node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
values |
|---|---|---|---|---|
22,978 | 30 | Title: Speculative Decoding with Big Little Decoder
Abstract: The recent emergence of Large Language Models based on the Transformer architecture has enabled dramatic advancements in the field of Natural Language Processing. However, these models have long inference latency, which limits their deployment, and which mak... | [
33953,
9381,
528,
1141,
31256,
20411,
40413
] | Test |
22,979 | 26 | Title: Influence maximization on temporal networks: a review
Abstract: Influence maximization (IM) is an important topic in network science where a small seed set is chosen to maximize the spread of influence on a network. Recently, this problem has attracted attention on temporal networks where the network structure c... | [
28781
] | Validation |
22,980 | 16 | Title: Introducing Construct Theory as a Standard Methodology for Inclusive AI Models
Abstract: Construct theory in social psychology, developed by George Kelly are mental constructs to predict and anticipate events. Constructs are how humans interpret, curate, predict and validate data; information. AI today is biased... | [] | Train |
22,981 | 2 | Title: External Behavior of a Logic Program and Verification of Refactoring
Abstract:
Refactoring is modifying a program without changing its external behavior. In this paper, we make the concept of external behavior precise for a simple answer set programming language. Then we describe a proof assistant for the task... | [] | Validation |
22,982 | 30 | Title: Pseudo-Label Training and Model Inertia in Neural Machine Translation
Abstract: Like many other machine learning applications, neural machine translation (NMT) benefits from over-parameterized deep neural models. However, these models have been observed to be brittle: NMT model predictions are sensitive to small... | [] | Train |
22,983 | 30 | Title: Accelerating Transducers through Adjacent Token Merging
Abstract: Recent end-to-end automatic speech recognition (ASR) systems often utilize a Transformer-based acoustic encoder that generates embedding at a high frame rate. However, this design is inefficient, particularly for long speech signals due to the qua... | [] | Validation |
22,984 | 30 | Title: Personalised Language Modelling of Screen Characters Using Rich Metadata Annotations
Abstract: Language models that are sensitive to external context can more effectively capture the speaking patterns of individuals with specific characteristics or in particular environments. However, obtaining and leveraging su... | [
28674,
18677
] | Train |
22,985 | 16 | Title: Large-scale Weakly Supervised Learning for Road Extraction from Satellite Imagery
Abstract: Automatic road extraction from satellite imagery using deep learning is a viable alternative to traditional manual mapping. Therefore it has received considerable attention recently. However, most of the existing methods ... | [] | Test |
22,986 | 8 | Title: Traffic Steering for 5G Multi-RAT Deployments using Deep Reinforcement Learning
Abstract: In 5G non-standalone mode, traffic steering is a critical technique to take full advantage of 5G new radio while optimizing dual connectivity of 5G and LTE networks in multiple radio access technology (RAT). An intelligent ... | [
41489,
5938,
25729
] | Test |
22,987 | 16 | Title: Domain Expansion of Image Generators
Abstract: Can one inject new concepts into an already trained generative model, while respecting its existing structure and knowledge? We propose a new task - domain expansion - to address this. Given a pretrained generator and novel (but related) domains, we expand the gener... | [
17200,
44177,
1082
] | Train |
22,988 | 26 | Title: Community detection in large hypergraphs
Abstract: Hypergraphs, describing networks where interactions take place among any number of units, are a natural tool to model many real-world social and biological systems. Here, we propose a principled framework to model the organization of higher-order data. Our appro... | [] | Validation |
22,989 | 28 | Title: Comparing Poisson and Gaussian channels
Abstract: Consider a pair of input distributions which after passing through a Poisson channel become ϵ-close in total variation. We show that they must necessarily then be ϵ0.5+o(1)-close after passing through a Gaussian channel as well. In the opposite direction, we show... | [] | Train |
22,990 | 38 | Title: TOBY: A Tool for Exploring Data in Academic Survey Papers
Abstract: This paper describes TOBY, a visualization tool that helps a user explore the contents of an academic survey paper. The visualization consists of four components: a hierarchical view of taxonomic data in the survey, a document similarity view in... | [] | Train |
22,991 | 9 | Title: A Note on Hardness of Computing Recursive Teaching Dimension
Abstract: nan | [] | Train |
22,992 | 4 | Title: Prophet: Conflict-Free Sharding Blockchain via Byzantine-Tolerant Deterministic Ordering
Abstract: Sharding scales throughput by splitting blockchain nodes into parallel groups. However, different shards’ independent and random scheduling for cross-shard transactions results in numerous conflicts and aborts, sin... | [
46152
] | Train |
22,993 | 30 | Title: Look-back Decoding for Open-Ended Text Generation
Abstract: Given a prefix (context), open-ended generation aims to decode texts that are coherent, which don't abruptly drift from previous topics, and informative, which don't suffer from undesired repetitions. In this paper, we propose Look-back, an improved dec... | [] | Train |
22,994 | 10 | Title: Reasoning about Causality in Games
Abstract: nan | [
17896,
6347,
37623,
23183
] | Validation |
22,995 | 16 | Title: Degeneration-Tuning: Using Scrambled Grid shield Unwanted Concepts from Stable Diffusion
Abstract: Owing to the unrestricted nature of the content in the training data, large text-to-image diffusion models, such as Stable Diffusion (SD), are capable of generating images with potentially copyrighted or dangerous ... | [
20514,
31588,
44741,
15983,
45104,
41874,
34074
] | Train |
22,996 | 16 | Title: NAVI: Category-Agnostic Image Collections with High-Quality 3D Shape and Pose Annotations
Abstract: Recent advances in neural reconstruction enable high-quality 3D object reconstruction from casually captured image collections. Current techniques mostly analyze their progress on relatively simple image collectio... | [
19738,
19630
] | Train |
22,997 | 31 | Title: Manipulating Federated Recommender Systems: Poisoning with Synthetic Users and Its Countermeasures
Abstract: Federated Recommender Systems (FedRecs) are considered privacy-preserving techniques to collaboratively learn a recommendation model without sharing user data. Since all participants can directly influenc... | [
4473,
39124
] | Train |
22,998 | 30 | Title: Small Models are Valuable Plug-ins for Large Language Models
Abstract: Large language models (LLMs) such as GPT-3 and GPT-4 are powerful but their weights are often publicly unavailable and their immense sizes make the models difficult to be tuned with common hardware. As a result, effectively tuning these model... | [
38849,
7397,
4902,
6958,
23247,
41425,
31923,
7860,
38262,
3609,
634,
45310,
43327
] | Validation |
22,999 | 27 | Title: Formal Verification of Intersection Safety for Automated Driving
Abstract: We build on our recent work on formalization of responsibility-sensitive safety (RSS) and present the first formal framework that enables mathematical proofs of the safety of control strategies in intersection scenarios. Intersection scen... | [
37877
] | Train |
23,000 | 3 | Title: Data-Driven Dystopia: an uninterrupted breach of ethics
Abstract: This article discusses the risks and complexities associated with the exponential rise in data and the misuse of data by large corporations. The article presents instances of data breaches and data harvesting practices that violate user privacy. I... | [] | Train |
23,001 | 4 | Title: Developing and Building Ontologies in Cyber Security
Abstract: Cyber Security is one of the most arising disciplines in our modern society. We work on Cybersecurity domain and in this the topic we chose is Cyber Security Ontologies. In this we gather all latest and previous ontologies and compare them on the bas... | [] | Train |
23,002 | 30 | Title: Triggering Multi-Hop Reasoning for Question Answering in Language Models using Soft Prompts and Random Walks
Abstract: Despite readily memorizing world knowledge about entities, pre-trained language models (LMs) struggle to compose together two or more facts to perform multi-hop reasoning in question-answering t... | [] | Test |
23,003 | 25 | Title: Artistic Curve Steganography Carried by Musical Audio
Abstract: In this work, we create artistic closed loop curves that trace out images and 3D shapes, which we then hide in musical audio as a form of steganography. We use traveling salesperson art to create artistic plane loops to trace out image contours, and... | [] | Train |
23,004 | 6 | Title: Power-up! What Can Generative Models Do for Human Computation Workflows?
Abstract: We are amidst an explosion of artificial intelligence research, particularly around large language models (LLMs). These models have a range of applications across domains like medicine, finance, commonsense knowledge graphs, and c... | [] | Train |
23,005 | 34 | Title: Knapsack with Small Items in Near-Quadratic Time
Abstract: The Bounded Knapsack problem is one of the most fundamental NP-complete problems at the intersection of computer science, optimization, and operations research. A recent line of research worked towards understanding the complexity of pseudopolynomial-tim... | [
34880,
29380,
20197,
10441,
14314,
11568,
40024,
23227
] | Train |
23,006 | 16 | Title: Three Ways to Improve Verbo-visual Fusion for Dense 3D Visual Grounding
Abstract: 3D visual grounding is the task of localizing the object in a 3D scene which is referred by a description in natural language. With a wide range of applications ranging from autonomous indoor robotics to AR/VR, the task has recentl... | [] | Train |
23,007 | 24 | Title: The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter
Abstract: Large pre-trained transformers are show-stealer in modern-day deep learning, and it becomes crucial to comprehend the parsimonious patterns that exist within them as they grow in scale. With exploding parameter cou... | [
16960,
12851,
13525
] | Validation |
23,008 | 24 | Title: Restoration-Degradation Beyond Linear Diffusions: A Non-Asymptotic Analysis For DDIM-Type Samplers
Abstract: We develop a framework for non-asymptotic analysis of deterministic samplers used for diffusion generative modeling. Several recent works have analyzed stochastic samplers using tools like Girsanov's theo... | [
16536,
2586,
34819,
33518
] | Train |
23,009 | 20 | Title: CelticGraph: Drawing Graphs as Celtic Knots and Links
Abstract: Celtic knots are an ancient art form often attributed to Celtic cultures, used to decorate monuments and manuscripts, and to symbolise eternity and interconnectedness. This paper describes the framework CelticGraph to draw graphs as Celtic knots and... | [] | Train |
23,010 | 17 | Title: Technical Companion to Example-Based Procedural Modeling Using Graph Grammars
Abstract: This is a companion piece to my paper on"Example-Based Procedural Modeling Using Graph Grammars."This paper examines some of the theoretical issues in more detail. This paper discusses some more complex parts of the implement... | [] | Test |
23,011 | 27 | Title: A Unifying Variational Framework for Gaussian Process Motion Planning
Abstract: To control how a robot moves, motion planning algorithms must compute paths in high-dimensional state spaces while accounting for physical constraints related to motors and joints, generating smooth and stable motions, avoiding obsta... | [] | Train |
23,012 | 27 | Title: RotorPy: A Python-based Multirotor Simulator with Aerodynamics for Education and Research
Abstract: Simulators play a critical role in aerial robotics both in and out of the classroom. We present RotorPy, a simulation environment written entirely in Python intentionally designed to be a lightweight and accessibl... | [] | Test |
23,013 | 27 | Title: Natural Language Robot Programming: NLP integrated with autonomous robotic grasping
Abstract: In this paper, we present a grammar-based natural language framework for robot programming, specifically for pick-and-place tasks. Our approach uses a custom dictionary of action words, designed to store together words ... | [
22115
] | Train |
23,014 | 16 | Title: SparseNeRF: Distilling Depth Ranking for Few-shot Novel View Synthesis
Abstract: Neural Radiance Field (NeRF) significantly degrades when only a limited number of views are available. To complement the lack of 3D information, depth-based models, such as DSNeRF and MonoSDF, explicitly assume the availability of a... | [
26086,
29000,
37769,
44681,
10315,
19308,
23760,
21367,
28189
] | Test |
23,015 | 16 | Title: VS-TransGRU: A Novel Transformer-GRU-based Framework Enhanced by Visual-Semantic Fusion for Egocentric Action Anticipation
Abstract: Egocentric action anticipation is a challenging task that aims to make advanced predictions of future actions from current and historical observations in the first-person view. Mos... | [] | Train |
23,016 | 4 | Title: On the Impact of the Hardware Warm-Up Time on Deep Learning-Based RF Fingerprinting
Abstract: Deep learning-based RF fingerprinting offers great potential for improving the security robustness of various emerging wireless networks. Although much progress has been done in enhancing fingerprinting methods, the imp... | [
8458,
10159
] | Train |
23,017 | 16 | Title: Vanishing Point Estimation in Uncalibrated Images with Prior Gravity Direction
Abstract: We tackle the problem of estimating a Manhattan frame, i.e. three orthogonal vanishing points, and the unknown focal length of the camera, leveraging a prior vertical direction. The direction can come from an Inertial Measur... | [] | Train |
23,018 | 16 | Title: AZTR: Aerial Video Action Recognition with Auto Zoom and Temporal Reasoning
Abstract: We propose a novel approach for aerial video action recognition. Our method is designed for videos captured using UAVs and can run on edge or mobile devices. We present a learning-based approach that uses customized auto zoom t... | [
27794,
7476,
12357
] | Test |
23,019 | 28 | Title: Coded matrix computation with gradient coding
Abstract: Polynomial based approaches, such as the Mat-Dot and entangled polynomial codes (EPC) have been used extensively within coded matrix computations to obtain schemes with good recovery thresholds. However, these schemes are well-recognized to suffer from poor... | [] | Test |
23,020 | 24 | Title: Control-aware echo state networks (Ca-ESN) for the suppression of extreme events
Abstract: Extreme event are sudden large-amplitude changes in the state or observables of chaotic nonlinear systems, which characterize many scientific phenomena. Because of their violent nature, extreme events typically have advers... | [] | Train |
23,021 | 16 | Title: TF-ICON: Diffusion-Based Training-Free Cross-Domain Image Composition
Abstract: Text-driven diffusion models have exhibited impressive generative capabilities, enabling various image editing tasks. In this paper, we propose TF-ICON, a novel Training-Free Image COmpositioN framework that harnesses the power of te... | [
16103,
32587,
28532,
41146,
43867
] | Train |
23,022 | 16 | Title: Transfer Learning for Olfactory Object Detection
Abstract: We investigate the effect of style and category similarity in multiple datasets used for object detection pretraining. We find that including an additional stage of object-detection pretraining can increase the detection performance considerably. While o... | [] | Train |
23,023 | 38 | Title: PatentsView-Evaluation: Evaluation Datasets and Tools to Advance Research on Inventor Name Disambiguation
Abstract: We present PatentsView-Evaluation, a Python package that enables researchers to evaluate the performance of inventor name disambiguation systems such as PatentsView.org. The package includes benchm... | [] | Train |
23,024 | 35 | Title: LeaFTL: A Learning-Based Flash Translation Layer for Solid-State Drives
Abstract: In modern solid-state drives (SSDs), the indexing of flash pages is a critical component in their storage controllers. It not only affects the data access performance, but also determines the efficiency of the precious in-device DR... | [] | Train |
23,025 | 16 | Title: Boosting Adversarial Transferability by Block Shuffle and Rotation
Abstract: Adversarial examples mislead deep neural networks with imperceptible perturbations and have brought significant threats to deep learning. An important aspect is their transferability, which refers to their ability to deceive other model... | [
30440,
4877
] | Test |
23,026 | 16 | Title: Iterative Reweighted Least Squares Networks With Convergence Guarantees for Solving Inverse Imaging Problems
Abstract: In this work we present a novel optimization strategy for image reconstruction tasks under analysis-based image regularization, which promotes sparse and/or low-rank solutions in some learned tr... | [
15419
] | Train |
23,027 | 30 | Title: HOP, UNION, GENERATE: Explainable Multi-hop Reasoning without Rationale Supervision
Abstract: Explainable multi-hop question answering (QA) not only predicts answers but also identifies rationales, i. e. subsets of input sentences used to derive the answers. This problem has been extensively studied under the su... | [] | Validation |
23,028 | 30 | Title: Parameter-Efficient Fine-Tuning with Layer Pruning on Free-Text Sequence-to-Sequence Modeling
Abstract: The increasing size of language models raises great research interests in parameter-efficient fine-tuning such as LoRA that freezes the pre-trained model, and injects small-scale trainable parameters for multi... | [
977,
32635
] | Train |
23,029 | 24 | Title: Composable Function-preserving Expansions for Transformer Architectures
Abstract: Training state-of-the-art neural networks requires a high cost in terms of compute and time. Model scale is recognized to be a critical factor to achieve and improve the state-of-the-art. Increasing the scale of a neural network no... | [
21825,
37070,
29396,
39480,
43641
] | Validation |
23,030 | 30 | Title: Relational Extraction on Wikipedia Tables using Convolutional and Memory Networks
Abstract: Relation extraction (RE) is the task of extracting relations between entities in text. Most RE methods extract relations from free-form running text and leave out other rich data sources, such as tables. We explore RE fro... | [] | Train |
23,031 | 34 | Title: On Colorful Vertex and Edge Cover Problems
Abstract: nan | [] | Train |
23,032 | 3 | Title: Finding differences in perspectives between designers and engineers to develop trustworthy AI for autonomous cars
Abstract: In the context of designing and implementing ethical Artificial Intelligence (AI), varying perspectives exist regarding developing trustworthy AI for autonomous cars. This study sheds light... | [
38073
] | Train |
23,033 | 24 | Title: Efficient Dynamics Modeling in Interactive Environments with Koopman Theory
Abstract: The accurate modeling of dynamics in interactive environments is critical for successful long-range prediction. Such a capability could advance Reinforcement Learning (RL) and Planning algorithms, but achieving it is challengin... | [] | Validation |
23,034 | 30 | Title: Don’t Retrain, Just Rewrite: Countering Adversarial Perturbations by Rewriting Text
Abstract: Can language models transform inputs to protect text classifiers against adversarial attacks? In this work, we present ATINTER, a model that intercepts and learns to rewrite adversarial inputs to make them non-adversari... | [] | Test |
23,035 | 24 | Title: The cross-sectional stock return predictions via quantum neural network and tensor network
Abstract: In this paper we investigate the application of quantum and quantum-inspired machine learning algorithms to stock return predictions. Specifically, we evaluate performance of quantum neural network, an algorithm ... | [] | Train |
23,036 | 30 | Title: Seen to Unseen: Exploring Compositional Generalization of Multi-Attribute Controllable Dialogue Generation
Abstract: Existing controllable dialogue generation work focuses on the single-attribute control and lacks generalization capability to out-of-distribution multiple attribute combinations. In this paper, we... | [] | Train |
23,037 | 24 | Title: MLOps: A Review
Abstract: Recently, Machine Learning (ML) has become a widely accepted method for significant progress that is rapidly evolving. Since it employs computational methods to teach machines and produce acceptable answers. The significance of the Machine Learning Operations (MLOps) methods, which can ... | [] | Test |
23,038 | 4 | Title: RETINA: Distributed and Secure Trust Management for Smart Grid Applications and Energy Trading
Abstract: The rapid adoption of smart grids demands robust security and efficiency measures due to their critical role in delivering electricity and their potential for customer-oriented benefits. This paper presents a... | [] | Validation |
23,039 | 18 | Title: An Exploration of the Impact of Mapping Style and Device Roadmap on Simulated ReRAM Architectures for Neuromorphic Computing
Abstract: This paper investigates the relationship between mapping style and device roadmap in Resistive Random Access Memory (ReRAM) architectures for neuromorphic computing. The study le... | [] | Train |
23,040 | 2 | Title: Dependency Tuples for Almost-Sure Innermost Termination of Probabilistic Term Rewriting (Short WST Version)
Abstract: Dependency pairs are one of the most powerful techniques to analyze termination of term rewrite systems (TRSs) automatically. We adapt the dependency pair framework to the probabilistic setting i... | [
28835
] | Test |
23,041 | 8 | Title: Flowsim: A Modular Simulation Platform for Microscopic Behavior Analysis of City-Scale Connected Autonomous Vehicles
Abstract: As connected autonomous vehicles (CAVs) become increasingly prevalent, there is a growing need for simulation platforms that can accurately evaluate CAV behavior in large-scale environme... | [] | Validation |
23,042 | 30 | Title: SkillQG: Learning to Generate Question for Reading Comprehension Assessment
Abstract: We present $\textbf{$\texttt{SkillQG}$}$: a question generation framework with controllable comprehension types for assessing and improving machine reading comprehension models. Existing question generation systems widely diffe... | [] | Train |
23,043 | 25 | Title: Speaker Recognition Using Isomorphic Graph Attention Network Based Pooling on Self-Supervised Representation
Abstract: The emergence of self-supervised representation (i.e., wav2vec 2.0) allows speaker-recognition approaches to process spoken signals through foundation models built on speech data. Nevertheless, ... | [] | Train |
23,044 | 17 | Title: Massive Uniform Mesh Decimation via a Fast Intrinsic Delaunay Triangulation
Abstract: Triangular meshes are still today the data structure at the main foundations of many computer graphics applications. With the increasing demand in content variety, a lot of effort has been and is being put into developing new a... | [] | Test |
23,045 | 25 | Title: ASTER: Automatic Speech Recognition System Accessibility Testing for Stutterers
Abstract: The popularity of automatic speech recognition (ASR) systems nowadays leads to an increasing need for improving their accessibility. Handling stuttering speech is an important feature for accessible ASR systems. To improve ... | [] | Train |
23,046 | 24 | Title: Sequential Linearithmic Time Optimal Unimodal Fitting When Minimizing Univariate Linear Losses
Abstract: This paper focuses on optimal unimodal transformation of the score outputs of a univariate learning model under linear loss functions. We demonstrate that the optimal mapping between score values and the targ... | [] | Test |
23,047 | 24 | Title: Data-driven Nonlinear Parametric Model Order Reduction Framework using Deep Hierarchical Variational Autoencoder
Abstract: A data-driven parametric model order reduction (MOR) method using a deep artificial neural network is proposed. The present network, which is the least-squares hierarchical variational autoe... | [
27950
] | Test |
23,048 | 24 | Title: MD-Manifold: A Medical-Distance-Based Representation Learning Approach for Medical Concept and Patient Representation
Abstract: Effectively representing medical concepts and patients is important for healthcare analytical applications. Representing medical concepts for healthcare analytical tasks requires incorp... | [] | Train |
23,049 | 24 | Title: Learning Sample Difficulty from Pre-trained Models for Reliable Prediction
Abstract: Large-scale pre-trained models have achieved remarkable success in a variety of scenarios and applications, but how to leverage them to improve the prediction reliability of downstream models is undesirably under-explored. Moreo... | [
28099
] | Train |
23,050 | 24 | Title: A Communication-Efficient Adaptive Algorithm for Federated Learning under Cumulative Regret
Abstract: We consider the problem of online stochastic optimization in a distributed setting with $M$ clients connected through a central server. We develop a distributed online learning algorithm that achieves order-opti... | [] | Test |
23,051 | 16 | Title: Towards Visual Foundational Models of Physical Scenes
Abstract: We describe a first step towards learning general-purpose visual representations of physical scenes using only image prediction as a training criterion. To do so, we first define"physical scene"and show that, even though different agents may maintai... | [
19781,
30566,
34074,
38959,
32980,
12665,
12474,
6270
] | Train |
23,052 | 27 | Title: UAV Tracking with Solid-State Lidars: Dynamic Multi-Frequency Scan Integration
Abstract: With the increasing use of drones across various industries, the navigation and tracking of these unmanned aerial vehicles (UAVs) in challenging environments (such as GNSS-denied environments) have become critical issues. In... | [
30785
] | Train |
23,053 | 10 | Title: Symbolic LTLf Best-Effort Synthesis
Abstract: We consider an agent acting to fulfil tasks in a nondeterministic environment. When a strategy that fulfills the task regardless of how the environment acts does not exist, the agent should at least avoid adopting strategies that prevent from fulfilling its task. Bes... | [] | Train |
23,054 | 28 | Title: A New Family of Perfect Polyphase Sequences with Low Cross-Correlation
Abstract: Spread spectrum multiple access systems demand minimum possible cross-correlation between the sequences within a set of sequences having good auto-correlation properties. Through a connection between generalised Frank sequences and ... | [] | Test |
23,055 | 16 | Title: HNeRV: A Hybrid Neural Representation for Videos
Abstract: Implicit neural representations store videos as neural networks and have performed well for various vision tasks such as video compression and denoising. With frame index or positional index as input, implicit representations (NeRV, E-NeRV, etc.) reconst... | [
9258,
11283,
29718
] | Test |
23,056 | 24 | Title: On Minimizing the Impact of Dataset Shifts on Actionable Explanations
Abstract: The Right to Explanation is an important regulatory principle that allows individuals to request actionable explanations for algorithmic decisions. However, several technical challenges arise when providing such actionable explanatio... | [] | Train |
23,057 | 23 | Title: Smaller, Faster, Greener: Compressing Pre-trained Code Models via Surrogate-Assisted Optimization
Abstract: Large pre-trained models of code have been adopted to tackle many software engineering tasks and achieved excellent results. However, their large model size and expensive energy consumption prevent them fr... | [] | Train |
23,058 | 16 | Title: Robust Point Cloud Processing through Positional Embedding
Abstract: End-to-end trained per-point embeddings are an essential ingredient of any state-of-the-art 3D point cloud processing such as detection or alignment. Methods like PointNet, or the more recent point cloud transformer -- and its variants -- all e... | [] | Train |
23,059 | 4 | Title: Account Verification on Social Media: User Perceptions and Paid Enrollment
Abstract: We investigate how users perceive social media account verification, how those perceptions compare to platform practices, and what happens when a gap emerges. We use recent changes in Twitter's verification process as a natural ... | [] | Test |
23,060 | 10 | Title: A comparative study of statistical and machine learning models on near-real-time daily emissions prediction
Abstract: The rapid ascent in carbon dioxide emissions is a major cause of global warming and climate change, which pose a huge threat to human survival and impose far-reaching influence on the global ecos... | [] | Train |
23,061 | 16 | Title: Bridging Vision and Language Encoders: Parameter-Efficient Tuning for Referring Image Segmentation
Abstract: Parameter Efficient Tuning (PET) has gained attention for reducing the number of parameters while maintaining performance and providing better hardware resource savings, but few studies investigate dense ... | [
20175
] | Train |
23,062 | 24 | Title: On the Learning Dynamics of Attention Networks
Abstract: Attention models are typically learned by optimizing one of three standard loss functions that are variously called -- soft attention, hard attention, and latent variable marginal likelihood (LVML) attention. All three paradigms are motivated by the same g... | [] | Train |
23,063 | 7 | Title: A variational approach to effective models for inelastic systems
Abstract: Given a set of inelastic material models, a microstructure, a macroscopic structural geometry, and a set of boundary conditions, one can in principle always solve the governing equations to determine the system's mechanical response. Howe... | [] | Train |
23,064 | 4 | Title: SoK: The MITRE ATT&CK Framework in Research and Practice
Abstract: The MITRE ATT&CK framework, a comprehensive knowledge base of adversary tactics and techniques, has been widely adopted by the cybersecurity industry as well as by academic researchers. Its broad range of industry applications include threat inte... | [] | Train |
23,065 | 25 | Title: HappyQuokka System for ICASSP 2023 Auditory EEG Challenge
Abstract: This report describes our submission to Task 2 of the Auditory EEG Decoding Challenge at ICASSP 2023 Signal Processing Grand Challenge (SPGC). Task 2 is a regression problem that focuses on reconstructing a speech envelope from an EEG signal. Fo... | [] | Train |
23,066 | 31 | Title: Starting Conversations with Search Engines - Interfaces that Elicit Natural Language Queries
Abstract: Search systems on the Web rely on user input to generate relevant results. Since early information retrieval systems, users are trained to issue keyword searches and adapt to the language of the system. Recent ... | [] | Test |
23,067 | 16 | Title: Vision Language Pre-training by Contrastive Learning with Cross-Modal Similarity Regulation
Abstract: In this paper, we reconsider the problem of (partial) false negative samples from the Mutual Information (MI) Maximization perspective, the traditional contrastive loss (like InfoNCE loss) will equally push away... | [] | Train |
23,068 | 4 | Title: Towards Runtime Customizable Trusted Execution Environment on FPGA-SoC
Abstract: Processing sensitive data and deploying well-designed Intellectual Property (IP) cores on remote Field Programmable Gate Array (FPGA) are prone to private data leakage and IP theft. One effective solution is constructing Trusted Exe... | [] | Validation |
23,069 | 16 | Title: Is context all you need? Scaling Neural Sign Language Translation to Large Domains of Discourse
Abstract: Sign Language Translation (SLT) is a challenging task that aims to generate spoken language sentences from sign language videos, both of which have different grammar and word/gloss order. From a Neural Machi... | [] | Train |
23,070 | 25 | Title: A Voice Disease Detection Method Based on MFCCs and Shallow CNN
Abstract: The incidence rate of voice diseases is increasing year by year. The use of software for remote diagnosis is a technical development trend and has important practical value. Among voice diseases, common diseases that cause hoarseness inclu... | [] | Validation |
23,071 | 16 | Title: Video alignment using unsupervised learning of local and global features
Abstract: In this paper, we tackle the problem of video alignment, the process of matching the frames of a pair of videos containing similar actions. The main challenge in video alignment is that accurate correspondence should be establishe... | [
29900
] | Train |
23,072 | 30 | Title: Knowledge-augmented Frame Semantic Parsing with Hybrid Prompt-tuning
Abstract: Frame semantics-based approaches have been widely used in semantic parsing tasks and have become mainstream. It remains challenging to disambiguate frame representations evoked by target lexical units under different contexts. Pre-tra... | [] | Test |
23,073 | 16 | Title: Early Detection of Red Palm Weevil Infestations using Deep Learning Classification of Acoustic Signals
Abstract: nan | [] | Test |
23,074 | 24 | Title: A Unified Framework for Soft Threshold Pruning
Abstract: Soft threshold pruning is among the cutting-edge pruning methods with state-of-the-art performance. However, previous methods either perform aimless searching on the threshold scheduler or simply set the threshold trainable, lacking theoretical explanation... | [
34035
] | Train |
23,075 | 30 | Title: Evaluating Factual Consistency of Texts with Semantic Role Labeling
Abstract: Automated evaluation of text generation systems has recently seen increasing attention, particularly checking whether generated text stays truthful to input sources.Existing methods frequently rely on an evaluation using task-specific ... | [
39451
] | Train |
23,076 | 24 | Title: Reinforcement Learning-Driven Linker Design via Fast Attention-based Point Cloud Alignment
Abstract: Proteolysis-Targeting Chimeras (PROTACs) represent a novel class of small molecules which are designed to act as a bridge between an E3 ligase and a disease-relevant protein, thereby promoting its subsequent degr... | [] | Train |
23,077 | 24 | Title: PredictChain: Empowering Collaboration and Data Accessibility for AI in a Decentralized Blockchain-based Marketplace
Abstract: Limited access to computing resources and training data poses significant challenges for individuals and groups aiming to train and utilize predictive machine learning models. Although n... | [] | Validation |
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