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What field is the article from? | Title: XAI for time-series classification leveraging image highlight methods
Abstract: Although much work has been done on explainability in the computer vision and
natural language processing (NLP) fields, there is still much work to be done
to explain methods applied to time series as time series by nature can not be... | Machine Learning |
What field is the article from? | Title: Continuous 16-bit Training: Accelerating 32-bit Pre-Trained Neural Networks
Abstract: In the field of deep learning, the prevalence of models initially trained
with 32-bit precision is a testament to its robustness and accuracy. However,
the continuous evolution of these models often demands further training, wh... | Machine Learning |
What field is the article from? | Title: PartSLIP++: Enhancing Low-Shot 3D Part Segmentation via Multi-View Instance Segmentation and Maximum Likelihood Estimation
Abstract: Open-world 3D part segmentation is pivotal in diverse applications such as
robotics and AR/VR. Traditional supervised methods often grapple with limited
3D data availability and st... | Computer Vision |
What field is the article from? | Title: Robot Skill Generalization via Keypoint Integrated Soft Actor-Critic Gaussian Mixture Models
Abstract: A long-standing challenge for a robotic manipulation system operating in
real-world scenarios is adapting and generalizing its acquired motor skills to
unseen environments. We tackle this challenge employing hy... | Robotics |
What field is the article from? | Title: "Do it my way!": Impact of Customizations on Trust perceptions in Human-Robot Collaboration
Abstract: Trust has been shown to be a key factor in effective human-robot
collaboration. In the context of assistive robotics, the effect of trust
factors on human experience is further pronounced. Personalization of ass... | Robotics |
What field is the article from? | Title: Scale-Dropout: Estimating Uncertainty in Deep Neural Networks Using Stochastic Scale
Abstract: Uncertainty estimation in Neural Networks (NNs) is vital in improving
reliability and confidence in predictions, particularly in safety-critical
applications. Bayesian Neural Networks (BayNNs) with Dropout as an
approx... | Machine Learning |
What field is the article from? | Title: Honeybee: Locality-enhanced Projector for Multimodal LLM
Abstract: In Multimodal Large Language Models (MLLMs), a visual projector plays a
crucial role in bridging pre-trained vision encoders with LLMs, enabling
profound visual understanding while harnessing the LLMs' robust capabilities.
Despite the importance ... | Computer Vision |
What field is the article from? | Title: Large Language Models for Mathematicians
Abstract: Large language models (LLMs) such as ChatGPT have received immense interest
for their general-purpose language understanding and, in particular, their
ability to generate high-quality text or computer code. For many professions,
LLMs represent an invaluable tool... | Computational Linguistics |
What field is the article from? | Title: Graph Convolutional Networks for Complex Traffic Scenario Classification
Abstract: A scenario-based testing approach can reduce the time required to obtain
statistically significant evidence of the safety of Automated Driving Systems
(ADS). Identifying these scenarios in an automated manner is a challenging
task... | Computer Vision |
What field is the article from? | Title: Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves
Abstract: Misunderstandings arise not only in interpersonal communication but also
between humans and Large Language Models (LLMs). Such discrepancies can make
LLMs interpret seemingly unambiguous questions in unexpected ways, yi... | Computational Linguistics |
What field is the article from? | Title: Protecting Publicly Available Data With Machine Learning Shortcuts
Abstract: Machine-learning (ML) shortcuts or spurious correlations are artifacts in
datasets that lead to very good training and test performance but severely
limit the model's generalization capability. Such shortcuts are insidious
because they ... | Artificial Intelligence |
What field is the article from? | Title: Introducing instance label correlation in multiple instance learning. Application to cancer detection on histopathological images
Abstract: In the last years, the weakly supervised paradigm of multiple instance
learning (MIL) has become very popular in many different areas. A paradigmatic
example is computationa... | Computer Vision |
What field is the article from? | Title: Exploring Social Bias in Downstream Applications of Text-to-Image Foundation Models
Abstract: Text-to-image diffusion models have been adopted into key commercial
workflows, such as art generation and image editing. Characterising the
implicit social biases they exhibit, such as gender and racial stereotypes, is... | Computers and Society |
What field is the article from? | Title: er.autopilot 1.0: The Full Autonomous Stack for Oval Racing at High Speeds
Abstract: The Indy Autonomous Challenge (IAC) brought together for the first time in
history nine autonomous racing teams competing at unprecedented speed and in
head-to-head scenario, using independently developed software on open-wheel
... | Robotics |
What field is the article from? | Title: Alignment for Honesty
Abstract: Recent research has made significant strides in applying alignment techniques
to enhance the helpfulness and harmlessness of large language models (LLMs) in
accordance with human intentions. In this paper, we argue for the importance of
alignment for honesty, ensuring that LLMs pr... | Computational Linguistics |
What field is the article from? | Title: Reducing Spatial Fitting Error in Distillation of Denoising Diffusion Models
Abstract: Denoising Diffusion models have exhibited remarkable capabilities in image
generation. However, generating high-quality samples requires a large number of
iterations. Knowledge distillation for diffusion models is an effective... | Computer Vision |
What field is the article from? | Title: ERASER: Machine Unlearning in MLaaS via an Inference Serving-Aware Approach
Abstract: Over the past few years, Machine Learning-as-a-Service (MLaaS) has received a
surging demand for supporting Machine Learning-driven services to offer
revolutionized user experience across diverse application areas. MLaaS provid... | Cryptography and Security |
What field is the article from? | Title: CarbNN: A Novel Active Transfer Learning Neural Network To Build De Novo Metal Organic Frameworks (MOFs) for Carbon Capture
Abstract: Over the past decade, climate change has become an increasing problem with
one of the major contributing factors being carbon dioxide (CO2) emissions;
almost 51% of total US carbo... | Machine Learning |
What field is the article from? | Title: Cognitive Dissonance: Why Do Language Model Outputs Disagree with Internal Representations of Truthfulness?
Abstract: Neural language models (LMs) can be used to evaluate the truth of factual
statements in two ways: they can be either queried for statement probabilities,
or probed for internal representations of... | Computational Linguistics |
What field is the article from? | Title: Debiasing, calibrating, and improving Semi-supervised Learning performance via simple Ensemble Projector
Abstract: Recent studies on semi-supervised learning (SSL) have achieved great success.
Despite their promising performance, current state-of-the-art methods tend
toward increasingly complex designs at the co... | Computer Vision |
What field is the article from? | Title: Meta learning with language models: Challenges and opportunities in the classification of imbalanced text
Abstract: Detecting out of policy speech (OOPS) content is important but difficult.
While machine learning is a powerful tool to tackle this challenging task, it
is hard to break the performance ceiling due ... | Machine Learning |
What field is the article from? | Title: Saturn: Efficient Multi-Large-Model Deep Learning
Abstract: In this paper, we propose Saturn, a new data system to improve the efficiency
of multi-large-model training (e.g., during model selection/hyperparameter
optimization). We first identify three key interconnected systems challenges
for users building larg... | Machine Learning |
What field is the article from? | Title: Hessian Aware Low-Rank Weight Perturbation for Continual Learning
Abstract: Continual learning aims to learn a series of tasks sequentially without
forgetting the knowledge acquired from the previous ones. In this work, we
propose the Hessian Aware Low-Rank Perturbation algorithm for continual
learning. By model... | Machine Learning |
What field is the article from? | Title: Content-based Controls For Music Large Language Modeling
Abstract: Recent years have witnessed a rapid growth of large-scale language models in
the domain of music audio. Such models enable end-to-end generation of
higher-quality music, and some allow conditioned generation using text
descriptions. However, the ... | Artificial Intelligence |
What field is the article from? | Title: Data-driven project planning: An integrated network learning and constraint relaxation approach in favor of scheduling
Abstract: Our focus is on projects, i.e., business processes, which are emerging as the
economic drivers of our times. Differently from day-to-day operational
processes that do not require detai... | Artificial Intelligence |
What field is the article from? | Title: Offline Imitation from Observation via Primal Wasserstein State Occupancy Matching
Abstract: In real-world scenarios, arbitrary interactions with the environment can
often be costly, and actions of expert demonstrations are not always available.
To reduce the need for both, Offline Learning from Observations (Lf... | Machine Learning |
What field is the article from? | Title: MultiModal-Learning for Predicting Molecular Properties: A Framework Based on Image and Graph Structures
Abstract: The quest for accurate prediction of drug molecule properties poses a
fundamental challenge in the realm of Artificial Intelligence Drug Discovery
(AIDD). An effective representation of drug molecul... | Machine Learning |
What field is the article from? | Title: Semi-automatic Data Enhancement for Document-Level Relation Extraction with Distant Supervision from Large Language Models
Abstract: Document-level Relation Extraction (DocRE), which aims to extract relations
from a long context, is a critical challenge in achieving fine-grained
structural comprehension and gene... | Computational Linguistics |
What field is the article from? | Title: Stellar: Systematic Evaluation of Human-Centric Personalized Text-to-Image Methods
Abstract: In this work, we systematically study the problem of personalized
text-to-image generation, where the output image is expected to portray
information about specific human subjects. E.g., generating images of oneself
appe... | Computer Vision |
What field is the article from? | Title: Temporal Shift -- Multi-Objective Loss Function for Improved Anomaly Fall Detection
Abstract: Falls are a major cause of injuries and deaths among older adults worldwide.
Accurate fall detection can help reduce potential injuries and additional
health complications. Different types of video modalities can be use... | Computer Vision |
What field is the article from? | Title: Minimax Exploiter: A Data Efficient Approach for Competitive Self-Play
Abstract: Recent advances in Competitive Self-Play (CSP) have achieved, or even
surpassed, human level performance in complex game environments such as Dota 2
and StarCraft II using Distributed Multi-Agent Reinforcement Learning (MARL).
One c... | Machine Learning |
What field is the article from? | Title: Automated Material Properties Extraction For Enhanced Beauty Product Discovery and Makeup Virtual Try-on
Abstract: The multitude of makeup products available can make it challenging to find
the ideal match for desired attributes. An intelligent approach for product
discovery is required to enhance the makeup sho... | Computer Vision |
What field is the article from? | Title: Investigating Data Contamination in Modern Benchmarks for Large Language Models
Abstract: Recent observations have underscored a disparity between the inflated
benchmark scores and the actual performance of LLMs, raising concerns about
potential contamination of evaluation benchmarks. This issue is especially
cr... | Computational Linguistics |
What field is the article from? | Title: Modular Neural Networks for Time Series Forecasting: Interpretability and Feature Selection using Attention
Abstract: Multivariate time series have many applications, from healthcare and
meteorology to life science. Although deep learning models have shown excellent
predictive performance for time series, they h... | Machine Learning |
What field is the article from? | Title: Autonomous Port Navigation With Ranging Sensors Using Model-Based Reinforcement Learning
Abstract: Autonomous shipping has recently gained much interest in the research
community. However, little research focuses on inland - and port navigation,
even though this is identified by countries such as Belgium and the... | Robotics |
What field is the article from? | Title: Salespeople vs SalesBot: Exploring the Role of Educational Value in Conversational Recommender Systems
Abstract: Making big purchases requires consumers to research or consult a salesperson
to gain domain expertise. However, existing conversational recommender systems
(CRS) often overlook users' lack of backgrou... | Computational Linguistics |
What field is the article from? | Title: Look-Ahead Selective Plasticity for Continual Learning of Visual Tasks
Abstract: Contrastive representation learning has emerged as a promising technique for
continual learning as it can learn representations that are robust to
catastrophic forgetting and generalize well to unseen future tasks. Previous
work in ... | Computer Vision |
What field is the article from? | Title: Towards Efficient 3D Object Detection in Bird's-Eye-View Space for Autonomous Driving: A Convolutional-Only Approach
Abstract: 3D object detection in Bird's-Eye-View (BEV) space has recently emerged as a
prevalent approach in the field of autonomous driving. Despite the demonstrated
improvements in accuracy and ... | Computer Vision |
What field is the article from? | Title: Can ChatGPT advance software testing intelligence? An experience report on metamorphic testing
Abstract: While ChatGPT is a well-known artificial intelligence chatbot being used to
answer human's questions, one may want to discover its potential in advancing
software testing. We examine the capability of ChatGPT... | Software Engineering |
What field is the article from? | Title: An Interactive Query Generation Assistant using LLM-based Prompt Modification and User Feedback
Abstract: While search is the predominant method of accessing information, formulating
effective queries remains a challenging task, especially for situations where
the users are not familiar with a domain, or searchi... | Artificial Intelligence |
What field is the article from? | Title: SAT-Based Algorithms for Regular Graph Pattern Matching
Abstract: Graph matching is a fundamental problem in pattern recognition, with many
applications such as software analysis and computational biology. One
well-known type of graph matching problem is graph isomorphism, which consists
of deciding if two graph... | Artificial Intelligence |
What field is the article from? | Title: LlamaRec: Two-Stage Recommendation using Large Language Models for Ranking
Abstract: Recently, large language models (LLMs) have exhibited significant progress in
language understanding and generation. By leveraging textual features,
customized LLMs are also applied for recommendation and demonstrate
improvement... | Information Retrieval |
What field is the article from? | Title: TSegFormer: 3D Tooth Segmentation in Intraoral Scans with Geometry Guided Transformer
Abstract: Optical Intraoral Scanners (IOS) are widely used in digital dentistry to
provide detailed 3D information of dental crowns and the gingiva. Accurate 3D
tooth segmentation in IOSs is critical for various dental applicat... | Computer Vision |
What field is the article from? | Title: VITATECS: A Diagnostic Dataset for Temporal Concept Understanding of Video-Language Models
Abstract: The ability to perceive how objects change over time is a crucial ingredient
in human intelligence. However, current benchmarks cannot faithfully reflect
the temporal understanding abilities of video-language mod... | Computer Vision |
What field is the article from? | Title: Minimizing Factual Inconsistency and Hallucination in Large Language Models
Abstract: Large Language Models (LLMs) are widely used in critical fields such as
healthcare, education, and finance due to their remarkable proficiency in
various language-related tasks. However, LLMs are prone to generating factually
i... | Computational Linguistics |
What field is the article from? | Title: TaCo: Enhancing Cross-Lingual Transfer for Low-Resource Languages in LLMs through Translation-Assisted Chain-of-Thought Processes
Abstract: LLMs such as ChatGPT and PaLM can be utilized to train on a new language and
revitalize low-resource languages. However, it is evidently very costly to
pretrain pr fine-tune... | Computational Linguistics |
What field is the article from? | Title: Navigating the generative AI era: Introducing the AI assessment scale for ethical GenAI assessment
Abstract: Recent developments in Generative Artificial Intelligence (GenAI) have
created a paradigm shift in multiple areas of society, and the use of these
technologies is likely to become a defining feature of ed... | Artificial Intelligence |
What field is the article from? | Title: Gaussian Grouping: Segment and Edit Anything in 3D Scenes
Abstract: The recent Gaussian Splatting achieves high-quality and real-time novel-view
synthesis of the 3D scenes. However, it is solely concentrated on the
appearance and geometry modeling, while lacking in fine-grained object-level
scene understanding. ... | Computer Vision |
What field is the article from? | Title: TempTabQA: Temporal Question Answering for Semi-Structured Tables
Abstract: Semi-structured data, such as Infobox tables, often include temporal
information about entities, either implicitly or explicitly. Can current NLP
systems reason about such information in semi-structured tables? To tackle this
question, w... | Computational Linguistics |
What field is the article from? | Title: The Significance of Machine Learning in Clinical Disease Diagnosis: A Review
Abstract: The global need for effective disease diagnosis remains substantial, given
the complexities of various disease mechanisms and diverse patient symptoms. To
tackle these challenges, researchers, physicians, and patients are turn... | Machine Learning |
What field is the article from? | Title: Get the Ball Rolling: Alerting Autonomous Robots When to Help to Close the Healthcare Loop
Abstract: To facilitate the advancement of research in healthcare robots without human
intervention or commands, we introduce the Autonomous Helping Challenge, along
with a crowd-sourcing large-scale dataset. The goal is t... | Robotics |
What field is the article from? | Title: EMDM: Efficient Motion Diffusion Model for Fast, High-Quality Motion Generation
Abstract: We introduce Efficient Motion Diffusion Model (EMDM) for fast and
high-quality human motion generation. Although previous motion diffusion models
have shown impressive results, they struggle to achieve fast generation while... | Computer Vision |
What field is the article from? | Title: Dance of Channel and Sequence: An Efficient Attention-Based Approach for Multivariate Time Series Forecasting
Abstract: In recent developments, predictive models for multivariate time series
analysis have exhibited commendable performance through the adoption of the
prevalent principle of channel independence. N... | Machine Learning |
What field is the article from? | Title: Auto MC-Reward: Automated Dense Reward Design with Large Language Models for Minecraft
Abstract: Traditional reinforcement-learning-based agents rely on sparse rewards that
often only use binary values to indicate task completion or failure. The
challenge in exploration efficiency makes it difficult to effective... | Artificial Intelligence |
What field is the article from? | Title: Data Factors for Better Compositional Generalization
Abstract: Recent diagnostic datasets on compositional generalization, such as SCAN
(Lake and Baroni, 2018) and COGS (Kim and Linzen, 2020), expose severe problems
in models trained from scratch on these datasets. However, in contrast to this
poor performance, ... | Computational Linguistics |
What field is the article from? | Title: Efficient Representation of the Activation Space in Deep Neural Networks
Abstract: The representations of the activation space of deep neural networks (DNNs)
are widely utilized for tasks like natural language processing, anomaly
detection and speech recognition. Due to the diverse nature of these tasks and
the ... | Machine Learning |
What field is the article from? | Title: Few-shot Hybrid Domain Adaptation of Image Generators
Abstract: Can a pre-trained generator be adapted to the hybrid of multiple target
domains and generate images with integrated attributes of them? In this work,
we introduce a new task -- Few-shot Hybrid Domain Adaptation (HDA). Given a
source generator and se... | Computer Vision |
What field is the article from? | Title: USat: A Unified Self-Supervised Encoder for Multi-Sensor Satellite Imagery
Abstract: Large, self-supervised vision models have led to substantial advancements for
automatically interpreting natural images. Recent works have begun tailoring
these methods to remote sensing data which has rich structure with
multi-... | Computer Vision |
What field is the article from? | Title: TriDeNT: Triple Deep Network Training for Privileged Knowledge Distillation in Histopathology
Abstract: Computational pathology models rarely utilise data that will not be available
for inference. This means most models cannot learn from highly informative data
such as additional immunohistochemical (IHC) stains... | Computer Vision |
What field is the article from? | Title: Cross-domain feature disentanglement for interpretable modeling of tumor microenvironment impact on drug response
Abstract: High-throughput screening technology has facilitated the generation of
large-scale drug responses across hundreds of cancer cell lines. However, there
exists significant discrepancy between... | Machine Learning |
What field is the article from? | Title: Assessing Prompt Injection Risks in 200+ Custom GPTs
Abstract: In the rapidly evolving landscape of artificial intelligence, ChatGPT has
been widely used in various applications. The new feature: customization of
ChatGPT models by users to cater to specific needs has opened new frontiers in
AI utility. However, ... | Cryptography and Security |
What field is the article from? | Title: Large Language Models: The Need for Nuance in Current Debates and a Pragmatic Perspective on Understanding
Abstract: Current Large Language Models (LLMs) are unparalleled in their ability to
generate grammatically correct, fluent text. LLMs are appearing rapidly, and
debates on LLM capacities have taken off, but... | Computational Linguistics |
What field is the article from? | Title: ReCoRe: Regularized Contrastive Representation Learning of World Model
Abstract: While recent model-free Reinforcement Learning (RL) methods have demonstrated
human-level effectiveness in gaming environments, their success in everyday
tasks like visual navigation has been limited, particularly under significant
... | Machine Learning |
What field is the article from? | Title: Preserving the knowledge of long clinical texts using aggregated ensembles of large language models
Abstract: Clinical texts, such as admission notes, discharge summaries, and progress
notes, contain rich and valuable information that can be used for various
clinical outcome prediction tasks. However, applying l... | Computational Linguistics |
What field is the article from? | Title: AI for All: Operationalising Diversity and Inclusion Requirements for AI Systems
Abstract: As Artificial Intelligence (AI) permeates many aspects of society, it brings
numerous advantages while at the same time raising ethical concerns and
potential risks, such as perpetuating inequalities through biased or
disc... | Computers and Society |
What field is the article from? | Title: A Critical Perceptual Pre-trained Model for Complex Trajectory Recovery
Abstract: The trajectory on the road traffic is commonly collected at a low sampling
rate, and trajectory recovery aims to recover a complete and continuous
trajectory from the sparse and discrete inputs. Recently, sequential language
models... | Machine Learning |
What field is the article from? | Title: Impact of Tokenization on LLaMa Russian Adaptation
Abstract: Latest instruction-tuned large language models (LLM) show great results on
various tasks, however, they often face performance degradation for non-English
input. There is evidence that the reason lies in inefficient tokenization
caused by low language ... | Computational Linguistics |
What field is the article from? | Title: COSMIC: Data Efficient Instruction-tuning For Speech In-Context Learning
Abstract: We present a data and cost efficient way of incorporating the speech modality
into a large language model (LLM). The resulting multi-modal LLM is a
COntextual Speech Model with Instruction-following/in-context-learning
Capabilitie... | Computational Linguistics |
What field is the article from? | Title: PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding
Abstract: Recent advances in text-to-image generation have made remarkable progress in
synthesizing realistic human photos conditioned on given text prompts. However,
existing personalized generation methods cannot simultaneously satisfy the... | Computer Vision |
What field is the article from? | Title: ToolTalk: Evaluating Tool-Usage in a Conversational Setting
Abstract: Large language models (LLMs) have displayed massive improvements in reasoning
and decision-making skills and can hold natural conversations with users. Many
recent works seek to augment LLM-based assistants with external tools so they
can acce... | Computational Linguistics |
What field is the article from? | Title: CycleAlign: Iterative Distillation from Black-box LLM to White-box Models for Better Human Alignment
Abstract: Language models trained on large-scale corpus often generate content that is
harmful, toxic, or contrary to human preferences, making their alignment with
human values a critical concern. Reinforcement ... | Computational Linguistics |
What field is the article from? | Title: Prediction of Locally Stationary Data Using Expert Advice
Abstract: The problem of continuous machine learning is studied. Within the framework
of the game-theoretic approach, when for calculating the next forecast, no
assumptions about the stochastic nature of the source that generates the data
flow are used --... | Machine Learning |
What field is the article from? | Title: Knowledge-Augmented Large Language Models for Personalized Contextual Query Suggestion
Abstract: Large Language Models (LLMs) excel at tackling various natural language
tasks. However, due to the significant costs involved in re-training or
fine-tuning them, they remain largely static and difficult to personaliz... | Information Retrieval |
What field is the article from? | Title: A Transformer-Based Model With Self-Distillation for Multimodal Emotion Recognition in Conversations
Abstract: Emotion recognition in conversations (ERC), the task of recognizing the
emotion of each utterance in a conversation, is crucial for building empathetic
machines. Existing studies focus mainly on capturi... | Artificial Intelligence |
What field is the article from? | Title: Distributional Latent Variable Models with an Application in Active Cognitive Testing
Abstract: Cognitive modeling commonly relies on asking participants to complete a
battery of varied tests in order to estimate attention, working memory, and
other latent variables. In many cases, these tests result in highly v... | Artificial Intelligence |
What field is the article from? | Title: GPT-4 Surpassing Human Performance in Linguistic Pragmatics
Abstract: As Large Language Models (LLMs) become increasingly integrated into everyday
life, their capabilities to understand and emulate human cognition are under
steady examination. This study investigates the ability of LLMs to comprehend
and interpr... | Computational Linguistics |
What field is the article from? | Title: Prompt Optimisation with Random Sampling
Abstract: Using the generative nature of a language model to generate task-relevant
separators has shown competitive results compared to human-curated prompts like
"TL;DR". We demonstrate that even randomly chosen tokens from the vocabulary as
separators can achieve near-... | Computational Linguistics |
What field is the article from? | Title: Exploring Parity Challenges in Reinforcement Learning through Curriculum Learning with Noisy Labels
Abstract: This paper delves into applying reinforcement learning (RL) in strategy
games, particularly those characterized by parity challenges, as seen in
specific positions of Go and Chess and a broader range of ... | Artificial Intelligence |
What field is the article from? | Title: minimax: Efficient Baselines for Autocurricula in JAX
Abstract: Unsupervised environment design (UED) is a form of automatic curriculum
learning for training robust decision-making agents to zero-shot transfer into
unseen environments. Such autocurricula have received much interest from the RL
community. However... | Machine Learning |
What field is the article from? | Title: Responsible AI Research Needs Impact Statements Too
Abstract: All types of research, development, and policy work can have unintended,
adverse consequences - work in responsible artificial intelligence (RAI),
ethical AI, or ethics in AI is no exception. | Artificial Intelligence |
What field is the article from? | Title: Infinite forecast combinations based on Dirichlet process
Abstract: Forecast combination integrates information from various sources by
consolidating multiple forecast results from the target time series. Instead of
the need to select a single optimal forecasting model, this paper introduces a
deep learning ense... | Machine Learning |
What field is the article from? | Title: I Was Blind but Now I See: Implementing Vision-Enabled Dialogue in Social Robots
Abstract: In the rapidly evolving landscape of human-computer interaction, the
integration of vision capabilities into conversational agents stands as a
crucial advancement. This paper presents an initial implementation of a
dialogu... | Robotics |
What field is the article from? | Title: Using Curiosity for an Even Representation of Tasks in Continual Offline Reinforcement Learning
Abstract: In this work, we investigate the means of using curiosity on replay buffers
to improve offline multi-task continual reinforcement learning when tasks,
which are defined by the non-stationarity in the environ... | Machine Learning |
What field is the article from? | Title: FFINet: Future Feedback Interaction Network for Motion Forecasting
Abstract: Motion forecasting plays a crucial role in autonomous driving, with the aim
of predicting the future reasonable motions of traffic agents. Most existing
methods mainly model the historical interactions between agents and the
environment... | Computer Vision |
What field is the article from? | Title: Do large language models and humans have similar behaviors in causal inference with script knowledge?
Abstract: Recently, large pre-trained language models (LLMs) have demonstrated superior
language understanding abilities, including zero-shot causal reasoning.
However, it is unclear to what extent their capabil... | Computational Linguistics |
What field is the article from? | Title: Language-Guided Transformer for Federated Multi-Label Classification
Abstract: Federated Learning (FL) is an emerging paradigm that enables multiple users
to collaboratively train a robust model in a privacy-preserving manner without
sharing their private data. Most existing approaches of FL only consider
tradit... | Computer Vision |
What field is the article from? | Title: Optimizing Fault-Tolerant Quality-Guaranteed Sensor Deployments for UAV Localization in Critical Areas via Computational Geometry
Abstract: The increasing spreading of small commercial Unmanned Aerial Vehicles (UAVs,
aka drones) presents serious threats for critical areas such as airports, power
plants, governme... | Robotics |
What field is the article from? | Title: Learning county from pixels: Corn yield prediction with attention-weighted multiple instance learning
Abstract: Remote sensing technology has become a promising tool in yield prediction.
Most prior work employs satellite imagery for county-level corn yield
prediction by spatially aggregating all pixels within a ... | Computer Vision |
What field is the article from? | Title: Training Robust Deep Physiological Measurement Models with Synthetic Video-based Data
Abstract: Recent advances in supervised deep learning techniques have demonstrated the
possibility to remotely measure human physiological vital signs (e.g.,
photoplethysmograph, heart rate) just from facial videos. However, th... | Computer Vision |
What field is the article from? | Title: Uncovering communities of pipelines in the task-fMRI analytical space
Abstract: Functional magnetic resonance imaging analytical workflows are highly
flexible with no definite consensus on how to choose a pipeline. While methods
have been developed to explore this analytical space, there is still a lack of
under... | Artificial Intelligence |
What field is the article from? | Title: Generating Interpretable Networks using Hypernetworks
Abstract: An essential goal in mechanistic interpretability to decode a network, i.e.,
to convert a neural network's raw weights to an interpretable algorithm. Given
the difficulty of the decoding problem, progress has been made to understand
the easier encod... | Machine Learning |
What field is the article from? | Title: Interactive Autonomous Navigation with Internal State Inference and Interactivity Estimation
Abstract: Deep reinforcement learning (DRL) provides a promising way for intelligent
agents (e.g., autonomous vehicles) to learn to navigate complex scenarios.
However, DRL with neural networks as function approximators ... | Robotics |
What field is the article from? | Title: AI-TA: Towards an Intelligent Question-Answer Teaching Assistant using Open-Source LLMs
Abstract: Responding to the thousands of student questions on online QA platforms each
semester has a considerable human cost, particularly in computing courses with
rapidly growing enrollments. To address the challenges of s... | Machine Learning |
What field is the article from? | Title: Bergeron: Combating Adversarial Attacks through a Conscience-Based Alignment Framework
Abstract: Modern Large language models (LLMs) can still generate responses that may not
be aligned with human expectations or values. While many weight-based alignment
methods have been proposed, many of them still leave model... | Cryptography and Security |
What field is the article from? | Title: Towards Generalized Multi-stage Clustering: Multi-view Self-distillation
Abstract: Existing multi-stage clustering methods independently learn the salient
features from multiple views and then perform the clustering task.
Particularly, multi-view clustering (MVC) has attracted a lot of attention in
multi-view or... | Computer Vision |
What field is the article from? | Title: Transformer as Linear Expansion of Learngene
Abstract: We propose expanding the shared Transformer module to produce and initialize
Transformers with diverse depths, enabling adaptation to dynamic resource
constraints. Drawing an analogy to genetic expansibility, we term such module
as learngene. To identify the... | Artificial Intelligence |
What field is the article from? | Title: Class-Incremental Continual Learning for General Purpose Healthcare Models
Abstract: Healthcare clinics regularly encounter dynamic data that changes due to
variations in patient populations, treatment policies, medical devices, and
emerging disease patterns. Deep learning models can suffer from catastrophic
for... | Machine Learning |
What field is the article from? | Title: Divide-and-Conquer Strategy for Large-Scale Dynamic Bayesian Network Structure Learning
Abstract: Dynamic Bayesian Networks (DBNs), renowned for their interpretability, have
become increasingly vital in representing complex stochastic processes in
various domains such as gene expression analysis, healthcare, and... | Machine Learning |
What field is the article from? | Title: A Framework for Realistic Simulation of Daily Human Activity
Abstract: For social robots like Astro which interact with and adapt to the daily
movements of users within the home, realistic simulation of human activity is
needed for feature development and testing. This paper presents a framework for
simulating d... | Robotics |
What field is the article from? | Title: Stable Diffusion Reference Only: Image Prompt and Blueprint Jointly Guided Multi-Condition Diffusion Model for Secondary Painting
Abstract: Stable Diffusion and ControlNet have achieved excellent results in the field
of image generation and synthesis. However, due to the granularity and method
of its control, th... | Computer Vision |
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