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What field is the article from? | Title: Multi-level Reasoning for Robotic Assembly: From Sequence Inference to Contact Selection
Abstract: Automating the assembly of objects from their parts is a complex problem with
innumerable applications in manufacturing, maintenance, and recycling. Unlike
existing research, which is limited to target segmentation... | Robotics |
What field is the article from? | Title: Dialogue-based generation of self-driving simulation scenarios using Large Language Models
Abstract: Simulation is an invaluable tool for developing and evaluating controllers
for self-driving cars. Current simulation frameworks are driven by
highly-specialist domain specific languages, and so a natural language... | Artificial Intelligence |
What field is the article from? | Title: Online Boosting Adaptive Learning under Concept Drift for Multistream Classification
Abstract: Multistream classification poses significant challenges due to the necessity
for rapid adaptation in dynamic streaming processes with concept drift. Despite
the growing research outcomes in this area, there has been a ... | Machine Learning |
What field is the article from? | Title: From Dialogue to Diagram: Task and Relationship Extraction from Natural Language for Accelerated Business Process Prototyping
Abstract: The automatic transformation of verbose, natural language descriptions into
structured process models remains a challenge of significant complexity - This
paper introduces a con... | Computational Linguistics |
What field is the article from? | Title: Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code
Abstract: In this work we systematically review the recent advancements in code
processing with language models, covering 50+ models, 30+ evaluation tasks,
170+ datasets, and 700 related works. We break down code proc... | Computational Linguistics |
What field is the article from? | Title: Mixing-Denoising Generalizable Occupancy Networks
Abstract: While current state-of-the-art generalizable implicit neural shape models
rely on the inductive bias of convolutions, it is still not entirely clear how
properties emerging from such biases are compatible with the task of 3D
reconstruction from point cl... | Computer Vision |
What field is the article from? | Title: Prompted Zero-Shot Multi-label Classification of Factual Incorrectness in Machine-Generated Summaries
Abstract: This study addresses the critical issue of factual inaccuracies in
machine-generated text summaries, an increasingly prevalent issue in
information dissemination. Recognizing the potential of such erro... | Computational Linguistics |
What field is the article from? | Title: Unsupervised textile defect detection using convolutional neural networks
Abstract: In this study, we propose a novel motif-based approach for unsupervised
textile anomaly detection that combines the benefits of traditional
convolutional neural networks with those of an unsupervised learning paradigm.
It consist... | Computer Vision |
What field is the article from? | Title: Measuring Five Accountable Talk Moves to Improve Instruction at Scale
Abstract: Providing consistent, individualized feedback to teachers on their
instruction can improve student learning outcomes. Such feedback can especially
benefit novice instructors who teach on online platforms and have limited
access to in... | Computers and Society |
What field is the article from? | Title: Towards Human-like Perception: Learning Structural Causal Model in Heterogeneous Graph
Abstract: Heterogeneous graph neural networks have become popular in various domains.
However, their generalizability and interpretability are limited due to the
discrepancy between their inherent inference flows and human rea... | Machine Learning |
What field is the article from? | Title: Pitfall of Optimism: Distributional Reinforcement Learning by Randomizing Risk Criterion
Abstract: Distributional reinforcement learning algorithms have attempted to utilize
estimated uncertainty for exploration, such as optimism in the face of
uncertainty. However, using the estimated variance for optimistic ex... | Machine Learning |
What field is the article from? | Title: ADAPTER-RL: Adaptation of Any Agent using Reinforcement Learning
Abstract: Deep Reinforcement Learning (DRL) agents frequently face challenges in
adapting to tasks outside their training distribution, including issues with
over-fitting, catastrophic forgetting and sample inefficiency. Although the
application of... | Artificial Intelligence |
What field is the article from? | Title: Batch Bayesian Optimization for Replicable Experimental Design
Abstract: Many real-world experimental design problems (a) evaluate multiple
experimental conditions in parallel and (b) replicate each condition multiple
times due to large and heteroscedastic observation noise. Given a fixed total
budget, this natu... | Machine Learning |
What field is the article from? | Title: FlowZero: Zero-Shot Text-to-Video Synthesis with LLM-Driven Dynamic Scene Syntax
Abstract: Text-to-video (T2V) generation is a rapidly growing research area that aims
to translate the scenes, objects, and actions within complex video text into a
sequence of coherent visual frames. We present FlowZero, a novel fr... | Computer Vision |
What field is the article from? | Title: Unveiling the Unseen Potential of Graph Learning through MLPs: Effective Graph Learners Using Propagation-Embracing MLPs
Abstract: Recent studies attempted to utilize multilayer perceptrons (MLPs) to solve
semi-supervised node classification on graphs, by training a student MLP by
knowledge distillation (KD) fro... | Machine Learning |
What field is the article from? | Title: Prompting LLMs with content plans to enhance the summarization of scientific articles
Abstract: This paper presents novel prompting techniques to improve the performance of
automatic summarization systems for scientific articles. Scientific article
summarization is highly challenging due to the length and comple... | Computational Linguistics |
What field is the article from? | Title: Perturbation-based Active Learning for Question Answering
Abstract: Building a question answering (QA) model with less annotation costs can be
achieved by utilizing active learning (AL) training strategy. It selects the
most informative unlabeled training data to update the model effectively.
Acquisition functio... | Computational Linguistics |
What field is the article from? | Title: Unsupervised Behavior Extraction via Random Intent Priors
Abstract: Reward-free data is abundant and contains rich prior knowledge of human
behaviors, but it is not well exploited by offline reinforcement learning (RL)
algorithms. In this paper, we propose UBER, an unsupervised approach to extract
useful behavio... | Machine Learning |
What field is the article from? | Title: Learning Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity
Abstract: This paper studies causal representation learning, the task of recovering
high-level latent variables and their causal relationships from low-level data
that we observe, assuming access to observations ge... | Machine Learning |
What field is the article from? | Title: Estimation of Concept Explanations Should be Uncertainty Aware
Abstract: Model explanations are very valuable for interpreting and debugging
prediction models. We study a specific kind of global explanations called
Concept Explanations, where the goal is to interpret a model using
human-understandable concepts. ... | Machine Learning |
What field is the article from? | Title: Robust and Scalable Hyperdimensional Computing With Brain-Like Neural Adaptations
Abstract: The Internet of Things (IoT) has facilitated many applications utilizing
edge-based machine learning (ML) methods to analyze locally collected data.
Unfortunately, popular ML algorithms often require intensive computation... | Machine Learning |
What field is the article from? | Title: CSGNN: Conquering Noisy Node labels via Dynamic Class-wise Selection
Abstract: Graph Neural Networks (GNNs) have emerged as a powerful tool for
representation learning on graphs, but they often suffer from overfitting and
label noise issues, especially when the data is scarce or imbalanced. Different
from the pa... | Machine Learning |
What field is the article from? | Title: Empowering Autonomous Driving with Large Language Models: A Safety Perspective
Abstract: Autonomous Driving (AD) faces crucial hurdles for commercial launch, notably
in the form of diminished public trust and safety concerns from long-tail
unforeseen driving scenarios. This predicament is due to the limitation o... | Artificial Intelligence |
What field is the article from? | Title: PaSCo: Urban 3D Panoptic Scene Completion with Uncertainty Awareness
Abstract: We propose the task of Panoptic Scene Completion (PSC) which extends the
recently popular Semantic Scene Completion (SSC) task with instance-level
information to produce a richer understanding of the 3D scene. Our PSC proposal
utilize... | Computer Vision |
What field is the article from? | Title: Meta Learning for Multi-View Visuomotor Systems
Abstract: This paper introduces a new approach for quickly adapting a multi-view
visuomotor system for robots to varying camera configurations from the baseline
setup. It utilises meta-learning to fine-tune the perceptual network while
keeping the policy network fi... | Robotics |
What field is the article from? | Title: rTisane: Externalizing conceptual models for data analysis increases engagement with domain knowledge and improves statistical model quality
Abstract: Statistical models should accurately reflect analysts' domain knowledge about
variables and their relationships. While recent tools let analysts express
these ass... | Human-Computer Interaction |
What field is the article from? | Title: Action Inference by Maximising Evidence: Zero-Shot Imitation from Observation with World Models
Abstract: Unlike most reinforcement learning agents which require an unrealistic amount
of environment interactions to learn a new behaviour, humans excel at learning
quickly by merely observing and imitating others. ... | Machine Learning |
What field is the article from? | Title: Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation
Abstract: In optimal transport (OT), a Monge map is known as a mapping that transports
a source distribution to a target distribution in the most cost-efficient way.
Recently, multiple neural estimators for Monge maps have been developed an... | Computer Vision |
What field is the article from? | Title: Synthetic Data Generation for Bridging Sim2Real Gap in a Production Environment
Abstract: Synthetic data is being used lately for training deep neural networks in
computer vision applications such as object detection, object segmentation and
6D object pose estimation. Domain randomization hereby plays an importa... | Computer Vision |
What field is the article from? | Title: Using State-of-the-Art Speech Models to Evaluate Oral Reading Fluency in Ghana
Abstract: This paper reports on a set of three recent experiments utilizing large-scale
speech models to evaluate the oral reading fluency (ORF) of students in Ghana.
While ORF is a well-established measure of foundational literacy, a... | Computational Linguistics |
What field is the article from? | Title: From Principle to Practice: Vertical Data Minimization for Machine Learning
Abstract: Aiming to train and deploy predictive models, organizations collect large
amounts of detailed client data, risking the exposure of private information in
the event of a breach. To mitigate this, policymakers increasingly demand... | Machine Learning |
What field is the article from? | Title: X-Adapter: Adding Universal Compatibility of Plugins for Upgraded Diffusion Model
Abstract: We introduce X-Adapter, a universal upgrader to enable the pretrained
plug-and-play modules (e.g., ControlNet, LoRA) to work directly with the
upgraded text-to-image diffusion model (e.g., SDXL) without further retraining... | Computer Vision |
What field is the article from? | Title: Handshape recognition for Argentinian Sign Language using ProbSom
Abstract: Automatic sign language recognition is an important topic within the areas of
human-computer interaction and machine learning. On the one hand, it poses a
complex challenge that requires the intervention of various knowledge areas,
such ... | Computer Vision |
What field is the article from? | Title: Multimodality of AI for Education: Towards Artificial General Intelligence
Abstract: This paper presents a comprehensive examination of how multimodal artificial
intelligence (AI) approaches are paving the way towards the realization of
Artificial General Intelligence (AGI) in educational contexts. It scrutinize... | Artificial Intelligence |
What field is the article from? | Title: TEAL: Tokenize and Embed ALL for Multi-modal Large Language Models
Abstract: Despite Multi-modal Large Language Models (MM-LLMs) have made exciting
strides recently, they are still struggling to efficiently model the
interactions among multi-modal inputs and the generation in non-textual
modalities. In this work... | Computational Linguistics |
What field is the article from? | Title: Kattis vs. ChatGPT: Assessment and Evaluation of Programming Tasks in the Age of Artificial Intelligence
Abstract: AI-powered education technologies can support students and teachers in
computer science education. However, with the recent developments in generative
AI, and especially the increasingly emerging po... | Artificial Intelligence |
What field is the article from? | Title: Pre-training LLMs using human-like development data corpus
Abstract: Pre-trained Large Language Models (LLMs) have shown success in a diverse set
of language inference and understanding tasks. The pre-training stage of LLMs
looks at a large corpus of raw textual data. The BabyLM shared task compares
LLM pre-trai... | Computational Linguistics |
What field is the article from? | Title: Verb Conjugation in Transformers Is Determined by Linear Encodings of Subject Number
Abstract: Deep architectures such as Transformers are sometimes criticized for having
uninterpretable "black-box" representations. We use causal intervention
analysis to show that, in fact, some linguistic features are represent... | Computational Linguistics |
What field is the article from? | Title: Transferring CLIP's Knowledge into Zero-Shot Point Cloud Semantic Segmentation
Abstract: Traditional 3D segmentation methods can only recognize a fixed range of
classes that appear in the training set, which limits their application in
real-world scenarios due to the lack of generalization ability. Large-scale
v... | Computer Vision |
What field is the article from? | Title: Reinforcement Neighborhood Selection for Unsupervised Graph Anomaly Detection
Abstract: Unsupervised graph anomaly detection is crucial for various practical
applications as it aims to identify anomalies in a graph that exhibit rare
patterns deviating significantly from the majority of nodes. Recent
advancements... | Machine Learning |
What field is the article from? | Title: Improving Denoising Diffusion Probabilistic Models via Exploiting Shared Representations
Abstract: In this work, we address the challenge of multi-task image generation with
limited data for denoising diffusion probabilistic models (DDPM), a class of
generative models that produce high-quality images by reversin... | Machine Learning |
What field is the article from? | Title: SCCA: Shifted Cross Chunk Attention for long contextual semantic expansion
Abstract: Sparse attention as a efficient method can significantly decrease the
computation cost, but current sparse attention tend to rely on window self
attention which block the global information flow. For this problem, we present
Shi... | Computational Linguistics |
What field is the article from? | Title: Mathematical Introduction to Deep Learning: Methods, Implementations, and Theory
Abstract: This book aims to provide an introduction to the topic of deep learning
algorithms. We review essential components of deep learning algorithms in full
mathematical detail including different artificial neural network (ANN)... | Machine Learning |
What field is the article from? | Title: A Survey of the Various Methodologies Towards making Artificial Intelligence More Explainable
Abstract: Machines are being increasingly used in decision-making processes, resulting
in the realization that decisions need explanations. Unfortunately, an
increasing number of these deployed models are of a 'black-bo... | Artificial Intelligence |
What field is the article from? | Title: Do Similar Entities have Similar Embeddings?
Abstract: Knowledge graph embedding models (KGEMs) developed for link prediction learn
vector representations for graph entities, known as embeddings. A common tacit
assumption is the KGE entity similarity assumption, which states that these
KGEMs retain the graph's s... | Artificial Intelligence |
What field is the article from? | Title: Sparse Low-rank Adaptation of Pre-trained Language Models
Abstract: Fine-tuning pre-trained large language models in a parameter-efficient manner
is widely studied for its effectiveness and efficiency. The popular method of
low-rank adaptation (LoRA) offers a notable approach, hypothesizing that the
adaptation p... | Computational Linguistics |
What field is the article from? | Title: AI Recommendation System for Enhanced Customer Experience: A Novel Image-to-Text Method
Abstract: Existing fashion recommendation systems encounter difficulties in using
visual data for accurate and personalized recommendations. This research
describes an innovative end-to-end pipeline that uses artificial intel... | Information Retrieval |
What field is the article from? | Title: Learning Independently from Causality in Multi-Agent Environments
Abstract: Multi-Agent Reinforcement Learning (MARL) comprises an area of growing
interest in the field of machine learning. Despite notable advances, there are
still problems that require investigation. The lazy agent pathology is a famous
problem... | Machine Learning |
What field is the article from? | Title: Taking control: Policies to address extinction risks from advanced AI
Abstract: This paper provides policy recommendations to reduce extinction risks from
advanced artificial intelligence (AI). First, we briefly provide background
information about extinction risks from AI. Second, we argue that voluntary
commit... | Artificial Intelligence |
What field is the article from? | Title: FoMo Rewards: Can we cast foundation models as reward functions?
Abstract: We explore the viability of casting foundation models as generic reward
functions for reinforcement learning. To this end, we propose a simple pipeline
that interfaces an off-the-shelf vision model with a large language model.
Specificall... | Machine Learning |
What field is the article from? | Title: Investigating Multi-Pivot Ensembling with Massively Multilingual Machine Translation Models
Abstract: Massively multilingual machine translation models allow for the translation
of a large number of languages with a single model, but have limited
performance on low- and very-low-resource translation directions. ... | Computational Linguistics |
What field is the article from? | Title: Towards Transferring Tactile-based Continuous Force Control Policies from Simulation to Robot
Abstract: The advent of tactile sensors in robotics has sparked many ideas on how
robots can leverage direct contact measurements of their environment
interactions to improve manipulation tasks. An important line of res... | Robotics |
What field is the article from? | Title: Speculative Exploration on the Concept of Artificial Agents Conducting Autonomous Research
Abstract: This paper engages in a speculative exploration of the concept of an
artificial agent capable of conducting research. Initially, it examines how the
act of research can be conceptually characterized, aiming to pr... | Artificial Intelligence |
What field is the article from? | Title: Towards Context-Aware Domain Generalization: Representing Environments with Permutation-Invariant Networks
Abstract: In this work, we show that information about the context of an input $X$ can
improve the predictions of deep learning models when applied in new domains or
production environments. We formalize th... | Machine Learning |
What field is the article from? | Title: Predictive Minds: LLMs As Atypical Active Inference Agents
Abstract: Large language models (LLMs) like GPT are often conceptualized as passive
predictors, simulators, or even stochastic parrots. We instead conceptualize
LLMs by drawing on the theory of active inference originating in cognitive
science and neuros... | Computational Linguistics |
What field is the article from? | Title: Detailed Human-Centric Text Description-Driven Large Scene Synthesis
Abstract: Text-driven large scene image synthesis has made significant progress with
diffusion models, but controlling it is challenging. While using additional
spatial controls with corresponding texts has improved the controllability of
large... | Computer Vision |
What field is the article from? | Title: Refine, Discriminate and Align: Stealing Encoders via Sample-Wise Prototypes and Multi-Relational Extraction
Abstract: This paper introduces RDA, a pioneering approach designed to address two
primary deficiencies prevalent in previous endeavors aiming at stealing
pre-trained encoders: (1) suboptimal performances... | Machine Learning |
What field is the article from? | Title: Probing and Mitigating Intersectional Social Biases in Vision-Language Models with Counterfactual Examples
Abstract: While vision-language models (VLMs) have achieved remarkable performance
improvements recently, there is growing evidence that these models also posses
harmful biases with respect to social attrib... | Computer Vision |
What field is the article from? | Title: Large Language Model-Driven Classroom Flipping: Empowering Student-Centric Peer Questioning with Flipped Interaction
Abstract: Reciprocal questioning is essential for effective teaching and learning,
fostering active engagement and deeper understanding through collaborative
interactions, especially in large clas... | Computers and Society |
What field is the article from? | Title: CPSOR-GCN: A Vehicle Trajectory Prediction Method Powered by Emotion and Cognitive Theory
Abstract: Active safety systems on vehicles often face problems with false alarms. Most
active safety systems predict the driver's trajectory with the assumption that
the driver is always in a normal emotion, and then infer... | Artificial Intelligence |
What field is the article from? | Title: Linking Surface Facts to Large-Scale Knowledge Graphs
Abstract: Open Information Extraction (OIE) methods extract facts from natural language
text in the form of ("subject"; "relation"; "object") triples. These facts are,
however, merely surface forms, the ambiguity of which impedes their downstream
usage; e.g.,... | Computational Linguistics |
What field is the article from? | Title: Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning
Abstract: Despite their tremendous success in many applications, large language models
often fall short of consistent reasoning and planning in various (language,
embodied, and social) scenarios, due to inherent limitatio... | Artificial Intelligence |
What field is the article from? | Title: A Self-enhancement Approach for Domain-specific Chatbot Training via Knowledge Mining and Digest
Abstract: Large Language Models (LLMs), despite their great power in language
generation, often encounter challenges when dealing with intricate and
knowledge-demanding queries in specific domains. This paper introdu... | Computational Linguistics |
What field is the article from? | Title: Towards Automated Recipe Genre Classification using Semi-Supervised Learning
Abstract: Sharing cooking recipes is a great way to exchange culinary ideas and provide
instructions for food preparation. However, categorizing raw recipes found
online into appropriate food genres can be challenging due to a lack of
a... | Computational Linguistics |
What field is the article from? | Title: On Tuning Neural ODE for Stability, Consistency and Faster Convergence
Abstract: Neural-ODE parameterize a differential equation using continuous depth neural
network and solve it using numerical ODE-integrator. These models offer a
constant memory cost compared to models with discrete sequence of hidden layers
... | Machine Learning |
What field is the article from? | Title: Mitigating Estimation Errors by Twin TD-Regularized Actor and Critic for Deep Reinforcement Learning
Abstract: We address the issue of estimation bias in deep reinforcement learning (DRL)
by introducing solution mechanisms that include a new, twin TD-regularized
actor-critic (TDR) method. It aims at reducing bot... | Machine Learning |
What field is the article from? | Title: An Information-Flow Perspective on Algorithmic Fairness
Abstract: This work presents insights gained by investigating the relationship between
algorithmic fairness and the concept of secure information flow. The problem of
enforcing secure information flow is well-studied in the context of information
security: ... | Cryptography and Security |
What field is the article from? | Title: Corrupting Convolution-based Unlearnable Datasets with Pixel-based Image Transformations
Abstract: Unlearnable datasets lead to a drastic drop in the generalization performance
of models trained on them by introducing elaborate and imperceptible
perturbations into clean training sets. Many existing defenses, e.g... | Computer Vision |
What field is the article from? | Title: Trustworthy AI: Deciding What to Decide
Abstract: When engaging in strategic decision-making, we are frequently confronted with
overwhelming information and data. The situation can be further complicated
when certain pieces of evidence contradict each other or become paradoxical.
The primary challenge is how to ... | Artificial Intelligence |
What field is the article from? | Title: PathoDuet: Foundation Models for Pathological Slide Analysis of H&E and IHC Stains
Abstract: Large amounts of digitized histopathological data display a promising future
for developing pathological foundation models via self-supervised learning
methods. Foundation models pretrained with these methods serve as a ... | Computer Vision |
What field is the article from? | Title: Informative Priors Improve the Reliability of Multimodal Clinical Data Classification
Abstract: Machine learning-aided clinical decision support has the potential to
significantly improve patient care. However, existing efforts in this domain
for principled quantification of uncertainty have largely been limited... | Computer Vision |
What field is the article from? | Title: An Eye on Clinical BERT: Investigating Language Model Generalization for Diabetic Eye Disease Phenotyping
Abstract: Diabetic eye disease is a major cause of blindness worldwide. The ability to
monitor relevant clinical trajectories and detect lapses in care is critical to
managing the disease and preventing blin... | Computational Linguistics |
What field is the article from? | Title: JaxMARL: Multi-Agent RL Environments in JAX
Abstract: Benchmarks play an important role in the development of machine learning
algorithms. For example, research in reinforcement learning (RL) has been
heavily influenced by available environments and benchmarks. However, RL
environments are traditionally run on t... | Machine Learning |
What field is the article from? | Title: Tackling the Abstraction and Reasoning Corpus (ARC) with Object-centric Models and the MDL Principle
Abstract: The Abstraction and Reasoning Corpus (ARC) is a challenging benchmark,
introduced to foster AI research towards human-level intelligence. It is a
collection of unique tasks about generating colored grid... | Artificial Intelligence |
What field is the article from? | Title: TempME: Towards the Explainability of Temporal Graph Neural Networks via Motif Discovery
Abstract: Temporal graphs are widely used to model dynamic systems with time-varying
interactions. In real-world scenarios, the underlying mechanisms of generating
future interactions in dynamic systems are typically governe... | Machine Learning |
What field is the article from? | Title: Discriminator Guidance for Autoregressive Diffusion Models
Abstract: We introduce discriminator guidance in the setting of Autoregressive
Diffusion Models. The use of a discriminator to guide a diffusion process has
previously been used for continuous diffusion models, and in this work we
derive ways of using a ... | Machine Learning |
What field is the article from? | Title: Causality Analysis for Evaluating the Security of Large Language Models
Abstract: Large Language Models (LLMs) such as GPT and Llama2 are increasingly adopted
in many safety-critical applications. Their security is thus essential. Even
with considerable efforts spent on reinforcement learning from human feedback... | Artificial Intelligence |
What field is the article from? | Title: Architecture of Data Anomaly Detection-Enhanced Decentralized Expert System for Early-Stage Alzheimer's Disease Prediction
Abstract: Alzheimer's Disease is a global health challenge that requires early and
accurate detection to improve patient outcomes. Magnetic Resonance Imaging
(MRI) holds significant diagnost... | Cryptography and Security |
What field is the article from? | Title: Defense semantics of argumentation: revisit
Abstract: In this paper we introduce a novel semantics, called defense semantics, for
Dung's abstract argumentation frameworks in terms of a notion of (partial)
defence, which is a triple encoding that one argument is (partially) defended
by another argument via attack... | Artificial Intelligence |
What field is the article from? | Title: LiFT: Unsupervised Reinforcement Learning with Foundation Models as Teachers
Abstract: We propose a framework that leverages foundation models as teachers, guiding
a reinforcement learning agent to acquire semantically meaningful behavior
without human feedback. In our framework, the agent receives task instruct... | Machine Learning |
What field is the article from? | Title: A Method to Improve the Performance of Reinforcement Learning Based on the Y Operator for a Class of Stochastic Differential Equation-Based Child-Mother Systems
Abstract: This paper introduces a novel operator, termed the Y operator, to elevate
control performance in Actor-Critic(AC) based reinforcement learning... | Artificial Intelligence |
What field is the article from? | Title: Gradient Informed Proximal Policy Optimization
Abstract: We introduce a novel policy learning method that integrates analytical
gradients from differentiable environments with the Proximal Policy
Optimization (PPO) algorithm. To incorporate analytical gradients into the PPO
framework, we introduce the concept of... | Machine Learning |
What field is the article from? | Title: Comparison of metaheuristics for the firebreak placement problem: a simulation-based optimization approach
Abstract: The problem of firebreak placement is crucial for fire prevention, and its
effectiveness at landscape scale will depend on their ability to impede the
progress of future wildfires. To provide an a... | Artificial Intelligence |
What field is the article from? | Title: What Planning Problems Can A Relational Neural Network Solve?
Abstract: Goal-conditioned policies are generally understood to be "feed-forward"
circuits, in the form of neural networks that map from the current state and
the goal specification to the next action to take. However, under what
circumstances such a ... | Machine Learning |
What field is the article from? | Title: New Boolean satisfiability problem heuristic strategy: Minimal Positive Negative Product Strategy
Abstract: This study presents a novel heuristic algorithm called the "Minimal Positive
Negative Product Strategy" to guide the CDCL algorithm in solving the Boolean
satisfiability problem. It provides a mathematical... | Artificial Intelligence |
What field is the article from? | Title: Mixed Distillation Helps Smaller Language Model Better Reasoning
Abstract: Despite the remarkable performance of large language models (LLMs) in recent
NLP tasks, their deployment poses substantial challenges due to high
computational and memory demands. Recent research has concentrated on improving
open-source ... | Computational Linguistics |
What field is the article from? | Title: ACTOR: Active Learning with Annotator-specific Classification Heads to Embrace Human Label Variation
Abstract: Label aggregation such as majority voting is commonly used to resolve
annotator disagreement in dataset creation. However, this may disregard
minority values and opinions. Recent studies indicate that l... | Computational Linguistics |
What field is the article from? | Title: Decomposing Hard SAT Instances with Metaheuristic Optimization
Abstract: In the article, within the framework of the Boolean Satisfiability problem
(SAT), the problem of estimating the hardness of specific Boolean formulas
w.r.t. a specific complete SAT solving algorithm is considered. Based on the
well-known St... | Artificial Intelligence |
What field is the article from? | Title: Dates Fruit Disease Recognition using Machine Learning
Abstract: Many countries such as Saudi Arabia, Morocco and Tunisia are among the top
exporters and consumers of palm date fruits. Date fruit production plays a
major role in the economies of the date fruit exporting countries. Date fruits
are susceptible to ... | Computer Vision |
What field is the article from? | Title: Language Model Agents Suffer from Compositional Generalization in Web Automation
Abstract: Language model agents (LMA) recently emerged as a promising paradigm on
muti-step decision making tasks, often outperforming humans and other
reinforcement learning agents. Despite the promise, their performance on
real-wo... | Machine Learning |
What field is the article from? | Title: The Linear Representation Hypothesis and the Geometry of Large Language Models
Abstract: Informally, the 'linear representation hypothesis' is the idea that
high-level concepts are represented linearly as directions in some
representation space. In this paper, we address two closely related questions:
What does ... | Computational Linguistics |
What field is the article from? | Title: UWB Based Static Gesture Classification
Abstract: Our paper presents a robust framework for UWB-based static gesture
recognition, leveraging proprietary UWB radar sensor technology. Extensive data
collection efforts were undertaken to compile datasets containing five commonly
used gestures. Our approach involves... | Computer Vision |
What field is the article from? | Title: Bridging the Gap: Addressing Discrepancies in Diffusion Model Training for Classifier-Free Guidance
Abstract: Diffusion models have emerged as a pivotal advancement in generative models,
setting new standards to the quality of the generated instances. In the current
paper we aim to underscore a discrepancy betwe... | Machine Learning |
What field is the article from? | Title: Labeling Neural Representations with Inverse Recognition
Abstract: Deep Neural Networks (DNNs) demonstrated remarkable capabilities in learning
complex hierarchical data representations, but the nature of these
representations remains largely unknown. Existing global explainability
methods, such as Network Disse... | Machine Learning |
What field is the article from? | Title: Chatbots Are Not Reliable Text Annotators
Abstract: Recent research highlights the significant potential of ChatGPT for text
annotation in social science research. However, ChatGPT is a closed-source
product which has major drawbacks with regards to transparency,
reproducibility, cost, and data protection. Recen... | Computational Linguistics |
What field is the article from? | Title: Diffused Task-Agnostic Milestone Planner
Abstract: Addressing decision-making problems using sequence modeling to predict future
trajectories shows promising results in recent years. In this paper, we take a
step further to leverage the sequence predictive method in wider areas such as
long-term planning, vision... | Robotics |
What field is the article from? | Title: Smart Home Goal Feature Model -- A guide to support Smart Homes for Ageing in Place
Abstract: Smart technologies are significant in supporting ageing in place for elderly.
Leveraging Artificial Intelligence (AI) and Machine Learning (ML), it provides
peace of mind, enabling the elderly to continue living indepen... | Human-Computer Interaction |
What field is the article from? | Title: Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives
Abstract: We present Ego-Exo4D, a diverse, large-scale multimodal multiview video
dataset and benchmark challenge. Ego-Exo4D centers around
simultaneously-captured egocentric and exocentric video of skilled human
activities... | Computer Vision |
What field is the article from? | Title: Past as a Guide: Leveraging Retrospective Learning for Python Code Completion
Abstract: This work presents Past as a Guide (PaG), a simple approach for Large
Language Models (LLMs) to improve the coding capabilities by integrating the
past history with interactive and iterative code refinements. To be specific,
... | Software Engineering |
What field is the article from? | Title: ICRA Roboethics Challenge 2023: Intelligent Disobedience in an Elderly Care Home
Abstract: With the projected surge in the elderly population, service robots offer a
promising avenue to enhance their well-being in elderly care homes. Such robots
will encounter complex scenarios which will require them to perform... | Robotics |
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