instruction stringclasses 1
value | input stringlengths 260 2.07k | output stringclasses 10
values |
|---|---|---|
What field is the article from? | Title: Prototypical Self-Explainable Models Without Re-training
Abstract: Explainable AI (XAI) has unfolded in two distinct research directions with,
on the one hand, post-hoc methods that explain the predictions of a pre-trained
black-box model and, on the other hand, self-explainable models (SEMs) which
are trained d... | Machine Learning |
What field is the article from? | Title: UniIR: Training and Benchmarking Universal Multimodal Information Retrievers
Abstract: Existing information retrieval (IR) models often assume a homogeneous format,
limiting their applicability to diverse user needs, such as searching for
images with text descriptions, searching for a news article with a headlin... | Computer Vision |
What field is the article from? | Title: Model-Based Minimum Bayes Risk Decoding
Abstract: Minimum Bayes Risk (MBR) decoding has been shown to be a powerful alternative
to beam search decoding in a variety of text generation tasks. MBR decoding
selects a hypothesis from a pool of hypotheses that has the least expected risk
under a probability model acc... | Artificial Intelligence |
What field is the article from? | Title: Large Human Language Models: A Need and the Challenges
Abstract: As research in human-centered NLP advances, there is a growing recognition of
the importance of incorporating human and social factors into NLP models. At
the same time, our NLP systems have become heavily reliant on LLMs, most of
which do not mode... | Computational Linguistics |
What field is the article from? | Title: THOS: A Benchmark Dataset for Targeted Hate and Offensive Speech
Abstract: Detecting harmful content on social media, such as Twitter, is made difficult
by the fact that the seemingly simple yes/no classification conceals a
significant amount of complexity. Unfortunately, while several datasets have
been collect... | Computational Linguistics |
What field is the article from? | Title: Computational Hypergraph Discovery, a Gaussian Process framework for connecting the dots
Abstract: Most scientific challenges can be framed into one of the following three
levels of complexity of function approximation. Type 1: Approximate an unknown
function given input/output data. Type 2: Consider a collectio... | Machine Learning |
What field is the article from? | Title: A Unifying Tensor View for Lightweight CNNs
Abstract: Despite the decomposition of convolutional kernels for lightweight CNNs being
well studied, existing works that rely on tensor network diagrams or
hyperdimensional abstraction lack geometry intuition. This work devises a new
perspective by linking a 3D-reshap... | Computer Vision |
What field is the article from? | Title: Towards Unsupervised Representation Learning: Learning, Evaluating and Transferring Visual Representations
Abstract: Unsupervised representation learning aims at finding methods that learn
representations from data without annotation-based signals. Abstaining from
annotations not only leads to economic benefits ... | Computer Vision |
What field is the article from? | Title: Augmenting Unsupervised Reinforcement Learning with Self-Reference
Abstract: Humans possess the ability to draw on past experiences explicitly when
learning new tasks and applying them accordingly. We believe this capacity for
self-referencing is especially advantageous for reinforcement learning agents
in the u... | Machine Learning |
What field is the article from? | Title: Text-to-3D with Classifier Score Distillation
Abstract: Text-to-3D generation has made remarkable progress recently, particularly
with methods based on Score Distillation Sampling (SDS) that leverages
pre-trained 2D diffusion models. While the usage of classifier-free guidance is
well acknowledged to be crucial ... | Computer Vision |
What field is the article from? | Title: ROME: Evaluating Pre-trained Vision-Language Models on Reasoning beyond Visual Common Sense
Abstract: Humans possess a strong capability for reasoning beyond common sense. For
example, given an unconventional image of a goldfish laying on the table next
to an empty fishbowl, a human would effortlessly determine ... | Computational Linguistics |
What field is the article from? | Title: Experimental Insights Towards Explainable and Interpretable Pedestrian Crossing Prediction
Abstract: In the context of autonomous driving, pedestrian crossing prediction is a key
component for improving road safety. Presently, the focus of these predictions
extends beyond achieving trustworthy results; it is shi... | Machine Learning |
What field is the article from? | Title: A Multi-solution Study on GDPR AI-enabled Completeness Checking of DPAs
Abstract: Specifying legal requirements for software systems to ensure their compliance
with the applicable regulations is a major concern to requirements engineering
(RE). Personal data which is collected by an organization is often shared ... | Software Engineering |
What field is the article from? | Title: The Data Provenance Initiative: A Large Scale Audit of Dataset Licensing & Attribution in AI
Abstract: The race to train language models on vast, diverse, and inconsistently
documented datasets has raised pressing concerns about the legal and ethical
risks for practitioners. To remedy these practices threatening... | Computational Linguistics |
What field is the article from? | Title: Video Dynamics Prior: An Internal Learning Approach for Robust Video Enhancements
Abstract: In this paper, we present a novel robust framework for low-level vision
tasks, including denoising, object removal, frame interpolation, and
super-resolution, that does not require any external training data corpus. Our
p... | Computer Vision |
What field is the article from? | Title: FreeFlow: A Comprehensive Understanding on Diffusion Probabilistic Models via Optimal Transport
Abstract: The blooming diffusion probabilistic models (DPMs) have garnered significant
interest due to their impressive performance and the elegant inspiration they
draw from physics. While earlier DPMs relied upon th... | Artificial Intelligence |
What field is the article from? | Title: KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval
Abstract: We study the ability of state-of-the art models to answer constraint
satisfaction queries for information retrieval (e.g., 'a list of ice cream
shops in San Diego'). In the past, such queries were considered to be tasks
that co... | Machine Learning |
What field is the article from? | Title: Label Propagation for Graph Label Noise
Abstract: Label noise is a common challenge in large datasets, as it can significantly
degrade the generalization ability of deep neural networks. Most existing
studies focus on noisy labels in computer vision; however, graph models
encompass both node features and graph t... | Machine Learning |
What field is the article from? | Title: What's Left? Concept Grounding with Logic-Enhanced Foundation Models
Abstract: Recent works such as VisProg and ViperGPT have smartly composed foundation
models for visual reasoning-using large language models (LLMs) to produce
programs that can be executed by pre-trained vision-language models. However,
they op... | Computer Vision |
What field is the article from? | Title: Linear Representations of Sentiment in Large Language Models
Abstract: Sentiment is a pervasive feature in natural language text, yet it is an open
question how sentiment is represented within Large Language Models (LLMs). In
this study, we reveal that across a range of models, sentiment is represented
linearly:... | Machine Learning |
What field is the article from? | Title: How Well Does GPT-4V(ision) Adapt to Distribution Shifts? A Preliminary Investigation
Abstract: In machine learning, generalization against distribution shifts -- where
deployment conditions diverge from the training scenarios -- is crucial,
particularly in fields like climate modeling, biomedicine, and autonomo... | Machine Learning |
What field is the article from? | Title: Mitigating Exposure Bias in Discriminator Guided Diffusion Models
Abstract: Diffusion Models have demonstrated remarkable performance in image
generation. However, their demanding computational requirements for training
have prompted ongoing efforts to enhance the quality of generated images
through modification... | Computer Vision |
What field is the article from? | Title: STADEE: STAtistics-based DEEp Detection of Machine Generated Text
Abstract: We present STADEE, a \textbf{STA}tistics-based \textbf{DEE}p detection method
to identify machine-generated text, addressing the limitations of current
methods that rely heavily on fine-tuning pre-trained language models (PLMs).
STADEE i... | Computational Linguistics |
What field is the article from? | Title: MobileSAMv2: Faster Segment Anything to Everything
Abstract: Segment anything model (SAM) addresses two practical yet challenging
segmentation tasks: \textbf{segment anything (SegAny)}, which utilizes a
certain point to predict the mask for a single object of interest, and
\textbf{segment everything (SegEvery)},... | Computer Vision |
What field is the article from? | Title: SegGen: Supercharging Segmentation Models with Text2Mask and Mask2Img Synthesis
Abstract: We propose SegGen, a highly-effective training data generation method for
image segmentation, which pushes the performance limits of state-of-the-art
segmentation models to a significant extent. SegGen designs and integrate... | Computer Vision |
What field is the article from? | Title: A recurrent connectionist model of melody perception : An exploration using TRACX2
Abstract: Are similar, or even identical, mechanisms used in the computational modeling
of speech segmentation, serial image processing and music processing? We
address this question by exploring how TRACX2, (French et al., 2011; ... | Artificial Intelligence |
What field is the article from? | Title: Outliers with Opposing Signals Have an Outsized Effect on Neural Network Optimization
Abstract: We identify a new phenomenon in neural network optimization which arises from
the interaction of depth and a particular heavy-tailed structure in natural
data. Our result offers intuitive explanations for several prev... | Machine Learning |
What field is the article from? | Title: The ICL Consistency Test
Abstract: Just like the previous generation of task-tuned models, large language models
(LLMs) that are adapted to tasks via prompt-based methods like
in-context-learning (ICL) perform well in some setups but not in others. This
lack of consistency in prompt-based learning hints at a lac... | Computational Linguistics |
What field is the article from? | Title: Enabling Human-Centered AI: A Methodological Perspective
Abstract: Human-centered AI (HCAI) is a design philosophy that advocates prioritizing
humans in designing, developing, and deploying intelligent systems, aiming to
maximize the benefits of AI to humans and avoid potential adverse impacts.
While HCAI contin... | Artificial Intelligence |
What field is the article from? | Title: Generalisable Agents for Neural Network Optimisation
Abstract: Optimising deep neural networks is a challenging task due to complex training
dynamics, high computational requirements, and long training times. To address
this difficulty, we propose the framework of Generalisable Agents for Neural
Network Optimisa... | Machine Learning |
What field is the article from? | Title: Utilizing Multiple Inputs Autoregressive Models for Bearing Remaining Useful Life Prediction
Abstract: Accurate prediction of the Remaining Useful Life (RUL) of rolling bearings is
crucial in industrial production, yet existing models often struggle with
limited generalization capabilities due to their inability... | Machine Learning |
What field is the article from? | Title: A Language Agent for Autonomous Driving
Abstract: Human-level driving is an ultimate goal of autonomous driving. Conventional
approaches formulate autonomous driving as a perception-prediction-planning
framework, yet their systems do not capitalize on the inherent reasoning
ability and experiential knowledge of ... | Computer Vision |
What field is the article from? | Title: IDENAS: Internal Dependency Exploration for Neural Architecture Search
Abstract: Machine learning is a powerful tool for extracting valuable information and
making various predictions from diverse datasets. Traditional algorithms rely
on well-defined input and output variables however, there are scenarios where
... | Machine Learning |
What field is the article from? | Title: Tackling Bias in Pre-trained Language Models: Current Trends and Under-represented Societies
Abstract: The benefits and capabilities of pre-trained language models (LLMs) in
current and future innovations are vital to any society. However, introducing
and using LLMs comes with biases and discrimination, resultin... | Computers and Society |
What field is the article from? | Title: Intrinsic Image Decomposition via Ordinal Shading
Abstract: Intrinsic decomposition is a fundamental mid-level vision problem that plays
a crucial role in various inverse rendering and computational photography
pipelines. Generating highly accurate intrinsic decompositions is an inherently
under-constrained task... | Computer Vision |
What field is the article from? | Title: Hybrid Quantum Neural Network in High-dimensional Data Classification
Abstract: The research explores the potential of quantum deep learning models to
address challenging machine learning problems that classical deep learning
models find difficult to tackle. We introduce a novel model architecture that
combines ... | Machine Learning |
What field is the article from? | Title: GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks
Abstract: In recent years, there has been a rapid development of spatio-temporal
prediction techniques in response to the increasing demands of traffic
management and travel planning. While advanced end-to-end models have achieved
notable s... | Machine Learning |
What field is the article from? | Title: Universal Jailbreak Backdoors from Poisoned Human Feedback
Abstract: Reinforcement Learning from Human Feedback (RLHF) is used to align large
language models to produce helpful and harmless responses. Yet, prior work
showed these models can be jailbroken by finding adversarial prompts that
revert the model to it... | Artificial Intelligence |
What field is the article from? | Title: Scope Compliance Uncertainty Estimate
Abstract: The zeitgeist of the digital era has been dominated by an expanding
integration of Artificial Intelligence~(AI) in a plethora of applications
across various domains. With this expansion, however, questions of the safety
and reliability of these methods come have be... | Artificial Intelligence |
What field is the article from? | Title: Extracting periodontitis diagnosis in clinical notes with RoBERTa and regular expression
Abstract: This study aimed to utilize text processing and natural language processing
(NLP) models to mine clinical notes for the diagnosis of periodontitis and to
evaluate the performance of a named entity recognition (NER)... | Artificial Intelligence |
What field is the article from? | Title: 3D-MIR: A Benchmark and Empirical Study on 3D Medical Image Retrieval in Radiology
Abstract: The increasing use of medical imaging in healthcare settings presents a
significant challenge due to the increasing workload for radiologists, yet it
also offers opportunity for enhancing healthcare outcomes if effective... | Computer Vision |
What field is the article from? | Title: Accented Speech Recognition With Accent-specific Codebooks
Abstract: Speech accents pose a significant challenge to state-of-the-art automatic
speech recognition (ASR) systems. Degradation in performance across
underrepresented accents is a severe deterrent to the inclusive adoption of
ASR. In this work, we prop... | Computational Linguistics |
What field is the article from? | Title: Enhancing Instance-Level Image Classification with Set-Level Labels
Abstract: Instance-level image classification tasks have traditionally relied on
single-instance labels to train models, e.g., few-shot learning and transfer
learning. However, set-level coarse-grained labels that capture relationships
among ins... | Machine Learning |
What field is the article from? | Title: Tackling Cyberattacks through AI-based Reactive Systems: A Holistic Review and Future Vision
Abstract: There is no denying that the use of Information Technology (IT) is undergoing
exponential growth in today's world. This digital transformation has also given
rise to a multitude of security challenges, notably ... | Cryptography and Security |
What field is the article from? | Title: Towards objective and systematic evaluation of bias in medical imaging AI
Abstract: Artificial intelligence (AI) models trained using medical images for clinical
tasks often exhibit bias in the form of disparities in performance between
subgroups. Since not all sources of biases in real-world medical imaging dat... | Computer Vision |
What field is the article from? | Title: The risks of risk-based AI regulation: taking liability seriously
Abstract: The development and regulation of multi-purpose, large "foundation models" of
AI seems to have reached a critical stage, with major investments and new
applications announced every other day. Some experts are calling for a
moratorium on ... | Computers and Society |
What field is the article from? | Title: ArchiGuesser -- AI Art Architecture Educational Game
Abstract: The use of generative AI in education is a controversial topic. Current
technology offers the potential to create educational content from text,
speech, to images based on simple input prompts. This can enhance productivity
by summarizing knowledge a... | Artificial Intelligence |
What field is the article from? | Title: Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions
Abstract: Recent advances in attention-free sequence models rely on convolutions as
alternatives to the attention operator at the core of Transformers. In
particular, long convolution sequence models have achieved state-of-the-art
perfor... | Machine Learning |
What field is the article from? | Title: Automated Parliaments: A Solution to Decision Uncertainty and Misalignment in Language Models
Abstract: As AI takes on a greater role in the modern world, it is essential to ensure
that AI models can overcome decision uncertainty and remain aligned with human
morality and interests. This research paper proposes ... | Artificial Intelligence |
What field is the article from? | Title: Early ChatGPT User Portrait through the Lens of Data
Abstract: Since its launch, ChatGPT has achieved remarkable success as a versatile
conversational AI platform, drawing millions of users worldwide and garnering
widespread recognition across academic, industrial, and general communities.
This paper aims to poi... | Human-Computer Interaction |
What field is the article from? | Title: A Survey of the Evolution of Language Model-Based Dialogue Systems
Abstract: Dialogue systems, including task-oriented_dialogue_system (TOD) and
open-domain_dialogue_system (ODD), have undergone significant transformations,
with language_models (LM) playing a central role. This survey delves into the
historical ... | Computational Linguistics |
What field is the article from? | Title: Scalable and Transferable Black-Box Jailbreaks for Language Models via Persona Modulation
Abstract: Despite efforts to align large language models to produce harmless responses,
they are still vulnerable to jailbreak prompts that elicit unrestricted
behaviour. In this work, we investigate persona modulation as a... | Computational Linguistics |
What field is the article from? | Title: Towards probabilistic Weather Forecasting with Conditioned Spatio-Temporal Normalizing Flows
Abstract: Generative normalizing flows are able to model multimodal spatial
distributions, and they have been shown to model temporal correlations
successfully as well. These models provide several benefits over other ty... | Machine Learning |
What field is the article from? | Title: Unmasking Deepfake Faces from Videos Using An Explainable Cost-Sensitive Deep Learning Approach
Abstract: Deepfake technology is widely used, which has led to serious worries about
the authenticity of digital media, making the need for trustworthy deepfake
face recognition techniques more urgent than ever. This ... | Computer Vision |
What field is the article from? | Title: Moderating Model Marketplaces: Platform Governance Puzzles for AI Intermediaries
Abstract: The AI development community is increasingly making use of hosting
intermediaries such as Hugging Face provide easy access to user-uploaded models
and training data. These model marketplaces lower technical deployment barr... | Computers and Society |
What field is the article from? | Title: Toward General-Purpose Robots via Foundation Models: A Survey and Meta-Analysis
Abstract: Building general-purpose robots that can operate seamlessly, in any
environment, with any object, and utilizing various skills to complete diverse
tasks has been a long-standing goal in Artificial Intelligence. Unfortunatel... | Robotics |
What field is the article from? | Title: InstructPTS: Instruction-Tuning LLMs for Product Title Summarization
Abstract: E-commerce product catalogs contain billions of items. Most products have
lengthy titles, as sellers pack them with product attributes to improve
retrieval, and highlight key product aspects. This results in a gap between
such unnatur... | Computational Linguistics |
What field is the article from? | Title: Will releasing the weights of future large language models grant widespread access to pandemic agents?
Abstract: Large language models can benefit research and human understanding by
providing tutorials that draw on expertise from many different fields. A
properly safeguarded model will refuse to provide "dual-u... | Artificial Intelligence |
What field is the article from? | Title: Data-Efficient Alignment of Large Language Models with Human Feedback Through Natural Language
Abstract: Learning from human feedback is a prominent technique to align the output of
large language models (LLMs) with human expectations. Reinforcement learning
from human feedback (RLHF) leverages human preference ... | Computational Linguistics |
What field is the article from? | Title: Two Stream Scene Understanding on Graph Embedding
Abstract: The paper presents a novel two-stream network architecture for enhancing
scene understanding in computer vision. This architecture utilizes a graph
feature stream and an image feature stream, aiming to merge the strengths of
both modalities for improved... | Computer Vision |
What field is the article from? | Title: Perspectives on the State and Future of Deep Learning -- 2023
Abstract: The goal of this series is to chronicle opinions and issues in the field of
machine learning as they stand today and as they change over time. The plan is
to host this survey periodically until the AI singularity
paperclip-frenzy-driven doom... | Artificial Intelligence |
What field is the article from? | Title: Refining Diffusion Planner for Reliable Behavior Synthesis by Automatic Detection of Infeasible Plans
Abstract: Diffusion-based planning has shown promising results in long-horizon,
sparse-reward tasks by training trajectory diffusion models and conditioning
the sampled trajectories using auxiliary guidance func... | Machine Learning |
What field is the article from? | Title: Enhancing Intrusion Detection In Internet Of Vehicles Through Federated Learning
Abstract: Federated learning is a technique of decentralized machine learning. that
allows multiple parties to collaborate and learn a shared model without sharing
their raw data. Our paper proposes a federated learning framework fo... | Cryptography and Security |
What field is the article from? | Title: Data-Driven Traffic Reconstruction and Kernel Methods for Identifying Stop-and-Go Congestion
Abstract: Identifying stop-and-go events (SAGs) in traffic flow presents an important
avenue for advancing data-driven research for climate change mitigation and
sustainability, owing to their substantial impact on carbo... | Machine Learning |
What field is the article from? | Title: Generalization Analysis of Policy Networks: An Example of Double-Integrator
Abstract: Extensive utilization of deep reinforcement learning (DRL) policy networks in
diverse continuous control tasks has raised questions regarding performance
degradation in expansive state spaces where the input state norm is large... | Machine Learning |
What field is the article from? | Title: Using Slisemap to interpret physical data
Abstract: Manifold visualisation techniques are commonly used to visualise
high-dimensional datasets in physical sciences. In this paper we apply a
recently introduced manifold visualisation method, called Slise, on datasets
from physics and chemistry. Slisemap combines ... | Machine Learning |
What field is the article from? | Title: Impact of HPO on AutoML Forecasting Ensembles
Abstract: A forecasting ensemble consisting of a diverse range of estimators for both
local and global univariate forecasting, in particular MQ-CNN,DeepAR, Prophet,
NPTS, ARIMA and ETS, can be used to make forecasts for a variety of problems.
This paper delves into t... | Machine Learning |
What field is the article from? | Title: Testing learning-enabled cyber-physical systems with Large-Language Models: A Formal Approach
Abstract: The integration of machine learning (ML) into cyber-physical systems (CPS)
offers significant benefits, including enhanced efficiency, predictive
capabilities, real-time responsiveness, and the enabling of aut... | Software Engineering |
What field is the article from? | Title: Embarassingly Simple Dataset Distillation
Abstract: Dataset distillation extracts a small set of synthetic training samples from
a large dataset with the goal of achieving competitive performance on test data
when trained on this sample. In this work, we tackle dataset distillation at
its core by treating it dir... | Machine Learning |
What field is the article from? | Title: VideoAssembler: Identity-Consistent Video Generation with Reference Entities using Diffusion Model
Abstract: Identity-consistent video generation seeks to synthesize videos that are
guided by both textual prompts and reference images of entities. Current
approaches typically utilize cross-attention layers to int... | Computer Vision |
What field is the article from? | Title: Improving fit to human reading times via temperature-scaled surprisal
Abstract: Past studies have provided broad support for that words with lower
predictability (i.e., higher surprisal) require more time for comprehension by
using large language models (LLMs) to simulate humans' cognitive load. In
general, thes... | Computational Linguistics |
What field is the article from? | Title: Boosting the Power of Small Multimodal Reasoning Models to Match Larger Models with Self-Consistency Training
Abstract: Multimodal reasoning is a challenging task that requires models to reason
across multiple modalities to answer questions. Existing approaches have made
progress by incorporating language and vi... | Artificial Intelligence |
What field is the article from? | Title: Effective Backdoor Mitigation Depends on the Pre-training Objective
Abstract: Despite the advanced capabilities of contemporary machine learning (ML)
models, they remain vulnerable to adversarial and backdoor attacks. This
vulnerability is particularly concerning in real-world deployments, where
compromised mode... | Machine Learning |
What field is the article from? | Title: Fact-based Court Judgment Prediction
Abstract: This extended abstract extends the research presented in "ILDC for CJPE:
Indian Legal Documents Corpus for Court Judgment Prediction and Explanation"
\cite{malik-etal-2021-ildc}, focusing on fact-based judgment prediction within
the context of Indian legal documents... | Computational Linguistics |
What field is the article from? | Title: Act-VIT: A Representationally Robust Attention Architecture for Skeleton Based Action Recognition Using Vision Transformer
Abstract: Skeleton-based action recognition receives the attention of many researchers
as it is robust to viewpoint and illumination changes, and its processing is
much more efficient than v... | Computer Vision |
What field is the article from? | Title: Video Summarization: Towards Entity-Aware Captions
Abstract: Existing popular video captioning benchmarks and models deal with generic
captions devoid of specific person, place or organization named entities. In
contrast, news videos present a challenging setting where the caption requires
such named entities fo... | Computer Vision |
What field is the article from? | Title: Overview of the TREC 2023 Product Product Search Track
Abstract: This is the first year of the TREC Product search track. The focus this year
was the creation of a reusable collection and evaluation of the impact of the
use of metadata and multi-modal data on retrieval accuracy. This year we
leverage the new pro... | Information Retrieval |
What field is the article from? | Title: Learning-Based Approaches to Predictive Monitoring with Conformal Statistical Guarantees
Abstract: This tutorial focuses on efficient methods to predictive monitoring (PM), the
problem of detecting at runtime future violations of a given requirement from
the current state of a system. While performing model chec... | Artificial Intelligence |
What field is the article from? | Title: Mark My Words: Analyzing and Evaluating Language Model Watermarks
Abstract: The capabilities of large language models have grown significantly in recent
years and so too have concerns about their misuse. In this context, the ability
to distinguish machine-generated text from human-authored content becomes
import... | Cryptography and Security |
What field is the article from? | Title: Inversion-Free Image Editing with Natural Language
Abstract: Despite recent advances in inversion-based editing, text-guided image
manipulation remains challenging for diffusion models. The primary bottlenecks
include 1) the time-consuming nature of the inversion process; 2) the struggle
to balance consistency w... | Computer Vision |
What field is the article from? | Title: Social Contract AI: Aligning AI Assistants with Implicit Group Norms
Abstract: We explore the idea of aligning an AI assistant by inverting a model of
users' (unknown) preferences from observed interactions. To validate our
proposal, we run proof-of-concept simulations in the economic ultimatum game,
formalizing... | Computational Linguistics |
What field is the article from? | Title: Enchancing Semi-Supervised Learning for Extractive Summarization with an LLM-based pseudolabeler
Abstract: This work tackles the task of extractive text summarization in a limited
labeled data scenario using a semi-supervised approach. Specifically, we
propose a prompt-based pseudolabel selection strategy using ... | Computational Linguistics |
What field is the article from? | Title: Can we infer the presence of Differential Privacy in Deep Learning models' weights? Towards more secure Deep Learning
Abstract: Differential Privacy (DP) is a key property to protect data and models from
integrity attacks. In the Deep Learning (DL) field, it is commonly implemented
through the Differentially Pri... | Machine Learning |
What field is the article from? | Title: Understanding the Effects of Projectors in Knowledge Distillation
Abstract: Conventionally, during the knowledge distillation process (e.g. feature
distillation), an additional projector is often required to perform feature
transformation due to the dimension mismatch between the teacher and the
student networks... | Computer Vision |
What field is the article from? | Title: LLMs for Science: Usage for Code Generation and Data Analysis
Abstract: Large language models (LLMs) have been touted to enable increased
productivity in many areas of today's work life. Scientific research as an area
of work is no exception: the potential of LLM-based tools to assist in the
daily work of scient... | Software Engineering |
What field is the article from? | Title: Automatic Aorta Segmentation with Heavily Augmented, High-Resolution 3-D ResUNet: Contribution to the SEG.A Challenge
Abstract: Automatic aorta segmentation from 3-D medical volumes is an important yet
difficult task. Several factors make the problem challenging, e.g. the
possibility of aortic dissection or the ... | Computer Vision |
What field is the article from? | Title: Making Large Multimodal Models Understand Arbitrary Visual Prompts
Abstract: While existing large vision-language multimodal models focus on whole image
understanding, there is a prominent gap in achieving region-specific
comprehension. Current approaches that use textual coordinates or spatial
encodings often f... | Computer Vision |
What field is the article from? | Title: A* search algorithm for an optimal investment problem in vehicle-sharing systems
Abstract: We study an optimal investment problem that arises in the context of the
vehicle-sharing system. Given a set of locations to build stations, we need to
determine i) the sequence of stations to be built and the number of ve... | Artificial Intelligence |
What field is the article from? | Title: Revisiting Graph-based Fraud Detection in Sight of Heterophily and Spectrum
Abstract: Graph-based fraud detection (GFD) can be regarded as a challenging
semi-supervised node binary classification task. In recent years, Graph Neural
Networks(GNN) have been widely applied to GFD, characterizing the anomalous
possi... | Machine Learning |
What field is the article from? | Title: Don't Waste a Single Annotation: Improving Single-Label Classifiers Through Soft Labels
Abstract: In this paper, we address the limitations of the common data annotation and
training methods for objective single-label classification tasks. Typically,
when annotating such tasks annotators are only asked to provid... | Computational Linguistics |
What field is the article from? | Title: Exploring the Impact of Lay User Feedback for Improving AI Fairness
Abstract: Fairness in AI is a growing concern for high-stakes decision making. Engaging
stakeholders, especially lay users, in fair AI development is promising yet
overlooked. Recent efforts explore enabling lay users to provide AI
fairness-rela... | Artificial Intelligence |
What field is the article from? | Title: Model-as-a-Service (MaaS): A Survey
Abstract: Due to the increased number of parameters and data in the pre-trained model
exceeding a certain level, a foundation model (e.g., a large language model)
can significantly improve downstream task performance and emerge with some
novel special abilities (e.g., deep lea... | Artificial Intelligence |
What field is the article from? | Title: MineSegSAT: An automated system to evaluate mining disturbed area extents from Sentinel-2 imagery
Abstract: Assessing the environmental impact of the mineral extraction industry plays a
critical role in understanding and mitigating the ecological consequences of
extractive activities. This paper presents MineSeg... | Computer Vision |
What field is the article from? | Title: ROSO: Improving Robotic Policy Inference via Synthetic Observations
Abstract: In this paper, we propose the use of generative artificial intelligence (AI)
to improve zero-shot performance of a pre-trained policy by altering
observations during inference. Modern robotic systems, powered by advanced
neural network... | Robotics |
What field is the article from? | Title: Detecting and Restoring Non-Standard Hands in Stable Diffusion Generated Images
Abstract: We introduce a pipeline to address anatomical inaccuracies in Stable
Diffusion generated hand images. The initial step involves constructing a
specialized dataset, focusing on hand anomalies, to train our models
effectively... | Computer Vision |
What field is the article from? | Title: Reacting like Humans: Incorporating Intrinsic Human Behaviors into NAO through Sound-Based Reactions for Enhanced Sociability
Abstract: Robots' acceptability among humans and their sociability can be significantly
enhanced by incorporating human-like reactions. Humans can react to
environmental events very quick... | Robotics |
What field is the article from? | Title: Multiple Instance Learning for Uplift Modeling
Abstract: Uplift modeling is widely used in performance marketing to estimate effects
of promotion campaigns (e.g., increase of customer retention rate). Since it is
impossible to observe outcomes of a recipient in treatment (e.g., receiving a
certain promotion) and... | Machine Learning |
What field is the article from? | Title: Efficient Off-Policy Safe Reinforcement Learning Using Trust Region Conditional Value at Risk
Abstract: This paper aims to solve a safe reinforcement learning (RL) problem with risk
measure-based constraints. As risk measures, such as conditional value at risk
(CVaR), focus on the tail distribution of cost signa... | Machine Learning |
What field is the article from? | Title: GraphTransformers for Geospatial Forecasting of Hurricane Trajectories
Abstract: In this paper we introduce a novel framework for trajectory prediction of
geospatial sequences using GraphTransformers. When viewed across several
sequences, we observed that a graph structure automatically emerges between
different... | Artificial Intelligence |
What field is the article from? | Title: PWISeg: Point-based Weakly-supervised Instance Segmentation for Surgical Instruments
Abstract: In surgical procedures, correct instrument counting is essential. Instance
segmentation is a location method that locates not only an object's bounding
box but also each pixel's specific details. However, obtaining mas... | Computer Vision |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.