, and healthcare domains. While existing
literatures have designed many sophisticated architectures based on RNNs, GNNs... | Machine Learning |
What field is the article from? | Title: SynthEnsemble: A Fusion of CNN, Vision Transformer, and Hybrid Models for Multi-Label Chest X-Ray Classification
Abstract: Chest X-rays are widely used to diagnose thoracic diseases, but the lack of
detailed information about these abnormalities makes it challenging to develop
accurate automated diagnosis system... | Computer Vision |
What field is the article from? | Title: From External to Swap Regret 2.0: An Efficient Reduction and Oblivious Adversary for Large Action Spaces
Abstract: We provide a novel reduction from swap-regret minimization to external-regret
minimization, which improves upon the classical reductions of Blum-Mansour
[BM07] and Stolz-Lugosi [SL05] in that it doe... | Machine Learning |
What field is the article from? | Title: Improving Biomedical Entity Linking with Retrieval-enhanced Learning
Abstract: Biomedical entity linking (BioEL) has achieved remarkable progress with the
help of pre-trained language models. However, existing BioEL methods usually
struggle to handle rare and difficult entities due to long-tailed distribution.
T... | Computational Linguistics |
What field is the article from? | Title: On Mask-based Image Set Desensitization with Recognition Support
Abstract: In recent years, Deep Neural Networks (DNN) have emerged as a practical
method for image recognition. The raw data, which contain sensitive
information, are generally exploited within the training process. However, when
the training proce... | Computer Vision |
What field is the article from? | Title: Loss Balancing for Fair Supervised Learning
Abstract: Supervised learning models have been used in various domains such as lending,
college admission, face recognition, natural language processing, etc. However,
they may inherit pre-existing biases from training data and exhibit
discrimination against protected ... | Machine Learning |
What field is the article from? | Title: Radar Perception in Autonomous Driving: Exploring Different Data Representations
Abstract: With the rapid advancements of sensor technology and deep learning,
autonomous driving systems are providing safe and efficient access to
intelligent vehicles as well as intelligent transportation. Among these
equipped sen... | Computer Vision |
What field is the article from? | Title: Non-autoregressive Streaming Transformer for Simultaneous Translation
Abstract: Simultaneous machine translation (SiMT) models are trained to strike a
balance between latency and translation quality. However, training these models
to achieve high quality while maintaining low latency often leads to a tendency
fo... | Computational Linguistics |
What field is the article from? | Title: Recognize Any Regions
Abstract: Understanding the semantics of individual regions or patches within
unconstrained images, such as in open-world object detection, represents a
critical yet challenging task in computer vision. Building on the success of
powerful image-level vision-language (ViL) foundation models ... | Computer Vision |
What field is the article from? | Title: Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems
Abstract: Artificial Intelligence (AI) systems such as autonomous vehicles, facial
recognition, and speech recognition systems are increasingly integrated into
our daily lives. However, despite their utility, these AI systems are
vul... | Cryptography and Security |
What field is the article from? | Title: Large Language Model is a Good Policy Teacher for Training Reinforcement Learning Agents
Abstract: Recent studies have shown that Large Language Models (LLMs) can be utilized
for solving complex sequential decision-making tasks by providing high-level
instructions. However, LLM-based agents face limitations in r... | Artificial Intelligence |
What field is the article from? | Title: Ignore This Title and HackAPrompt: Exposing Systemic Vulnerabilities of LLMs through a Global Scale Prompt Hacking Competition
Abstract: Large Language Models (LLMs) are deployed in interactive contexts with direct
user engagement, such as chatbots and writing assistants. These deployments are
vulnerable to prom... | Cryptography and Security |
What field is the article from? | Title: LSTM-CNN: An efficient diagnostic network for Parkinson's disease utilizing dynamic handwriting analysis
Abstract: Background and objectives: Dynamic handwriting analysis, due to its
non-invasive and readily accessible nature, has recently emerged as a vital
adjunctive method for the early diagnosis of Parkinson... | Artificial Intelligence |
What field is the article from? | Title: CommunityAI: Towards Community-based Federated Learning
Abstract: Federated Learning (FL) has emerged as a promising paradigm to train machine
learning models collaboratively while preserving data privacy. However, its
widespread adoption faces several challenges, including scalability,
heterogeneous data and de... | Machine Learning |
What field is the article from? | Title: Toxicity Detection is NOT all you Need: Measuring the Gaps to Supporting Volunteer Content Moderators
Abstract: Extensive efforts in automated approaches for content moderation have been
focused on developing models to identify toxic, offensive, and hateful content
-- with the aim of lightening the load for mode... | Computational Linguistics |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.