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What field is the article from? | Title: Leveraging Speculative Sampling and KV-Cache Optimizations Together for Generative AI using OpenVINO
Abstract: Inference optimizations are critical for improving user experience and
reducing infrastructure costs and power consumption. In this article, we
illustrate a form of dynamic execution known as speculativ... | Machine Learning |
What field is the article from? | Title: Explainable Spatio-Temporal Graph Neural Networks
Abstract: Spatio-temporal graph neural networks (STGNNs) have gained popularity as a
powerful tool for effectively modeling spatio-temporal dependencies in diverse
real-world urban applications, including intelligent transportation and public
safety. However, the... | Machine Learning |
What field is the article from? | Title: Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization
Abstract: Large foundation models are becoming ubiquitous, but training them from
scratch is prohibitively expensive. Thus, efficiently adapting these powerful
models to downstream tasks is increasingly important. In this paper, we study a
pri... | Machine Learning |
What field is the article from? | Title: Learning to Design and Use Tools for Robotic Manipulation
Abstract: When limited by their own morphologies, humans and some species of animals
have the remarkable ability to use objects from the environment toward
accomplishing otherwise impossible tasks. Robots might similarly unlock a range
of additional capab... | Robotics |
What field is the article from? | Title: MalPurifier: Enhancing Android Malware Detection with Adversarial Purification against Evasion Attacks
Abstract: Machine learning (ML) has gained significant adoption in Android malware
detection to address the escalating threats posed by the rapid proliferation of
malware attacks. However, recent studies have r... | Cryptography and Security |
What field is the article from? | Title: Active Wildfires Detection and Dynamic Escape Routes Planning for Humans through Information Fusion between Drones and Satellites
Abstract: UAVs are playing an increasingly important role in the field of wilderness
rescue by virtue of their flexibility. This paper proposes a fusion of UAV
vision technology and s... | Artificial Intelligence |
What field is the article from? | Title: One-2-3-45++: Fast Single Image to 3D Objects with Consistent Multi-View Generation and 3D Diffusion
Abstract: Recent advancements in open-world 3D object generation have been remarkable,
with image-to-3D methods offering superior fine-grained control over their
text-to-3D counterparts. However, most existing mo... | Computer Vision |
What field is the article from? | Title: (Ir)rationality in AI: State of the Art, Research Challenges and Open Questions
Abstract: The concept of rationality is central to the field of artificial
intelligence. Whether we are seeking to simulate human reasoning, or the goal
is to achieve bounded optimality, we generally seek to make artificial agents
as... | Artificial Intelligence |
What field is the article from? | Title: Hypergraph-Guided Disentangled Spectrum Transformer Networks for Near-Infrared Facial Expression Recognition
Abstract: With the strong robusticity on illumination variations, near-infrared (NIR)
can be an effective and essential complement to visible (VIS) facial expression
recognition in low lighting or complet... | Computer Vision |
What field is the article from? | Title: Towards Formal Fault Injection for Safety Assessment of Automated Systems
Abstract: Reasoning about safety, security, and other dependability attributes of
autonomous systems is a challenge that needs to be addressed before the
adoption of such systems in day-to-day life. Formal methods is a class of
methods tha... | Artificial Intelligence |
What field is the article from? | Title: Improving embedding of graphs with missing data by soft manifolds
Abstract: Embedding graphs in continous spaces is a key factor in designing and
developing algorithms for automatic information extraction to be applied in
diverse tasks (e.g., learning, inferring, predicting). The reliability of graph
embeddings ... | Machine Learning |
What field is the article from? | Title: CausalCite: A Causal Formulation of Paper Citations
Abstract: Evaluating the significance of a paper is pivotal yet challenging for the
scientific community. While the citation count is the most commonly used proxy
for this purpose, they are widely criticized for failing to accurately reflect
a paper's true impa... | Computational Linguistics |
What field is the article from? | Title: SceneDM: Scene-level Multi-agent Trajectory Generation with Consistent Diffusion Models
Abstract: Realistic scene-level multi-agent motion simulations are crucial for
developing and evaluating self-driving algorithms. However, most existing works
focus on generating trajectories for a certain single agent type, ... | Robotics |
What field is the article from? | Title: Structured World Representations in Maze-Solving Transformers
Abstract: Transformer models underpin many recent advances in practical machine
learning applications, yet understanding their internal behavior continues to
elude researchers. Given the size and complexity of these models, forming a
comprehensive pic... | Machine Learning |
What field is the article from? | Title: Vanishing Gradients in Reinforcement Finetuning of Language Models
Abstract: Pretrained language models are commonly aligned with human preferences and
downstream tasks via reinforcement finetuning (RFT), which entails maximizing a
(possibly learned) reward function using policy gradient algorithms. This work
hi... | Machine Learning |
What field is the article from? | Title: Revamping AI Models in Dermatology: Overcoming Critical Challenges for Enhanced Skin Lesion Diagnosis
Abstract: The surge in developing deep learning models for diagnosing skin lesions
through image analysis is notable, yet their clinical black faces challenges.
Current dermatology AI models have limitations: li... | Computer Vision |
What field is the article from? | Title: Towards Auditing Large Language Models: Improving Text-based Stereotype Detection
Abstract: Large Language Models (LLM) have made significant advances in the recent past
becoming more mainstream in Artificial Intelligence (AI) enabled human-facing
applications. However, LLMs often generate stereotypical output i... | Computational Linguistics |
What field is the article from? | Title: Back Transcription as a Method for Evaluating Robustness of Natural Language Understanding Models to Speech Recognition Errors
Abstract: In a spoken dialogue system, an NLU model is preceded by a speech recognition
system that can deteriorate the performance of natural language understanding.
This paper proposes... | Computational Linguistics |
What field is the article from? | Title: Mapping the Empirical Evidence of the GDPR (In-)Effectiveness: A Systematic Review
Abstract: In the realm of data protection, a striking disconnect prevails between
traditional domains of doctrinal, legal, theoretical, and policy-based
inquiries and a burgeoning body of empirical evidence. Much of the scholarly
... | Computers and Society |
What field is the article from? | Title: Improving Compositional Generalization Using Iterated Learning and Simplicial Embeddings
Abstract: Compositional generalization, the ability of an agent to generalize to unseen
combinations of latent factors, is easy for humans but hard for deep neural
networks. A line of research in cognitive science has hypoth... | Machine Learning |
What field is the article from? | Title: Towards Transparency in Coreference Resolution: A Quantum-Inspired Approach
Abstract: Guided by grammatical structure, words compose to form sentences, and guided
by discourse structure, sentences compose to form dialogues and documents. The
compositional aspect of sentence and discourse units is often overlooke... | Computational Linguistics |
What field is the article from? | Title: OtterHD: A High-Resolution Multi-modality Model
Abstract: In this paper, we present OtterHD-8B, an innovative multimodal model evolved
from Fuyu-8B, specifically engineered to interpret high-resolution visual
inputs with granular precision. Unlike conventional models that are constrained
by fixed-size vision enc... | Computer Vision |
What field is the article from? | Title: Backward Learning for Goal-Conditioned Policies
Abstract: Can we learn policies in reinforcement learning without rewards? Can we learn
a policy just by trying to reach a goal state? We answer these questions
positively by proposing a multi-step procedure that first learns a world model
that goes backward in tim... | Machine Learning |
What field is the article from? | Title: Topology Recoverability Prediction for Ad-Hoc Robot Networks: A Data-Driven Fault-Tolerant Approach
Abstract: Faults occurring in ad-hoc robot networks may fatally perturb their
topologies leading to disconnection of subsets of those networks. Optimal
topology synthesis is generally resource-intensive and time-c... | Robotics |
What field is the article from? | Title: FormaT5: Abstention and Examples for Conditional Table Formatting with Natural Language
Abstract: Formatting is an important property in tables for visualization,
presentation, and analysis. Spreadsheet software allows users to automatically
format their tables by writing data-dependent conditional formatting (C... | Artificial Intelligence |
What field is the article from? | Title: Moments for Perceptive Narration Analysis Through the Emotional Attachment of Audience to Discourse and Story
Abstract: In this work, our goal is to develop a theoretical framework that can
eventually be used for analyzing the effectiveness of visual stories such as
feature films to comic books. To develop this ... | Artificial Intelligence |
What field is the article from? | Title: Ensembling Textual and Structure-Based Models for Knowledge Graph Completion
Abstract: We consider two popular approaches to Knowledge Graph Completion (KGC):
textual models that rely on textual entity descriptions, and structure-based
models that exploit the connectivity structure of the Knowledge Graph (KG).
P... | Computational Linguistics |
What field is the article from? | Title: Adapters: A Unified Library for Parameter-Efficient and Modular Transfer Learning
Abstract: We introduce Adapters, an open-source library that unifies
parameter-efficient and modular transfer learning in large language models. By
integrating 10 diverse adapter methods into a unified interface, Adapters
offers ea... | Computational Linguistics |
What field is the article from? | Title: A Comprehensive Review of AI-enabled Unmanned Aerial Vehicle: Trends, Vision , and Challenges
Abstract: In recent years, the combination of artificial intelligence (AI) and unmanned
aerial vehicles (UAVs) has brought about advancements in various areas. This
comprehensive analysis explores the changing landscape... | Artificial Intelligence |
What field is the article from? | Title: Algorithms for automatic intents extraction and utterances classification for goal-oriented dialogue systems
Abstract: Modern machine learning techniques in the natural language processing domain
can be used to automatically generate scripts for goal-oriented dialogue
systems. The current article presents a gene... | Artificial Intelligence |
What field is the article from? | Title: Look At Me, No Replay! SurpriseNet: Anomaly Detection Inspired Class Incremental Learning
Abstract: Continual learning aims to create artificial neural networks capable of
accumulating knowledge and skills through incremental training on a sequence of
tasks. The main challenge of continual learning is catastroph... | Artificial Intelligence |
What field is the article from? | Title: Retro-BLEU: Quantifying Chemical Plausibility of Retrosynthesis Routes through Reaction Template Sequence Analysis
Abstract: Computer-assisted methods have emerged as valuable tools for retrosynthesis
analysis. However, quantifying the plausibility of generated retrosynthesis
routes remains a challenging task. W... | Machine Learning |
What field is the article from? | Title: KPIs-Based Clustering and Visualization of HPC jobs: a Feature Reduction Approach
Abstract: High-Performance Computing (HPC) systems need to be constantly monitored to
ensure their stability. The monitoring systems collect a tremendous amount of
data about different parameters or Key Performance Indicators (KPIs... | Artificial Intelligence |
What field is the article from? | Title: OTOv3: Automatic Architecture-Agnostic Neural Network Training and Compression from Structured Pruning to Erasing Operators
Abstract: Compressing a predefined deep neural network (DNN) into a compact sub-network
with competitive performance is crucial in the efficient machine learning
realm. This topic spans var... | Machine Learning |
What field is the article from? | Title: A Language Model with Limited Memory Capacity Captures Interference in Human Sentence Processing
Abstract: Two of the central factors believed to underpin human sentence processing
difficulty are expectations and retrieval from working memory. A recent attempt
to create a unified cognitive model integrating thes... | Computational Linguistics |
What field is the article from? | Title: Frontier Language Models are not Robust to Adversarial Arithmetic, or "What do I need to say so you agree 2+2=5?
Abstract: We introduce and study the problem of adversarial arithmetic, which provides
a simple yet challenging testbed for language model alignment. This problem is
comprised of arithmetic questions ... | Computational Linguistics |
What field is the article from? | Title: Gender inference: can chatGPT outperform common commercial tools?
Abstract: An increasing number of studies use gender information to understand
phenomena such as gender bias, inequity in access and participation, or the
impact of the Covid pandemic response. Unfortunately, most datasets do not
include self-repo... | Computational Linguistics |
What field is the article from? | Title: Visual tracking brain computer interface
Abstract: Brain-computer interfaces (BCIs) offer a way to interact with computers
without relying on physical movements. Non-invasive electroencephalography
(EEG)-based visual BCIs, known for efficient speed and calibration ease, face
limitations in continuous tasks due t... | Human-Computer Interaction |
What field is the article from? | Title: Efficient LLM Inference on CPUs
Abstract: Large language models (LLMs) have demonstrated remarkable performance and
tremendous potential across a wide range of tasks. However, deploying these
models has been challenging due to the astronomical amount of model parameters,
which requires a demand for large memory ... | Machine Learning |
What field is the article from? | Title: LooGLE: Can Long-Context Language Models Understand Long Contexts?
Abstract: Large language models (LLMs), despite their impressive performance in various
language tasks, are typically limited to processing texts within context-window
size. This limitation has spurred significant research efforts to enhance LLMs... | Computational Linguistics |
What field is the article from? | Title: Lecture Notes in Probabilistic Diffusion Models
Abstract: Diffusion models are loosely modelled based on non-equilibrium
thermodynamics, where \textit{diffusion} refers to particles flowing from
high-concentration regions towards low-concentration regions. In statistics,
the meaning is quite similar, namely the ... | Machine Learning |
What field is the article from? | Title: Zero-Shot Goal-Directed Dialogue via RL on Imagined Conversations
Abstract: Large language models (LLMs) have emerged as powerful and general solutions
to many natural language tasks. However, many of the most important
applications of language generation are interactive, where an agent has to talk
to a person t... | Machine Learning |
What field is the article from? | Title: Is Machine Learning Unsafe and Irresponsible in Social Sciences? Paradoxes and Reconsidering from Recidivism Prediction Tasks
Abstract: The paper addresses some fundamental and hotly debated issues for high-stakes
event predictions underpinning the computational approach to social sciences.
We question several p... | Computers and Society |
What field is the article from? | Title: Multi-Resolution Diffusion for Privacy-Sensitive Recommender Systems
Abstract: While recommender systems have become an integral component of the Web
experience, their heavy reliance on user data raises privacy and security
concerns. Substituting user data with synthetic data can address these
concerns, but accu... | Information Retrieval |
What field is the article from? | Title: SEMQA: Semi-Extractive Multi-Source Question Answering
Abstract: Recently proposed long-form question answering (QA) systems, supported by
large language models (LLMs), have shown promising capabilities. Yet,
attributing and verifying their generated abstractive answers can be difficult,
and automatically evalua... | Computational Linguistics |
What field is the article from? | Title: RDR: the Recap, Deliberate, and Respond Method for Enhanced Language Understanding
Abstract: Natural language understanding (NLU) using neural network pipelines often
requires additional context that is not solely present in the input data.
Through Prior research, it has been evident that NLU benchmarks are susc... | Computational Linguistics |
What field is the article from? | Title: Towards Mitigating Perceived Unfairness in Contracts from a Non-Legal Stakeholder's Perspective
Abstract: Commercial contracts are known to be a valuable source for deriving
project-specific requirements. However, contract negotiations mainly occur
among the legal counsel of the parties involved. The participati... | Computational Linguistics |
What field is the article from? | Title: Large Language Models for Robotics: A Survey
Abstract: The human ability to learn, generalize, and control complex manipulation
tasks through multi-modality feedback suggests a unique capability, which we
refer to as dexterity intelligence. Understanding and assessing this
intelligence is a complex task. Amidst ... | Robotics |
What field is the article from? | Title: Emotion Recognition by Video: A review
Abstract: Video emotion recognition is an important branch of affective computing, and
its solutions can be applied in different fields such as human-computer
interaction (HCI) and intelligent medical treatment. Although the number of
papers published in the field of emotio... | Computer Vision |
What field is the article from? | Title: Breast Cancer classification by adaptive weighted average ensemble of previously trained models
Abstract: Breast cancer is a serious disease that inflicts millions of people each
year, and the number of cases is increasing. Early detection is the best way to
reduce the impact of the disease. Researchers have dev... | Artificial Intelligence |
What field is the article from? | Title: Generative Input: Towards Next-Generation Input Methods Paradigm
Abstract: Since the release of ChatGPT, generative models have achieved tremendous
success and become the de facto approach for various NLP tasks. However, its
application in the field of input methods remains under-explored. Many neural
network ap... | Computational Linguistics |
What field is the article from? | Title: On The Truthfulness of 'Surprisingly Likely' Responses of Large Language Models
Abstract: The surprisingly likely criterion in the seminal work of Prelec (the Bayesian
Truth Serum) guarantees truthfulness in a game-theoretic multi-agent setting,
by rewarding rational agents to maximise the expected information g... | Machine Learning |
What field is the article from? | Title: FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objects
Abstract: We present FoundationPose, a unified foundation model for 6D object pose
estimation and tracking, supporting both model-based and model-free setups. Our
approach can be instantly applied at test-time to a novel object without
fine... | Computer Vision |
What field is the article from? | Title: Verification of Neural Reachable Tubes via Scenario Optimization and Conformal Prediction
Abstract: Learning-based approaches for controlling safety-critical systems are rapidly
growing in popularity; thus, it is important to assure their performance and
safety. Hamilton-Jacobi (HJ) reachability analysis is a po... | Robotics |
What field is the article from? | Title: Counterfactual-Augmented Importance Sampling for Semi-Offline Policy Evaluation
Abstract: In applying reinforcement learning (RL) to high-stakes domains, quantitative
and qualitative evaluation using observational data can help practitioners
understand the generalization performance of new policies. However, thi... | Machine Learning |
What field is the article from? | Title: Interpreting Pretrained Language Models via Concept Bottlenecks
Abstract: Pretrained language models (PLMs) have made significant strides in various
natural language processing tasks. However, the lack of interpretability due to
their ``black-box'' nature poses challenges for responsible implementation.
Although... | Computational Linguistics |
What field is the article from? | Title: An Empirical Bayes Framework for Open-Domain Dialogue Generation
Abstract: To engage human users in meaningful conversation, open-domain dialogue agents
are required to generate diverse and contextually coherent dialogue. Despite
recent advancements, which can be attributed to the usage of pretrained
language mo... | Computational Linguistics |
What field is the article from? | Title: Social, Legal, Ethical, Empathetic, and Cultural Rules: Compilation and Reasoning (Extended Version)
Abstract: The rise of AI-based and autonomous systems is raising concerns and
apprehension due to potential negative repercussions stemming from their
behavior or decisions. These systems must be designed to comp... | Artificial Intelligence |
What field is the article from? | Title: Evaluating Supervision Levels Trade-Offs for Infrared-Based People Counting
Abstract: Object detection models are commonly used for people counting (and
localization) in many applications but require a dataset with costly bounding
box annotations for training. Given the importance of privacy in people
counting, ... | Computer Vision |
What field is the article from? | Title: KITS: Inductive Spatio-Temporal Kriging with Increment Training Strategy
Abstract: Sensors are commonly deployed to perceive the environment. However, due to
the high cost, sensors are usually sparsely deployed. Kriging is the tailored
task to infer the unobserved nodes (without sensors) using the observed sourc... | Machine Learning |
What field is the article from? | Title: Local Universal Rule-based Explanations
Abstract: Explainable artificial intelligence (XAI) is one of the most intensively
developed are of AI in recent years. It is also one of the most fragmented one
with multiple methods that focus on different aspects of explanations. This
makes difficult to obtain the full ... | Artificial Intelligence |
What field is the article from? | Title: Signal Temporal Logic-Guided Apprenticeship Learning
Abstract: Apprenticeship learning crucially depends on effectively learning rewards,
and hence control policies from user demonstrations. Of particular difficulty
is the setting where the desired task consists of a number of sub-goals with
temporal dependencie... | Robotics |
What field is the article from? | Title: Nonlinear Multi-objective Reinforcement Learning with Provable Guarantees
Abstract: We describe RA-E3 (Reward-Aware Explicit Explore or Exploit), an algorithm
with provable guarantees for solving a single or multi-objective Markov
Decision Process (MDP) where we want to maximize the expected value of a
nonlinear... | Machine Learning |
What field is the article from? | Title: Diffusion-C: Unveiling the Generative Challenges of Diffusion Models through Corrupted Data
Abstract: In our contemporary academic inquiry, we present "Diffusion-C," a
foundational methodology to analyze the generative restrictions of Diffusion
Models, particularly those akin to GANs, DDPM, and DDIM. By employin... | Machine Learning |
What field is the article from? | Title: Transdisciplinary AI Education: The Confluence of Curricular and Community Needs in the Instruction of Artificial Intelligence
Abstract: The integration of artificial intelligence (AI) into education has the
potential to transform the way we learn and teach. In this paper, we examine
the current state of AI in e... | Computers and Society |
What field is the article from? | Title: Unbiased organism-agnostic and highly sensitive signal peptide predictor with deep protein language model
Abstract: Signal peptide (SP) is a short peptide located in the N-terminus of proteins.
It is essential to target and transfer transmembrane and secreted proteins to
correct positions. Compared with traditio... | Artificial Intelligence |
What field is the article from? | Title: ReConTab: Regularized Contrastive Representation Learning for Tabular Data
Abstract: Representation learning stands as one of the critical machine learning
techniques across various domains. Through the acquisition of high-quality
features, pre-trained embeddings significantly reduce input space redundancy,
bene... | Machine Learning |
What field is the article from? | Title: Computational Copyright: Towards A Royalty Model for AI Music Generation Platforms
Abstract: The advancement of generative AI has given rise to pressing copyright
challenges, particularly in music industry. This paper focuses on the economic
aspects of these challenges, emphasizing that the economic impact const... | Artificial Intelligence |
What field is the article from? | Title: JarviX: A LLM No code Platform for Tabular Data Analysis and Optimization
Abstract: In this study, we introduce JarviX, a sophisticated data analytics framework.
JarviX is designed to employ Large Language Models (LLMs) to facilitate an
automated guide and execute high-precision data analyzes on tabular datasets... | Machine Learning |
What field is the article from? | Title: Rethinking Decision Transformer via Hierarchical Reinforcement Learning
Abstract: Decision Transformer (DT) is an innovative algorithm leveraging recent
advances of the transformer architecture in reinforcement learning (RL).
However, a notable limitation of DT is its reliance on recalling trajectories
from data... | Machine Learning |
What field is the article from? | Title: Medical Image Retrieval Using Pretrained Embeddings
Abstract: A wide range of imaging techniques and data formats available for medical
images make accurate retrieval from image databases challenging.
Efficient retrieval systems are crucial in advancing medical research,
enabling large-scale studies and innova... | Computer Vision |
What field is the article from? | Title: Intelligent Anomaly Detection for Lane Rendering Using Transformer with Self-Supervised Pre-Training and Customized Fine-Tuning
Abstract: The burgeoning navigation services using digital maps provide great
convenience to drivers. Nevertheless, the presence of anomalies in lane
rendering map images occasionally i... | Computer Vision |
What field is the article from? | Title: Diversified Node Sampling based Hierarchical Transformer Pooling for Graph Representation Learning
Abstract: Graph pooling methods have been widely used on downsampling graphs, achieving
impressive results on multiple graph-level tasks like graph classification and
graph generation. An important line called node... | Artificial Intelligence |
What field is the article from? | Title: Correction with Backtracking Reduces Hallucination in Summarization
Abstract: Abstractive summarization aims at generating natural language summaries of a
source document that are succinct while preserving the important elements.
Despite recent advances, neural text summarization models are known to be
susceptib... | Computational Linguistics |
What field is the article from? | Title: MI-Gen: Multiple Instance Generation of Pathology Reports for Gigapixel Whole-Slide Images
Abstract: Whole slide images are the foundation of digital pathology for the diagnosis
and treatment of carcinomas. Writing pathology reports is laborious and
error-prone for inexperienced pathologists. To reduce the workl... | Computer Vision |
What field is the article from? | Title: Concept Distillation: Leveraging Human-Centered Explanations for Model Improvement
Abstract: Humans use abstract concepts for understanding instead of hard features.
Recent interpretability research has focused on human-centered concept
explanations of neural networks. Concept Activation Vectors (CAVs) estimate ... | Machine Learning |
What field is the article from? | Title: Neural Machine Translation of Clinical Text: An Empirical Investigation into Multilingual Pre-Trained Language Models and Transfer-Learning
Abstract: We conduct investigations on clinical text machine translation by examining
multilingual neural network models using deep learning such as Transformer
based struct... | Computational Linguistics |
What field is the article from? | Title: Apollo's Oracle: Retrieval-Augmented Reasoning in Multi-Agent Debates
Abstract: Multi-agent debate systems are designed to derive accurate and consistent
conclusions through adversarial interactions among agents. However, these
systems often encounter challenges due to cognitive constraints, manifesting as
(1) a... | Computational Linguistics |
What field is the article from? | Title: Compositional Chain-of-Thought Prompting for Large Multimodal Models
Abstract: The combination of strong visual backbones and Large Language Model (LLM)
reasoning has led to Large Multimodal Models (LMMs) becoming the current
standard for a wide range of vision and language (VL) tasks. However, recent
research h... | Computer Vision |
What field is the article from? | Title: LMD: Faster Image Reconstruction with Latent Masking Diffusion
Abstract: As a class of fruitful approaches, diffusion probabilistic models (DPMs) have
shown excellent advantages in high-resolution image reconstruction. On the
other hand, masked autoencoders (MAEs), as popular self-supervised vision
learners, hav... | Computer Vision |
What field is the article from? | Title: Do Physicians Know How to Prompt? The Need for Automatic Prompt Optimization Help in Clinical Note Generation
Abstract: This study examines the effect of prompt engineering on the performance of
Large Language Models (LLMs) in clinical note generation. We introduce an
Automatic Prompt Optimization (APO) framewor... | Computational Linguistics |
What field is the article from? | Title: Analyzing and Predicting Low-Listenership Trends in a Large-Scale Mobile Health Program: A Preliminary Investigation
Abstract: Mobile health programs are becoming an increasingly popular medium for
dissemination of health information among beneficiaries in less privileged
communities. Kilkari is one of the world... | Machine Learning |
What field is the article from? | Title: Contrastive Multi-Level Graph Neural Networks for Session-based Recommendation
Abstract: Session-based recommendation (SBR) aims to predict the next item at a certain
time point based on anonymous user behavior sequences. Existing methods
typically model session representation based on simple item transition
inf... | Information Retrieval |
What field is the article from? | Title: The Case for Universal Basic Computing Power
Abstract: The Universal Basic Computing Power (UBCP) initiative ensures global, free
access to a set amount of computing power specifically for AI research and
development (R&D). This initiative comprises three key elements. First, UBCP
must be cost free, with its usa... | Artificial Intelligence |
What field is the article from? | Title: Contractive error feedback for gradient compression
Abstract: On-device memory concerns in distributed deep learning have become severe due
to (i) the growth of model size in multi-GPU training, and (ii) the wide
adoption of deep neural networks for federated learning on IoT devices which
have limited storage. I... | Machine Learning |
What field is the article from? | Title: Distributed Learning of Mixtures of Experts
Abstract: In modern machine learning problems we deal with datasets that are either
distributed by nature or potentially large for which distributing the
computations is usually a standard way to proceed, since centralized algorithms
are in general ineffective. We prop... | Machine Learning |
What field is the article from? | Title: Challenging Common Assumptions in Multi-task Learning
Abstract: While multi-task learning (MTL) has gained significant attention in recent
years, its underlying mechanisms remain poorly understood. Recent methods did
not yield consistent performance improvements over single task learning (STL)
baselines, undersc... | Machine Learning |
What field is the article from? | Title: General Phrase Debiaser: Debiasing Masked Language Models at a Multi-Token Level
Abstract: The social biases and unwelcome stereotypes revealed by pretrained language
models are becoming obstacles to their application. Compared to numerous
debiasing methods targeting word level, there has been relatively less
at... | Computational Linguistics |
What field is the article from? | Title: PromptInfuser: How Tightly Coupling AI and UI Design Impacts Designers' Workflows
Abstract: Prototyping AI applications is notoriously difficult. While large language
model (LLM) prompting has dramatically lowered the barriers to AI prototyping,
designers are still prototyping AI functionality and UI separately.... | Human-Computer Interaction |
What field is the article from? | Title: Quilt-LLaVA: Visual Instruction Tuning by Extracting Localized Narratives from Open-Source Histopathology Videos
Abstract: The gigapixel scale of whole slide images (WSIs) poses a challenge for
histopathology multi-modal chatbots, requiring a global WSI analysis for
diagnosis, compounding evidence from different... | Computer Vision |
What field is the article from? | Title: An Empirical Study of Benchmarking Chinese Aspect Sentiment Quad Prediction
Abstract: Aspect sentiment quad prediction (ASQP) is a critical subtask of aspect-level
sentiment analysis. Current ASQP datasets are characterized by their small size
and low quadruple density, which hinders technical development. To ex... | Computational Linguistics |
What field is the article from? | Title: Alignment is not sufficient to prevent large language models from generating harmful information: A psychoanalytic perspective
Abstract: Large Language Models (LLMs) are central to a multitude of applications but
struggle with significant risks, notably in generating harmful content and
biases. Drawing an analog... | Computational Linguistics |
What field is the article from? | Title: I-PHYRE: Interactive Physical Reasoning
Abstract: Current evaluation protocols predominantly assess physical reasoning in
stationary scenes, creating a gap in evaluating agents' abilities to interact
with dynamic events. While contemporary methods allow agents to modify initial
scene configurations and observe c... | Artificial Intelligence |
What field is the article from? | Title: Going beyond persistent homology using persistent homology
Abstract: Representational limits of message-passing graph neural networks (MP-GNNs),
e.g., in terms of the Weisfeiler-Leman (WL) test for isomorphism, are well
understood. Augmenting these graph models with topological features via
persistent homology (... | Machine Learning |
What field is the article from? | Title: Evaluating Neighbor Explainability for Graph Neural Networks
Abstract: Explainability in Graph Neural Networks (GNNs) is a new field growing in the
last few years. In this publication we address the problem of determining how
important is each neighbor for the GNN when classifying a node and how to
measure the p... | Machine Learning |
What field is the article from? | Title: Grounding Foundation Models through Federated Transfer Learning: A General Framework
Abstract: Foundation Models (FMs) such as GPT-4 encoded with vast knowledge and
powerful emergent abilities have achieved remarkable success in various natural
language processing and computer vision tasks. Grounding FMs by adap... | Machine Learning |
What field is the article from? | Title: Knowledge-Based Support for Adhesive Selection: Will it Stick?
Abstract: As the popularity of adhesive joints in industry increases, so does the need
for tools to support the process of selecting a suitable adhesive. While some
such tools already exist, they are either too limited in scope, or offer too
little f... | Artificial Intelligence |
What field is the article from? | Title: Straggler-resilient Federated Learning: Tackling Computation Heterogeneity with Layer-wise Partial Model Training in Mobile Edge Network
Abstract: Federated Learning (FL) enables many resource-limited devices to train a
model collaboratively without data sharing. However, many existing works focus
on model-homog... | Machine Learning |
What field is the article from? | Title: Inspecting Explainability of Transformer Models with Additional Statistical Information
Abstract: Transformer becomes more popular in the vision domain in recent years so
there is a need for finding an effective way to interpret the Transformer model
by visualizing it. In recent work, Chefer et al. can visualize... | Computer Vision |
What field is the article from? | Title: You don't need a personality test to know these models are unreliable: Assessing the Reliability of Large Language Models on Psychometric Instruments
Abstract: The versatility of Large Language Models (LLMs) on natural language
understanding tasks has made them popular for research in social sciences. In
particu... | Computational Linguistics |
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