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What field is the article from? | Title: Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework
Abstract: Fairness for machine learning predictions is widely required in practice for
legal, ethical, and societal reasons. Existing work typically focuses on
settings without unobserved confounding, even though unobserved confounding ... | Machine Learning |
What field is the article from? | Title: A Pseudo-Semantic Loss for Autoregressive Models with Logical Constraints
Abstract: Neuro-symbolic AI bridges the gap between purely symbolic and neural
approaches to learning. This often requires maximizing the likelihood of a
symbolic constraint w.r.t the neural network's output distribution. Such output
distr... | Machine Learning |
What field is the article from? | Title: ASI: Accuracy-Stability Index for Evaluating Deep Learning Models
Abstract: In the context of deep learning research, where model introductions
continually occur, the need for effective and efficient evaluation remains
paramount. Existing methods often emphasize accuracy metrics, overlooking
stability. To addres... | Machine Learning |
What field is the article from? | Title: Dense Visual Odometry Using Genetic Algorithm
Abstract: Our work aims to estimate the camera motion mounted on the head of a mobile
robot or a moving object from RGB-D images in a static scene. The problem of
motion estimation is transformed into a nonlinear least squares function.
Methods for solving such probl... | Robotics |
What field is the article from? | Title: TESTA: Temporal-Spatial Token Aggregation for Long-form Video-Language Understanding
Abstract: Large-scale video-language pre-training has made remarkable strides in
advancing video-language understanding tasks. However, the heavy computational
burden of video encoding remains a formidable efficiency bottleneck,... | Computer Vision |
What field is the article from? | Title: Revealing Networks: Understanding Effective Teacher Practices in AI-Supported Classrooms using Transmodal Ordered Network Analysis
Abstract: Learning analytics research increasingly studies classroom learning with
AI-based systems through rich contextual data from outside these systems,
especially student-teache... | Computers and Society |
What field is the article from? | Title: DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer
Abstract: Large Language Models (LLMs) have emerged as dominant tools for various
tasks, particularly when tailored for a specific target by prompt tuning.
Nevertheless, concerns surrounding data privacy present obstacles due to the
tuned ... | Computational Linguistics |
What field is the article from? | Title: InstructPipe: Building Visual Programming Pipelines with Human Instructions
Abstract: Visual programming provides beginner-level programmers with a coding-free
experience to build their customized pipelines. Existing systems require users
to build a pipeline entirely from scratch, implying that novice users need... | Human-Computer Interaction |
What field is the article from? | Title: TD-MPC2: Scalable, Robust World Models for Continuous Control
Abstract: TD-MPC is a model-based reinforcement learning (RL) algorithm that performs
local trajectory optimization in the latent space of a learned implicit
(decoder-free) world model. In this work, we present TD-MPC2: a series of
improvements upon t... | Machine Learning |
What field is the article from? | Title: A Study on the Calibration of In-context Learning
Abstract: Modern auto-regressive language models are trained to minimize log loss on
broad data by predicting the next token so they are expected to get calibrated
answers in next-token prediction tasks. We study this for in-context learning
(ICL), a widely used ... | Computational Linguistics |
What field is the article from? | Title: Real-Time Neural Rasterization for Large Scenes
Abstract: We propose a new method for realistic real-time novel-view synthesis (NVS) of
large scenes. Existing neural rendering methods generate realistic results, but
primarily work for small scale scenes (<50 square meters) and have difficulty
at large scale (>10... | Computer Vision |
What field is the article from? | Title: Efficient Classification of Student Help Requests in Programming Courses Using Large Language Models
Abstract: The accurate classification of student help requests with respect to the type
of help being sought can enable the tailoring of effective responses.
Automatically classifying such requests is non-trivial... | Computers and Society |
What field is the article from? | Title: Gaze Detection and Analysis for Initiating Joint Activity in Industrial Human-Robot Collaboration
Abstract: Collaborative robots (cobots) are widely used in industrial applications, yet
extensive research is still needed to enhance human-robot collaborations and
operator experience. A potential approach to impro... | Robotics |
What field is the article from? | Title: Reviewing Developments of Graph Convolutional Network Techniques for Recommendation Systems
Abstract: The Recommender system is a vital information service on today's Internet.
Recently, graph neural networks have emerged as the leading approach for
recommender systems. We try to review recent literature on grap... | Information Retrieval |
What field is the article from? | Title: ChatSOS: LLM-based knowledge Q&A system for safety engineering
Abstract: Recent advancements in large language models (LLMs) have notably propelled
natural language processing (NLP) capabilities, demonstrating significant
potential in safety engineering applications. Despite these advancements, LLMs
face constra... | Artificial Intelligence |
What field is the article from? | Title: Towards A Unified View of Answer Calibration for Multi-Step Reasoning
Abstract: Large Language Models (LLMs) employing Chain-of-Thought (CoT) prompting have
broadened the scope for improving multi-step reasoning capabilities. Usually,
answer calibration strategies such as step-level or path-level calibration pla... | Computational Linguistics |
What field is the article from? | Title: State-of-the-Art Review and Synthesis: A Requirement-based Roadmap for Standardized Predictive Maintenance Automation Using Digital Twin Technologies
Abstract: Recent digital advances have popularized predictive maintenance (PMx),
offering enhanced efficiency, automation, accuracy, cost savings, and
independence... | Artificial Intelligence |
What field is the article from? | Title: Two-step dynamic obstacle avoidance
Abstract: Dynamic obstacle avoidance (DOA) is a fundamental challenge for any
autonomous vehicle, independent of whether it operates in sea, air, or land.
This paper proposes a two-step architecture for handling DOA tasks by combining
supervised and reinforcement learning (RL)... | Robotics |
What field is the article from? | Title: Generative artificial intelligence enhances individual creativity but reduces the collective diversity of novel content
Abstract: Creativity is core to being human. Generative artificial intelligence (GenAI)
holds promise for humans to be more creative by offering new ideas, or less
creative by anchoring on GenA... | Human-Computer Interaction |
What field is the article from? | Title: Towards Reliable Participation in UAV-Enabled Federated Edge Learning on Non-IID Data
Abstract: Federated Learning (FL) is a decentralized machine learning (ML) technique
that allows a number of participants to train an ML model collaboratively
without having to share their private local datasets with others. Wh... | Machine Learning |
What field is the article from? | Title: Stochastic Directly-Follows Process Discovery Using Grammatical Inference
Abstract: Starting with a collection of traces generated by process executions, process
discovery is the task of constructing a simple model that describes the
process, where simplicity is often measured in terms of model size. The
challen... | Artificial Intelligence |
What field is the article from? | Title: H-GAP: Humanoid Control with a Generalist Planner
Abstract: Humanoid control is an important research challenge offering avenues for
integration into human-centric infrastructures and enabling physics-driven
humanoid animations. The daunting challenges in this field stem from the
difficulty of optimizing in high... | Machine Learning |
What field is the article from? | Title: Tuning-less Object Naming with a Foundation Model
Abstract: We implement a real-time object naming system that enables learning a set of
named entities never seen. Our approach employs an existing foundation model
that we consider ready to see anything before starting. It turns seen images
into relatively small ... | Computational Linguistics |
What field is the article from? | Title: Doodle Your 3D: From Abstract Freehand Sketches to Precise 3D Shapes
Abstract: In this paper, we democratise 3D content creation, enabling precise
generation of 3D shapes from abstract sketches while overcoming limitations
tied to drawing skills. We introduce a novel part-level modelling and alignment
framework ... | Computer Vision |
What field is the article from? | Title: Exploring Geometry of Blind Spots in Vision Models
Abstract: Despite the remarkable success of deep neural networks in a myriad of
settings, several works have demonstrated their overwhelming sensitivity to
near-imperceptible perturbations, known as adversarial attacks. On the other
hand, prior works have also o... | Computer Vision |
What field is the article from? | Title: Helping Language Models Learn More: Multi-dimensional Task Prompt for Few-shot Tuning
Abstract: Large language models (LLMs) can be used as accessible and intelligent
chatbots by constructing natural language queries and directly inputting the
prompt into the large language model. However, different prompt' cons... | Computational Linguistics |
What field is the article from? | Title: DAMEX: Dataset-aware Mixture-of-Experts for visual understanding of mixture-of-datasets
Abstract: Construction of a universal detector poses a crucial question: How can we
most effectively train a model on a large mixture of datasets? The answer lies
in learning dataset-specific features and ensembling their kno... | Computer Vision |
What field is the article from? | Title: Generalization of Fitness Exercise Recognition from Doppler Measurements by Domain-adaption and Few-Shot Learning
Abstract: In previous works, a mobile application was developed using an unmodified
commercial off-the-shelf smartphone to recognize whole-body exercises. The
working principle was based on the ultra... | Artificial Intelligence |
What field is the article from? | Title: STEER: Semantic Turn Extension-Expansion Recognition for Voice Assistants
Abstract: In the context of a voice assistant system, steering refers to the phenomenon
in which a user issues a follow-up command attempting to direct or clarify a
previous turn. We propose STEER, a steering detection model that predicts
... | Computational Linguistics |
What field is the article from? | Title: Task Tree Retrieval For Robotic Cooking
Abstract: This paper is based on developing different algorithms, which generate the
task tree planning for the given goal node(recipe). The knowledge
representation of the dishes is called FOON. It contains the different objects
and their between them with respective to t... | Robotics |
What field is the article from? | Title: TaskWeaver: A Code-First Agent Framework
Abstract: Large Language Models (LLMs) have shown impressive abilities in natural
language understanding and generation, leading to their use in applications
such as chatbots and virtual assistants. However, existing LLM frameworks face
limitations in handling domain-spec... | Artificial Intelligence |
What field is the article from? | Title: Concept Alignment as a Prerequisite for Value Alignment
Abstract: Value alignment is essential for building AI systems that can safely and
reliably interact with people. However, what a person values -- and is even
capable of valuing -- depends on the concepts that they are currently using to
understand and eval... | Artificial Intelligence |
What field is the article from? | Title: Toward the Tradeoffs between Privacy, Fairness and Utility in Federated Learning
Abstract: Federated Learning (FL) is a novel privacy-protection distributed machine
learning paradigm that guarantees user privacy and prevents the risk of data
leakage due to the advantage of the client's local training. Researcher... | Machine Learning |
What field is the article from? | Title: On The Fairness Impacts of Hardware Selection in Machine Learning
Abstract: In the machine learning ecosystem, hardware selection is often regarded as a
mere utility, overshadowed by the spotlight on algorithms and data. This
oversight is particularly problematic in contexts like ML-as-a-service
platforms, where... | Machine Learning |
What field is the article from? | Title: Resource-constrained knowledge diffusion processes inspired by human peer learning
Abstract: We consider a setting where a population of artificial learners is given, and
the objective is to optimize aggregate measures of performance, under
constraints on training resources. The problem is motivated by the study... | Machine Learning |
What field is the article from? | Title: The Limits of Fair Medical Imaging AI In The Wild
Abstract: As artificial intelligence (AI) rapidly approaches human-level performance in
medical imaging, it is crucial that it does not exacerbate or propagate
healthcare disparities. Prior research has established AI's capacity to infer
demographic data from che... | Computers and Society |
What field is the article from? | Title: DARLEI: Deep Accelerated Reinforcement Learning with Evolutionary Intelligence
Abstract: We present DARLEI, a framework that combines evolutionary algorithms with
parallelized reinforcement learning for efficiently training and evolving
populations of UNIMAL agents. Our approach utilizes Proximal Policy
Optimiza... | Artificial Intelligence |
What field is the article from? | Title: Using Artificial French Data to Understand the Emergence of Gender Bias in Transformer Language Models
Abstract: Numerous studies have demonstrated the ability of neural language models to
learn various linguistic properties without direct supervision. This work takes
an initial step towards exploring the less r... | Computational Linguistics |
What field is the article from? | Title: Exploring Values in Museum Artifacts in the SPICE project: a Preliminary Study
Abstract: This document describes the rationale, the implementation and a preliminary
evaluation of a semantic reasoning tool developed in the EU H2020 SPICE project
to enhance the diversity of perspectives experienced by museum visit... | Artificial Intelligence |
What field is the article from? | Title: A Causal Disentangled Multi-Granularity Graph Classification Method
Abstract: Graph data widely exists in real life, with large amounts of data and complex
structures. It is necessary to map graph data to low-dimensional embedding.
Graph classification, a critical graph task, mainly relies on identifying the
imp... | Machine Learning |
What field is the article from? | Title: OpinSummEval: Revisiting Automated Evaluation for Opinion Summarization
Abstract: Opinion summarization sets itself apart from other types of summarization
tasks due to its distinctive focus on aspects and sentiments. Although certain
automated evaluation methods like ROUGE have gained popularity, we have found
... | Computational Linguistics |
What field is the article from? | Title: Generating Valid and Natural Adversarial Examples with Large Language Models
Abstract: Deep learning-based natural language processing (NLP) models, particularly
pre-trained language models (PLMs), have been revealed to be vulnerable to
adversarial attacks. However, the adversarial examples generated by many
mai... | Computational Linguistics |
What field is the article from? | Title: CoheSentia: A Novel Benchmark of Incremental versus Holistic Assessment of Coherence in Generated Texts
Abstract: Coherence is a linguistic term that refers to the relations between small
textual units (sentences, propositions), which make the text logically
consistent and meaningful to the reader. With the adva... | Computational Linguistics |
What field is the article from? | Title: Generative AI for Software Metadata: Overview of the Information Retrieval in Software Engineering Track at FIRE 2023
Abstract: The Information Retrieval in Software Engineering (IRSE) track aims to
develop solutions for automated evaluation of code comments in a machine
learning framework based on human and lar... | Software Engineering |
What field is the article from? | Title: When is Offline Policy Selection Sample Efficient for Reinforcement Learning?
Abstract: Offline reinforcement learning algorithms often require careful
hyperparameter tuning. Consequently, before deployment, we need to select
amongst a set of candidate policies. As yet, however, there is little
understanding abo... | Machine Learning |
What field is the article from? | Title: Data-Driven Risk Modeling for Infrastructure Projects Using Artificial Intelligence Techniques
Abstract: Managing project risk is a key part of the successful implementation of any
large project and is widely recognized as a best practice for public agencies
to deliver infrastructures. The conventional method of... | Software Engineering |
What field is the article from? | Title: Rethinking Samples Selection for Contrastive Learning: Mining of Potential Samples
Abstract: Contrastive learning predicts whether two images belong to the same category
by training a model to make their feature representations as close or as far
away as possible. In this paper, we rethink how to mine samples in... | Computer Vision |
What field is the article from? | Title: Diverse Conventions for Human-AI Collaboration
Abstract: Conventions are crucial for strong performance in cooperative multi-agent
games, because they allow players to coordinate on a shared strategy without
explicit communication. Unfortunately, standard multi-agent reinforcement
learning techniques, such as se... | Artificial Intelligence |
What field is the article from? | Title: SequenceMatch: Revisiting the design of weak-strong augmentations for Semi-supervised learning
Abstract: Semi-supervised learning (SSL) has become popular in recent years because it
allows the training of a model using a large amount of unlabeled data. However,
one issue that many SSL methods face is the confirm... | Computer Vision |
What field is the article from? | Title: Using Early Readouts to Mediate Featural Bias in Distillation
Abstract: Deep networks tend to learn spurious feature-label correlations in real-world
supervised learning tasks. This vulnerability is aggravated in distillation,
where a student model may have lesser representational capacity than the
corresponding... | Machine Learning |
What field is the article from? | Title: Trust, Accountability, and Autonomy in Knowledge Graph-based AI for Self-determination
Abstract: Knowledge Graphs (KGs) have emerged as fundamental platforms for powering
intelligent decision-making and a wide range of Artificial Intelligence (AI)
services across major corporations such as Google, Walmart, and A... | Artificial Intelligence |
What field is the article from? | Title: Exploring the Robustness of Decentralized Training for Large Language Models
Abstract: Decentralized training of large language models has emerged as an effective
way to democratize this technology. However, the potential threats associated
with this approach have not been carefully discussed, which would hinder... | Machine Learning |
What field is the article from? | Title: SAMSGL: Series-Aligned Multi-Scale Graph Learning for Spatio-Temporal Forecasting
Abstract: Spatio-temporal forecasting in various domains, like traffic prediction and
weather forecasting, is a challenging endeavor, primarily due to the
difficulties in modeling propagation dynamics and capturing high-dimensional... | Machine Learning |
What field is the article from? | Title: SemanticBoost: Elevating Motion Generation with Augmented Textual Cues
Abstract: Current techniques face difficulties in generating motions from intricate
semantic descriptions, primarily due to insufficient semantic annotations in
datasets and weak contextual understanding. To address these issues, we present
S... | Computer Vision |
What field is the article from? | Title: GPT4All: An Ecosystem of Open Source Compressed Language Models
Abstract: Large language models (LLMs) have recently achieved human-level performance
on a range of professional and academic benchmarks. The accessibility of these
models has lagged behind their performance. State-of-the-art LLMs require
costly inf... | Computational Linguistics |
What field is the article from? | Title: Enabling High-Level Machine Reasoning with Cognitive Neuro-Symbolic Systems
Abstract: High-level reasoning can be defined as the capability to generalize over
knowledge acquired via experience, and to exhibit robust behavior in novel
situations. Such form of reasoning is a basic skill in humans, who seamlessly
u... | Artificial Intelligence |
What field is the article from? | Title: Survey on Memory-Augmented Neural Networks: Cognitive Insights to AI Applications
Abstract: This paper explores Memory-Augmented Neural Networks (MANNs), delving into
how they blend human-like memory processes into AI. It covers different memory
types, like sensory, short-term, and long-term memory, linking psyc... | Artificial Intelligence |
What field is the article from? | Title: Resolving Crash Bugs via Large Language Models: An Empirical Study
Abstract: Crash bugs cause unexpected program behaviors or even termination, requiring
high-priority resolution. However, manually resolving crash bugs is challenging
and labor-intensive, and researchers have proposed various techniques for their... | Software Engineering |
What field is the article from? | Title: Alleviating Behavior Data Imbalance for Multi-Behavior Graph Collaborative Filtering
Abstract: Graph collaborative filtering, which learns user and item representations
through message propagation over the user-item interaction graph, has been
shown to effectively enhance recommendation performance. However, mos... | Information Retrieval |
What field is the article from? | Title: Benchmarks for Physical Reasoning AI
Abstract: Physical reasoning is a crucial aspect in the development of general AI
systems, given that human learning starts with interacting with the physical
world before progressing to more complex concepts. Although researchers have
studied and assessed the physical reason... | Artificial Intelligence |
What field is the article from? | Title: Leveraging Diffusion Perturbations for Measuring Fairness in Computer Vision
Abstract: Computer vision models have been known to encode harmful biases, leading to
the potentially unfair treatment of historically marginalized groups, such as
people of color. However, there remains a lack of datasets balanced alon... | Computer Vision |
What field is the article from? | Title: Distance-Based Propagation for Efficient Knowledge Graph Reasoning
Abstract: Knowledge graph completion (KGC) aims to predict unseen edges in knowledge
graphs (KGs), resulting in the discovery of new facts. A new class of methods
have been proposed to tackle this problem by aggregating path information.
These me... | Machine Learning |
What field is the article from? | Title: Style-Aware Radiology Report Generation with RadGraph and Few-Shot Prompting
Abstract: Automatically generated reports from medical images promise to improve the
workflow of radiologists. Existing methods consider an image-to-report modeling
task by directly generating a fully-fledged report from an image. Howev... | Artificial Intelligence |
What field is the article from? | Title: Learning Safety Constraints From Demonstration Using One-Class Decision Trees
Abstract: The alignment of autonomous agents with human values is a pivotal challenge
when deploying these agents within physical environments, where safety is an
important concern. However, defining the agent's objective as a reward a... | Machine Learning |
What field is the article from? | Title: SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery
Abstract: Geographic location is essential for modeling tasks in fields ranging from
ecology to epidemiology to the Earth system sciences. However, extracting
relevant and meaningful characteristics of a location can be challenging, ofte... | Computer Vision |
What field is the article from? | Title: FedSN: A General Federated Learning Framework over LEO Satellite Networks
Abstract: Recently, a large number of Low Earth Orbit (LEO) satellites have been
launched and deployed successfully in space by commercial companies, such as
SpaceX. Due to multimodal sensors equipped by the LEO satellites, they serve
not ... | Machine Learning |
What field is the article from? | Title: Continual Diffusion with STAMINA: STack-And-Mask INcremental Adapters
Abstract: Recent work has demonstrated a remarkable ability to customize text-to-image
diffusion models to multiple, fine-grained concepts in a sequential (i.e.,
continual) manner while only providing a few example images for each concept.
Thi... | Computer Vision |
What field is the article from? | Title: Personas as a Way to Model Truthfulness in Language Models
Abstract: Large Language Models (LLMs) are trained on vast amounts of text from the
internet, which contains both factual and misleading information about the
world. Can language models discern truth from falsehood in this contradicting
data? Expanding o... | Computational Linguistics |
What field is the article from? | Title: Panoptic Video Scene Graph Generation
Abstract: Towards building comprehensive real-world visual perception systems, we
propose and study a new problem called panoptic scene graph generation (PVSG).
PVSG relates to the existing video scene graph generation (VidSGG) problem,
which focuses on temporal interactions... | Computer Vision |
What field is the article from? | Title: A Unified View on Forgetting and Strong Equivalence Notions in Answer Set Programming
Abstract: Answer Set Programming (ASP) is a prominent rule-based language for knowledge
representation and reasoning with roots in logic programming and non-monotonic
reasoning. The aim to capture the essence of removing (ir)re... | Artificial Intelligence |
What field is the article from? | Title: Probable Object Location (POLo) Score Estimation for Efficient Object Goal Navigation
Abstract: To advance the field of autonomous robotics, particularly in object search
tasks within unexplored environments, we introduce a novel framework centered
around the Probable Object Location (POLo) score. Utilizing a 3D... | Robotics |
What field is the article from? | Title: Efficiently Adapting Pretrained Language Models To New Languages
Abstract: Recent large language models (LLM) exhibit sub-optimal performance on
low-resource languages, as the training data of these models is usually
dominated by English and other high-resource languages. Furthermore, it is
challenging to train ... | Computational Linguistics |
What field is the article from? | Title: Exploring the Privacy-Energy Consumption Tradeoff for Split Federated Learning
Abstract: Split Federated Learning (SFL) has recently emerged as a promising
distributed learning technology, leveraging the strengths of both federated
learning and split learning. It emphasizes the advantages of rapid convergence
wh... | Machine Learning |
What field is the article from? | Title: Causal Models Applied to the Patterns of Human Migration due to Climate Change
Abstract: The impacts of mass migration, such as crisis induced by climate change,
extend beyond environmental concerns and can greatly affect social
infrastructure and public services, such as education, healthcare, and
security. The... | Computers and Society |
What field is the article from? | Title: Greedy PIG: Adaptive Integrated Gradients
Abstract: Deep learning has become the standard approach for most machine learning
tasks. While its impact is undeniable, interpreting the predictions of deep
learning models from a human perspective remains a challenge. In contrast to
model training, model interpretabil... | Machine Learning |
What field is the article from? | Title: Cooperative Network Learning for Large-Scale and Decentralized Graphs
Abstract: Graph research, the systematic study of interconnected data points
represented as graphs, plays a vital role in capturing intricate relationships
within networked systems. However, in the real world, as graphs scale up,
concerns abou... | Machine Learning |
What field is the article from? | Title: Large Language Models are Clinical Reasoners: Reasoning-Aware Diagnosis Framework with Prompt-Generated Rationales
Abstract: Machine reasoning has made great progress in recent years owing to large
language models (LLMs). In the clinical domain, however, most NLP-driven
projects mainly focus on clinical classifi... | Computational Linguistics |
What field is the article from? | Title: Bad Students Make Great Teachers: Active Learning Accelerates Large-Scale Visual Understanding
Abstract: We propose a method for accelerating large-scale pre-training with online
data selection policies. For the first time, we demonstrate that model-based
data selection can reduce the total computation needed to... | Artificial Intelligence |
What field is the article from? | Title: Apollo: Zero-shot MultiModal Reasoning with Multiple Experts
Abstract: We propose a modular framework that leverages the expertise of different
foundation models over different modalities and domains in order to perform a
single, complex, multi-modal task, without relying on prompt engineering or
otherwise tailo... | Computational Linguistics |
What field is the article from? | Title: A multi-modal table tennis robot system
Abstract: In recent years, robotic table tennis has become a popular research challenge
for perception and robot control. Here, we present an improved table tennis
robot system with high accuracy vision detection and fast robot reaction. Based
on previous work, our system ... | Robotics |
What field is the article from? | Title: Sample Dominance Aware Framework via Non-Parametric Estimation for Spontaneous Brain-Computer Interface
Abstract: Deep learning has shown promise in decoding brain signals, such as
electroencephalogram (EEG), in the field of brain-computer interfaces (BCIs).
However, the non-stationary characteristics of EEG sig... | Machine Learning |
What field is the article from? | Title: Enhancing Person Re-Identification through Tensor Feature Fusion
Abstract: In this paper, we present a novel person reidentification (PRe-ID) system
that based on tensor feature representation and multilinear subspace learning.
Our approach utilizes pretrained CNNs for high-level feature extraction, along
with L... | Computer Vision |
What field is the article from? | Title: Improved DDIM Sampling with Moment Matching Gaussian Mixtures
Abstract: We propose using a Gaussian Mixture Model (GMM) as reverse transition
operator (kernel) within the Denoising Diffusion Implicit Models (DDIM)
framework, which is one of the most widely used approaches for accelerated
sampling from pre-traine... | Computer Vision |
What field is the article from? | Title: BIVDiff: A Training-Free Framework for General-Purpose Video Synthesis via Bridging Image and Video Diffusion Models
Abstract: Diffusion models have made tremendous progress in text-driven image and video
generation. Now text-to-image foundation models are widely applied to various
downstream image synthesis tas... | Computer Vision |
What field is the article from? | Title: Proceedings Fifth International Workshop on Formal Methods for Autonomous Systems
Abstract: This EPTCS volume contains the proceedings for the Fifth International
Workshop on Formal Methods for Autonomous Systems (FMAS 2023), which was held
on the 15th and 16th of November 2023. FMAS 2023 was co-located with 18t... | Artificial Intelligence |
What field is the article from? | Title: Learning adaptive planning representations with natural language guidance
Abstract: Effective planning in the real world requires not only world knowledge, but
the ability to leverage that knowledge to build the right representation of the
task at hand. Decades of hierarchical planning techniques have used
domai... | Artificial Intelligence |
What field is the article from? | Title: HALO: An Ontology for Representing Hallucinations in Generative Models
Abstract: Recent progress in generative AI, including large language models (LLMs) like
ChatGPT, has opened up significant opportunities in fields ranging from natural
language processing to knowledge discovery and data mining. However, there... | Artificial Intelligence |
What field is the article from? | Title: Revolutionizing Healthcare Image Analysis in Pandemic-Based Fog-Cloud Computing Architectures
Abstract: The emergence of pandemics has significantly emphasized the need for
effective solutions in healthcare data analysis. One particular challenge in
this domain is the manual examination of medical images, such a... | Computer Vision |
What field is the article from? | Title: Three Conjectures on Unexpectedeness
Abstract: Unexpectedness is a central concept in Simplicity Theory, a theory of
cognition relating various inferential processes to the computation of
Kolmogorov complexities, rather than probabilities. Its predictive power has
been confirmed by several experiments with human... | Artificial Intelligence |
What field is the article from? | Title: RichDreamer: A Generalizable Normal-Depth Diffusion Model for Detail Richness in Text-to-3D
Abstract: Lifting 2D diffusion for 3D generation is a challenging problem due to the
lack of geometric prior and the complex entanglement of materials and lighting
in natural images. Existing methods have shown promise by... | Computer Vision |
What field is the article from? | Title: Transformation vs Tradition: Artificial General Intelligence (AGI) for Arts and Humanities
Abstract: Recent advances in artificial general intelligence (AGI), particularly large
language models and creative image generation systems have demonstrated
impressive capabilities on diverse tasks spanning the arts and ... | Artificial Intelligence |
What field is the article from? | Title: PolyFit: A Peg-in-hole Assembly Framework for Unseen Polygon Shapes via Sim-to-real Adaptation
Abstract: The study addresses the foundational and challenging task of peg-in-hole
assembly in robotics, where misalignments caused by sensor inaccuracies and
mechanical errors often result in insertion failures or jam... | Robotics |
What field is the article from? | Title: LongQLoRA: Efficient and Effective Method to Extend Context Length of Large Language Models
Abstract: We present LongQLoRA, an efficient and effective method to extend context
length of large language models with less training resources. LongQLoRA
combines the advantages of Position Interpolation, QLoRA and Shif... | Computational Linguistics |
What field is the article from? | Title: Representing visual classification as a linear combination of words
Abstract: Explainability is a longstanding challenge in deep learning, especially in
high-stakes domains like healthcare. Common explainability methods highlight
image regions that drive an AI model's decision. Humans, however, heavily rely
on l... | Artificial Intelligence |
What field is the article from? | Title: Constraint Model for the Satellite Image Mosaic Selection Problem
Abstract: Satellite imagery solutions are widely used to study and monitor different
regions of the Earth. However, a single satellite image can cover only a
limited area. In cases where a larger area of interest is studied, several
images must be... | Artificial Intelligence |
What field is the article from? | Title: Nova$^+$: Generative Language Models for Binaries
Abstract: Generative large language models (LLMs) pre-trained on code have shown
impressive effectiveness in code generation, program repair, and document
analysis. However, existing generative LLMs focus on source code and are not
specialized for binaries. There... | Software Engineering |
What field is the article from? | Title: tsMorph: generation of semi-synthetic time series to understand algorithm performance
Abstract: Time series forecasting is a subject of significant scientific and industrial
importance. Despite the widespread utilization of forecasting methods, there is
a dearth of research aimed at comprehending the conditions ... | Machine Learning |
What field is the article from? | Title: PCRDiffusion: Diffusion Probabilistic Models for Point Cloud Registration
Abstract: We propose a new framework that formulates point cloud registration as a
denoising diffusion process from noisy transformation to object transformation.
During training stage, object transformation diffuses from ground-truth
tran... | Computer Vision |
What field is the article from? | Title: Forecasting Auxiliary Energy Consumption for Electric Heavy-Duty Vehicles
Abstract: Accurate energy consumption prediction is crucial for optimizing the
operation of electric commercial heavy-duty vehicles, e.g., route planning for
charging. Moreover, understanding why certain predictions are cast is paramount
f... | Machine Learning |
What field is the article from? | Title: CG3D: Compositional Generation for Text-to-3D via Gaussian Splatting
Abstract: With the onset of diffusion-based generative models and their ability to
generate text-conditioned images, content generation has received a massive
invigoration. Recently, these models have been shown to provide useful guidance
for t... | Computer Vision |
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