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What field is the article from? | Title: DMS*: Minimizing Makespan for Multi-Agent Combinatorial Path Finding
Abstract: Multi-Agent Combinatorial Path Finding (MCPF) seeks collision-free paths for
multiple agents from their initial to goal locations, while visiting a set of
intermediate target locations in the middle of the paths. MCPF is challenging
a... | Robotics |
What field is the article from? | Title: The Self 2.0: How AI-Enhanced Self-Clones Transform Self-Perception and Improve Presentation Skills
Abstract: This study explores the impact of AI-generated digital self-clones on
improving online presentation skills. We carried out a mixed-design experiment
involving 44 international students, comparing self-re... | Human-Computer Interaction |
What field is the article from? | Title: Artificial Intelligence in Sustainable Vertical Farming
Abstract: As global challenges of population growth, climate change, and resource
scarcity intensify, the agricultural landscape is at a critical juncture.
Sustainable vertical farming emerges as a transformative solution to address
these challenges by maxi... | Computers and Society |
What field is the article from? | Title: ECLM: Efficient Edge-Cloud Collaborative Learning with Continuous Environment Adaptation
Abstract: Pervasive mobile AI applications primarily employ one of the two learning
paradigms: cloud-based learning (with powerful large models) or on-device
learning (with lightweight small models). Despite their own advant... | Machine Learning |
What field is the article from? | Title: The Generative AI Paradox: "What It Can Create, It May Not Understand"
Abstract: The recent wave of generative AI has sparked unprecedented global attention,
with both excitement and concern over potentially superhuman levels of
artificial intelligence: models now take only seconds to produce outputs that
would ... | Artificial Intelligence |
What field is the article from? | Title: Backdoor Activation Attack: Attack Large Language Models using Activation Steering for Safety-Alignment
Abstract: To ensure AI safety, instruction-tuned Large Language Models (LLMs) are
specifically trained to ensure alignment, which refers to making models behave
in accordance with human intentions. While these... | Cryptography and Security |
What field is the article from? | Title: MOCHa: Multi-Objective Reinforcement Mitigating Caption Hallucinations
Abstract: While recent years have seen rapid progress in image-conditioned text
generation, image captioning still suffers from the fundamental issue of
hallucinations, the generation of spurious details that cannot be inferred from
the given... | Computer Vision |
What field is the article from? | Title: Theory of Mind in Large Language Models: Examining Performance of 11 State-of-the-Art models vs. Children Aged 7-10 on Advanced Tests
Abstract: To what degree should we ascribe cognitive capacities to Large Language
Models (LLMs), such as the ability to reason about intentions and beliefs known
as Theory of Mind... | Computational Linguistics |
What field is the article from? | Title: Leveraging Large Language Models to Build and Execute Computational Workflows
Abstract: The recent development of large language models (LLMs) with multi-billion
parameters, coupled with the creation of user-friendly application programming
interfaces (APIs), has paved the way for automatically generating and ex... | Artificial Intelligence |
What field is the article from? | Title: Towards Improving Robustness Against Common Corruptions in Object Detectors Using Adversarial Contrastive Learning
Abstract: Neural networks have revolutionized various domains, exhibiting remarkable
accuracy in tasks like natural language processing and computer vision.
However, their vulnerability to slight al... | Computer Vision |
What field is the article from? | Title: Towards the Inferrence of Structural Similarity of Combinatorial Landscapes
Abstract: One of the most common problem-solving heuristics is by analogy. For a given
problem, a solver can be viewed as a strategic walk on its fitness landscape.
Thus if a solver works for one problem instance, we expect it will also ... | Machine Learning |
What field is the article from? | Title: Virtual Action Actor-Critic Framework for Exploration (Student Abstract)
Abstract: Efficient exploration for an agent is challenging in reinforcement learning
(RL). In this paper, a novel actor-critic framework namely virtual action
actor-critic (VAAC), is proposed to address the challenge of efficient
explorati... | Machine Learning |
What field is the article from? | Title: FedFN: Feature Normalization for Alleviating Data Heterogeneity Problem in Federated Learning
Abstract: Federated Learning (FL) is a collaborative method for training models while
preserving data privacy in decentralized settings. However, FL encounters
challenges related to data heterogeneity, which can result ... | Machine Learning |
What field is the article from? | Title: Integrating Summarization and Retrieval for Enhanced Personalization via Large Language Models
Abstract: Personalization, the ability to tailor a system to individual users, is an
essential factor in user experience with natural language processing (NLP)
systems. With the emergence of Large Language Models (LLMs... | Computational Linguistics |
What field is the article from? | Title: Bias Resilient Multi-Step Off-Policy Goal-Conditioned Reinforcement Learning
Abstract: In goal-conditioned reinforcement learning (GCRL), sparse rewards present
significant challenges, often obstructing efficient learning. Although
multi-step GCRL can boost this efficiency, it can also lead to off-policy
biases ... | Machine Learning |
What field is the article from? | Title: Transfer of Reinforcement Learning-Based Controllers from Model- to Hardware-in-the-Loop
Abstract: The process of developing control functions for embedded systems is
resource-, time-, and data-intensive, often resulting in sub-optimal cost and
solutions approaches. Reinforcement Learning (RL) has great potentia... | Machine Learning |
What field is the article from? | Title: Open Knowledge Base Canonicalization with Multi-task Unlearning
Abstract: The construction of large open knowledge bases (OKBs) is integral to many
applications in the field of mobile computing. Noun phrases and relational
phrases in OKBs often suffer from redundancy and ambiguity, which calls for the
investigat... | Artificial Intelligence |
What field is the article from? | Title: Panoptica -- instance-wise evaluation of 3D semantic and instance segmentation maps
Abstract: This paper introduces panoptica, a versatile and performance-optimized
package designed for computing instance-wise segmentation quality metrics from
2D and 3D segmentation maps. panoptica addresses the limitations of e... | Computer Vision |
What field is the article from? | Title: Enhancing Functional Data Analysis with Sequential Neural Networks: Advantages and Comparative Study
Abstract: Functional Data Analysis (FDA) is a statistical domain developed to handle
functional data characterized by high dimensionality and complex data
structures. Sequential Neural Networks (SNNs) are special... | Machine Learning |
What field is the article from? | Title: CharacterGLM: Customizing Chinese Conversational AI Characters with Large Language Models
Abstract: In this paper, we present CharacterGLM, a series of models built upon
ChatGLM, with model sizes ranging from 6B to 66B parameters. Our CharacterGLM
is designed for generating Character-based Dialogues (CharacterDi... | Computational Linguistics |
What field is the article from? | Title: Probabilistic Inference in Reinforcement Learning Done Right
Abstract: A popular perspective in Reinforcement learning (RL) casts the problem as
probabilistic inference on a graphical model of the Markov decision process
(MDP). The core object of study is the probability of each state-action pair
being visited u... | Machine Learning |
What field is the article from? | Title: Adapt Anything: Tailor Any Image Classifiers across Domains And Categories Using Text-to-Image Diffusion Models
Abstract: We do not pursue a novel method in this paper, but aim to study if a modern
text-to-image diffusion model can tailor any task-adaptive image classifier
across domains and categories. Existing... | Computer Vision |
What field is the article from? | Title: A Review On Table Recognition Based On Deep Learning
Abstract: Table recognition is using the computer to automatically understand the
table, to detect the position of the table from the document or picture, and to
correctly extract and identify the internal structure and content of the table.
After earlier main... | Computer Vision |
What field is the article from? | Title: ARIA: On the interaction between Architectures, Aggregation methods and Initializations in federated visual classification
Abstract: Federated Learning (FL) is a collaborative training paradigm that allows for
privacy-preserving learning of cross-institutional models by eliminating the
exchange of sensitive data... | Computer Vision |
What field is the article from? | Title: Causal Structure Learning Supervised by Large Language Model
Abstract: Causal discovery from observational data is pivotal for deciphering complex
relationships. Causal Structure Learning (CSL), which focuses on deriving
causal Directed Acyclic Graphs (DAGs) from data, faces challenges due to vast
DAG spaces and... | Artificial Intelligence |
What field is the article from? | Title: AviationGPT: A Large Language Model for the Aviation Domain
Abstract: The advent of ChatGPT and GPT-4 has captivated the world with large language
models (LLMs), demonstrating exceptional performance in question-answering,
summarization, and content generation. The aviation industry is characterized
by an abunda... | Computational Linguistics |
What field is the article from? | Title: Conceptual Model Interpreter for Large Language Models
Abstract: Large Language Models (LLMs) recently demonstrated capabilities for
generating source code in common programming languages. Additionally,
commercial products such as ChatGPT 4 started to provide code interpreters,
allowing for the automatic executi... | Software Engineering |
What field is the article from? | Title: Fin-QD: A Computational Design Framework for Soft Grippers: Integrating MAP-Elites and High-fidelity FEM
Abstract: Computational design can excite the full potential of soft robotics that has
the drawbacks of being highly nonlinear from material, structure, and contact.
Up to date, enthusiastic research interest... | Robotics |
What field is the article from? | Title: ROAM: memory-efficient large DNN training via optimized operator ordering and memory layout
Abstract: As deep learning models continue to increase in size, the memory requirements
for training have surged. While high-level techniques like offloading,
recomputation, and compression can alleviate memory pressure, ... | Machine Learning |
What field is the article from? | Title: An Integrative Paradigm for Enhanced Stroke Prediction: Synergizing XGBoost and xDeepFM Algorithms
Abstract: Stroke prediction plays a crucial role in preventing and managing this
debilitating condition. In this study, we address the challenge of stroke
prediction using a comprehensive dataset, and propose an en... | Computer Vision |
What field is the article from? | Title: Kinematic-aware Prompting for Generalizable Articulated Object Manipulation with LLMs
Abstract: Generalizable articulated object manipulation is essential for home-assistant
robots. Recent efforts focus on imitation learning from demonstrations or
reinforcement learning in simulation, however, due to the prohibi... | Robotics |
What field is the article from? | Title: Formal Methods for Autonomous Systems
Abstract: Formal methods refer to rigorous, mathematical approaches to system
development and have played a key role in establishing the correctness of
safety-critical systems. The main building blocks of formal methods are models
and specifications, which are analogous to b... | Artificial Intelligence |
What field is the article from? | Title: NOD-TAMP: Multi-Step Manipulation Planning with Neural Object Descriptors
Abstract: Developing intelligent robots for complex manipulation tasks in household and
factory settings remains challenging due to long-horizon tasks, contact-rich
manipulation, and the need to generalize across a wide variety of object s... | Robotics |
What field is the article from? | Title: zkFDL: An efficient and privacy-preserving decentralized federated learning with zero knowledge proof
Abstract: Federated leaning (FL) has been frequently used in various field of studies
and businesses. Traditional centralized FL systems suffer from serious issues.
To address these concerns, decentralized feder... | Cryptography and Security |
What field is the article from? | Title: Appearance Codes using Joint Embedding Learning of Multiple Modalities
Abstract: The use of appearance codes in recent work on generative modeling has enabled
novel view renders with variable appearance and illumination, such as day-time
and night-time renders of a scene. A major limitation of this technique is ... | Computer Vision |
What field is the article from? | Title: Traffic Signal Control Using Lightweight Transformers: An Offline-to-Online RL Approach
Abstract: Efficient traffic signal control is critical for reducing traffic congestion
and improving overall transportation efficiency. The dynamic nature of traffic
flow has prompted researchers to explore Reinforcement Lear... | Machine Learning |
What field is the article from? | Title: An Empathetic User-Centric Chatbot for Emotional Support
Abstract: This paper explores the intersection of Otome Culture and artificial
intelligence, particularly focusing on how Otome-oriented games fulfill the
emotional needs of young women. These games, which are deeply rooted in a
subcultural understanding o... | Human-Computer Interaction |
What field is the article from? | Title: GPT in Data Science: A Practical Exploration of Model Selection
Abstract: There is an increasing interest in leveraging Large Language Models (LLMs)
for managing structured data and enhancing data science processes. Despite the
potential benefits, this integration poses significant questions regarding
their reli... | Artificial Intelligence |
What field is the article from? | Title: A Survey of AI Text-to-Image and AI Text-to-Video Generators
Abstract: Text-to-Image and Text-to-Video AI generation models are revolutionary
technologies that use deep learning and natural language processing (NLP)
techniques to create images and videos from textual descriptions. This paper
investigates cutting... | Computer Vision |
What field is the article from? | Title: LLM-TAKE: Theme Aware Keyword Extraction Using Large Language Models
Abstract: Keyword extraction is one of the core tasks in natural language processing.
Classic extraction models are notorious for having a short attention span which
make it hard for them to conclude relational connections among the words and
s... | Information Retrieval |
What field is the article from? | Title: SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization
Abstract: In real-world scenarios, achieving domain generalization (DG) presents
significant challenges as models are required to generalize to unknown target
distributions. Generalizing to unseen multi-modal distributions poses even... | Computer Vision |
What field is the article from? | Title: A Comparative Analysis of Large Language Models for Code Documentation Generation
Abstract: This paper presents a comprehensive comparative analysis of Large Language
Models (LLMs) for generation of code documentation. Code documentation is an
essential part of the software writing process. The paper evaluates m... | Software Engineering |
What field is the article from? | Title: Can persistent homology whiten Transformer-based black-box models? A case study on BERT compression
Abstract: Large Language Models (LLMs) like BERT have gained significant prominence due
to their remarkable performance in various natural language processing tasks.
However, they come with substantial computation... | Machine Learning |
What field is the article from? | Title: Uplifting the Expressive Power of Graph Neural Networks through Graph Partitioning
Abstract: Graph Neural Networks (GNNs) have paved its way for being a cornerstone in
graph related learning tasks. From a theoretical perspective, the expressive
power of GNNs is primarily characterised according to their ability ... | Machine Learning |
What field is the article from? | Title: FAIRLABEL: Correcting Bias in Labels
Abstract: There are several algorithms for measuring fairness of ML models. A
fundamental assumption in these approaches is that the ground truth is fair or
unbiased. In real-world datasets, however, the ground truth often contains data
that is a result of historical and soci... | Machine Learning |
What field is the article from? | Title: Neuro-Symbolic Integration Brings Causal and Reliable Reasoning Proofs
Abstract: Though prompting LLMs with various reasoning structures produces reasoning
proofs along with answers, these proofs are not ensured to be causal and
reliable due to the inherent defects of LLMs. Tracking such deficiencies, we
present... | Artificial Intelligence |
What field is the article from? | Title: Diffusion Models for Reinforcement Learning: A Survey
Abstract: Diffusion models have emerged as a prominent class of generative models,
surpassing previous methods regarding sample quality and training stability.
Recent works have shown the advantages of diffusion models in improving
reinforcement learning (RL)... | Machine Learning |
What field is the article from? | Title: Analyzing and Explaining Image Classifiers via Diffusion Guidance
Abstract: While deep learning has led to huge progress in complex image classification
tasks like ImageNet, unexpected failure modes, e.g. via spurious features, call
into question how reliably these classifiers work in the wild. Furthermore, for
... | Computer Vision |
What field is the article from? | Title: GPT-4V(ision) as A Social Media Analysis Engine
Abstract: Recent research has offered insights into the extraordinary capabilities of
Large Multimodal Models (LMMs) in various general vision and language tasks.
There is growing interest in how LMMs perform in more specialized domains.
Social media content, inher... | Computer Vision |
What field is the article from? | Title: Fast Sampling via De-randomization for Discrete Diffusion Models
Abstract: Diffusion models have emerged as powerful tools for high-quality data
generation, such as image generation. Despite its success in continuous spaces,
discrete diffusion models, which apply to domains such as texts and natural
languages, r... | Machine Learning |
What field is the article from? | Title: Confounder Balancing in Adversarial Domain Adaptation for Pre-Trained Large Models Fine-Tuning
Abstract: The excellent generalization, contextual learning, and emergence abilities in
the pre-trained large models (PLMs) handle specific tasks without direct
training data, making them the better foundation models i... | Machine Learning |
What field is the article from? | Title: Panel Transitions for Genre Analysis in Visual Narratives
Abstract: Understanding how humans communicate and perceive narratives is important for
media technology research and development. This is particularly important in
current times when there are tools and algorithms that are easily available for
amateur us... | Artificial Intelligence |
What field is the article from? | Title: DONUT-hole: DONUT Sparsification by Harnessing Knowledge and Optimizing Learning Efficiency
Abstract: This paper introduces DONUT-hole, a sparse OCR-free visual document
understanding (VDU) model that addresses the limitations of its predecessor
model, dubbed DONUT. The DONUT model, leveraging a transformer arch... | Computer Vision |
What field is the article from? | Title: Human-Centric Autonomous Systems With LLMs for User Command Reasoning
Abstract: The evolution of autonomous driving has made remarkable advancements in
recent years, evolving into a tangible reality. However, a human-centric
large-scale adoption hinges on meeting a variety of multifaceted requirements.
To ensure... | Computational Linguistics |
What field is the article from? | Title: An adversarial attack approach for eXplainable AI evaluation on deepfake detection models
Abstract: With the rising concern on model interpretability, the application of
eXplainable AI (XAI) tools on deepfake detection models has been a topic of
interest recently. In image classification tasks, XAI tools highlig... | Computer Vision |
What field is the article from? | Title: Reinforcement Replaces Supervision: Query focused Summarization using Deep Reinforcement Learning
Abstract: Query-focused Summarization (QfS) deals with systems that generate summaries
from document(s) based on a query. Motivated by the insight that Reinforcement
Learning (RL) provides a generalization to Superv... | Computational Linguistics |
What field is the article from? | Title: MGCT: Mutual-Guided Cross-Modality Transformer for Survival Outcome Prediction using Integrative Histopathology-Genomic Features
Abstract: The rapidly emerging field of deep learning-based computational pathology has
shown promising results in utilizing whole slide images (WSIs) to objectively
prognosticate canc... | Computer Vision |
What field is the article from? | Title: Emotion-Aware Music Recommendation System: Enhancing User Experience Through Real-Time Emotional Context
Abstract: This study addresses the deficiency in conventional music recommendation
systems by focusing on the vital role of emotions in shaping users music
choices. These systems often disregard the emotional... | Information Retrieval |
What field is the article from? | Title: GPT-4 and Safety Case Generation: An Exploratory Analysis
Abstract: In the ever-evolving landscape of software engineering, the emergence of
large language models (LLMs) and conversational interfaces, exemplified by
ChatGPT, is nothing short of revolutionary. While their potential is undeniable
across various do... | Software Engineering |
What field is the article from? | Title: Conversational AI Threads for Visualizing Multidimensional Datasets
Abstract: Generative Large Language Models (LLMs) show potential in data analysis, yet
their full capabilities remain uncharted. Our work explores the capabilities of
LLMs for creating and refining visualizations via conversational interfaces. W... | Human-Computer Interaction |
What field is the article from? | Title: CONFORM: Contrast is All You Need For High-Fidelity Text-to-Image Diffusion Models
Abstract: Images produced by text-to-image diffusion models might not always faithfully
represent the semantic intent of the provided text prompt, where the model
might overlook or entirely fail to produce certain objects. Existin... | Computer Vision |
What field is the article from? | Title: Reinforcement Learning from Diffusion Feedback: Q* for Image Search
Abstract: Large vision-language models are steadily gaining personalization
capabilities at the cost of fine-tuning or data augmentation. We present two
models for image generation using model-agnostic learning that align semantic
priors with ge... | Computer Vision |
What field is the article from? | Title: Think Before You Speak: Cultivating Communication Skills of Large Language Models via Inner Monologue
Abstract: The emergence of large language models (LLMs) further improves the
capabilities of open-domain dialogue systems and can generate fluent, coherent,
and diverse responses. However, LLMs still lack an imp... | Computational Linguistics |
What field is the article from? | Title: Learn to Refuse: Making Large Language Models More Controllable and Reliable through Knowledge Scope Limitation and Refusal Mechanism
Abstract: Large language models (LLMs) have demonstrated impressive language
understanding and generation capabilities, enabling them to answer a wide range
of questions across va... | Computational Linguistics |
What field is the article from? | Title: A Unified Approach to Count-Based Weakly-Supervised Learning
Abstract: High-quality labels are often very scarce, whereas unlabeled data with
inferred weak labels occurs more naturally. In many cases, these weak labels
dictate the frequency of each respective class over a set of instances. In this
paper, we deve... | Machine Learning |
What field is the article from? | Title: In-Context Ability Transfer for Question Decomposition in Complex QA
Abstract: Answering complex questions is a challenging task that requires question
decomposition and multistep reasoning for arriving at the solution. While
existing supervised and unsupervised approaches are specialized to a certain
task and i... | Computational Linguistics |
What field is the article from? | Title: Customize your NeRF: Adaptive Source Driven 3D Scene Editing via Local-Global Iterative Training
Abstract: In this paper, we target the adaptive source driven 3D scene editing task by
proposing a CustomNeRF model that unifies a text description or a reference
image as the editing prompt. However, obtaining desir... | Computer Vision |
What field is the article from? | Title: DSR-Diff: Depth Map Super-Resolution with Diffusion Model
Abstract: Color-guided depth map super-resolution (CDSR) improve the spatial resolution
of a low-quality depth map with the corresponding high-quality color map,
benefiting various applications such as 3D reconstruction, virtual reality, and
augmented rea... | Computer Vision |
What field is the article from? | Title: AFPQ: Asymmetric Floating Point Quantization for LLMs
Abstract: Large language models (LLMs) show great performance in various tasks, but
face deployment challenges from limited memory capacity and bandwidth. Low-bit
weight quantization can save memory and accelerate inference. Although
floating-point (FP) forma... | Computational Linguistics |
What field is the article from? | Title: Keeping Users Engaged During Repeated Administration of the Same Questionnaire: Using Large Language Models to Reliably Diversify Questions
Abstract: Standardized, validated questionnaires are vital tools in HCI research and
healthcare, offering dependable self-report data. However, their repeated use
in longitu... | Human-Computer Interaction |
What field is the article from? | Title: Robust Domain Misinformation Detection via Multi-modal Feature Alignment
Abstract: Social media misinformation harms individuals and societies and is
potentialized by fast-growing multi-modal content (i.e., texts and images),
which accounts for higher "credibility" than text-only news pieces. Although
existing s... | Artificial Intelligence |
What field is the article from? | Title: Making Data Work Count
Abstract: In this paper, we examine the work of data annotation. Specifically, we focus
on the role of counting or quantification in organising annotation work. Based
on an ethnographic study of data annotation in two outsourcing centres in
India, we observe that counting practices and its... | Human-Computer Interaction |
What field is the article from? | Title: Closed Drafting as a Case Study for First-Principle Interpretability, Memory, and Generalizability in Deep Reinforcement Learning
Abstract: Closed drafting or "pick and pass" is a popular game mechanic where each
round players select a card or other playable element from their hand and pass
the rest to the next ... | Machine Learning |
What field is the article from? | Title: Breaking Boundaries: Balancing Performance and Robustness in Deep Wireless Traffic Forecasting
Abstract: Balancing the trade-off between accuracy and robustness is a long-standing
challenge in time series forecasting. While most of existing robust algorithms
have achieved certain suboptimal performance on clean ... | Machine Learning |
What field is the article from? | Title: Foveation in the Era of Deep Learning
Abstract: In this paper, we tackle the challenge of actively attending to visual scenes
using a foveated sensor. We introduce an end-to-end differentiable foveated
active vision architecture that leverages a graph convolutional network to
process foveated images, and a simpl... | Computer Vision |
What field is the article from? | Title: AI-Generated Images Introduce Invisible Relevance Bias to Text-Image Retrieval
Abstract: With the advancement of generation models, AI-generated content (AIGC) is
becoming more realistic, flooding the Internet. A recent study suggests that
this phenomenon has elevated the issue of source bias in text retrieval f... | Information Retrieval |
What field is the article from? | Title: Cross-Domain Robustness of Transformer-based Keyphrase Generation
Abstract: Modern models for text generation show state-of-the-art results in many
natural language processing tasks. In this work, we explore the effectiveness
of abstractive text summarization models for keyphrase selection. A list of
keyphrases ... | Computational Linguistics |
What field is the article from? | Title: SCOPE-RL: A Python Library for Offline Reinforcement Learning and Off-Policy Evaluation
Abstract: This paper introduces SCOPE-RL, a comprehensive open-source Python software
designed for offline reinforcement learning (offline RL), off-policy evaluation
(OPE), and selection (OPS). Unlike most existing libraries ... | Machine Learning |
What field is the article from? | Title: Enhancing Lightweight Neural Networks for Small Object Detection in IoT Applications
Abstract: Advances in lightweight neural networks have revolutionized computer vision
in a broad range of IoT applications, encompassing remote monitoring and
process automation. However, the detection of small objects, which is... | Computer Vision |
What field is the article from? | Title: Jellyfish: A Large Language Model for Data Preprocessing
Abstract: In this paper, we present Jellyfish, an open-source LLM as a universal task
solver for DP. Built on the Llama 2 13B model, Jellyfish is instruction-tuned
with the datasets of several typical DP tasks including error detection, data
imputation, sc... | Artificial Intelligence |
What field is the article from? | Title: FormalGeo: The First Step Toward Human-like IMO-level Geometric Automated Reasoning
Abstract: This is the first paper in a series of work we have accomplished over the
past three years. In this paper, we have constructed a consistent formal plane
geometry system. This will serve as a crucial bridge between IMO-l... | Artificial Intelligence |
What field is the article from? | Title: Guided Flows for Generative Modeling and Decision Making
Abstract: Classifier-free guidance is a key component for enhancing the performance of
conditional generative models across diverse tasks. While it has previously
demonstrated remarkable improvements for the sample quality, it has only been
exclusively emp... | Machine Learning |
What field is the article from? | Title: MetaReVision: Meta-Learning with Retrieval for Visually Grounded Compositional Concept Acquisition
Abstract: Humans have the ability to learn novel compositional concepts by recalling
and generalizing primitive concepts acquired from past experiences. Inspired by
this observation, in this paper, we propose MetaR... | Computational Linguistics |
What field is the article from? | Title: Let's Think Outside the Box: Exploring Leap-of-Thought in Large Language Models with Creative Humor Generation
Abstract: Chain-of-Thought (CoT) guides large language models (LLMs) to reason
step-by-step, and can motivate their logical reasoning ability. While effective
for logical tasks, CoT is not conducive to ... | Artificial Intelligence |
What field is the article from? | Title: Designing Long-term Group Fair Policies in Dynamical Systems
Abstract: Neglecting the effect that decisions have on individuals (and thus, on the
underlying data distribution) when designing algorithmic decision-making
policies may increase inequalities and unfairness in the long term - even if
fairness consider... | Artificial Intelligence |
What field is the article from? | Title: Autonomous Robotic Reinforcement Learning with Asynchronous Human Feedback
Abstract: Ideally, we would place a robot in a real-world environment and leave it
there improving on its own by gathering more experience autonomously. However,
algorithms for autonomous robotic learning have been challenging to realize ... | Machine Learning |
What field is the article from? | Title: Multi-State Brain Network Discovery
Abstract: Brain network discovery aims to find nodes and edges from the spatio-temporal
signals obtained by neuroimaging data, such as fMRI scans of human brains.
Existing methods tend to derive representative or average brain networks,
assuming observed signals are generated ... | Machine Learning |
What field is the article from? | Title: Safe Reinforcement Learning in Tensor Reproducing Kernel Hilbert Space
Abstract: This paper delves into the problem of safe reinforcement learning (RL) in a
partially observable environment with the aim of achieving safe-reachability
objectives. In traditional partially observable Markov decision processes
(POMD... | Machine Learning |
What field is the article from? | Title: TIAGo RL: Simulated Reinforcement Learning Environments with Tactile Data for Mobile Robots
Abstract: Tactile information is important for robust performance in robotic tasks that
involve physical interaction, such as object manipulation. However, with more
data included in the reasoning and control process, mod... | Robotics |
What field is the article from? | Title: Generalized Contrastive Divergence: Joint Training of Energy-Based Model and Diffusion Model through Inverse Reinforcement Learning
Abstract: We present Generalized Contrastive Divergence (GCD), a novel objective
function for training an energy-based model (EBM) and a sampler simultaneously.
GCD generalizes Cont... | Machine Learning |
What field is the article from? | Title: StochGradAdam: Accelerating Neural Networks Training with Stochastic Gradient Sampling
Abstract: In the rapidly advancing domain of deep learning optimization, this paper
unveils the StochGradAdam optimizer, a novel adaptation of the well-regarded
Adam algorithm. Central to StochGradAdam is its gradient sampling... | Machine Learning |
What field is the article from? | Title: Technical Report on the Learning of Case Relevance in Case-Based Reasoning with Abstract Argumentation
Abstract: Case-based reasoning is known to play an important role in several legal
settings. In this paper we focus on a recent approach to case-based reasoning,
supported by an instantiation of abstract argume... | Artificial Intelligence |
What field is the article from? | Title: Weakly-supervised Deep Cognate Detection Framework for Low-Resourced Languages Using Morphological Knowledge of Closely-Related Languages
Abstract: Exploiting cognates for transfer learning in under-resourced languages is an
exciting opportunity for language understanding tasks, including unsupervised
machine tr... | Computational Linguistics |
What field is the article from? | Title: Proving Conjectures Acquired by Composing Multiple Biases
Abstract: We present the proofs of the conjectures mentioned in the paper published in
the proceedings of the 2024 AAAI conference [1], and discovered by the
decomposition methods presented in the same paper. | Artificial Intelligence |
What field is the article from? | Title: MIA-BAD: An Approach for Enhancing Membership Inference Attack and its Mitigation with Federated Learning
Abstract: The membership inference attack (MIA) is a popular paradigm for compromising
the privacy of a machine learning (ML) model. MIA exploits the natural
inclination of ML models to overfit upon the trai... | Cryptography and Security |
What field is the article from? | Title: Unifying Structure and Language Semantic for Efficient Contrastive Knowledge Graph Completion with Structured Entity Anchors
Abstract: The goal of knowledge graph completion (KGC) is to predict missing links in a
KG using trained facts that are already known. In recent, pre-trained language
model (PLM) based met... | Artificial Intelligence |
What field is the article from? | Title: Aiming to Minimize Alcohol-Impaired Road Fatalities: Utilizing Fairness-Aware and Domain Knowledge-Infused Artificial Intelligence
Abstract: Approximately 30% of all traffic fatalities in the United States are
attributed to alcohol-impaired driving. This means that, despite stringent laws
against this offense in... | Machine Learning |
What field is the article from? | Title: BELT: Old-School Backdoor Attacks can Evade the State-of-the-Art Defense with Backdoor Exclusivity Lifting
Abstract: Deep neural networks (DNNs) are susceptible to backdoor attacks, where
malicious functionality is embedded to allow attackers to trigger incorrect
classifications. Old-school backdoor attacks use ... | Cryptography and Security |
What field is the article from? | Title: EHRTutor: Enhancing Patient Understanding of Discharge Instructions
Abstract: Large language models have shown success as a tutor in education in various
fields. Educating patients about their clinical visits plays a pivotal role in
patients' adherence to their treatment plans post-discharge. This paper
presents... | Computational Linguistics |
What field is the article from? | Title: ChatTraffic: Text-to-Traffic Generation via Diffusion Model
Abstract: Traffic prediction is one of the most significant foundations in Intelligent
Transportation Systems (ITS). Traditional traffic prediction methods rely only
on historical traffic data to predict traffic trends and face two main
challenges. 1) i... | Machine Learning |
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