node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
values |
|---|---|---|---|---|
24,878 | 8 | Title: Virtual Network Embedding without Explicit Virtual Network Specification
Abstract: Network virtualization enables Internet service providers to run multiple heterogeneous and dedicated network architectures for different customers on a shared substrate. In existing works on virtual network embedding (VNE), each ... | [] | Train |
24,879 | 31 | Title: Bootstrapping Contrastive Learning Enhanced Music Cold-Start Matching
Abstract: We study a particular matching task we call Music Cold-Start Matching. In short, given a cold-start song request, we expect to retrieve songs with similar audiences and then fastly push the cold-start song to the audiences of the ret... | [] | Train |
24,880 | 24 | Title: Ahead-of-Time P-Tuning
Abstract: In this paper, we propose Ahead-of-Time (AoT) P-Tuning, a novel parameter-efficient fine-tuning method for pre-trained Language Models (LMs) that adds input-dependent bias before each Transformer layer. We evaluate AoT P-Tuning on GLUE and SuperGLUE benchmarking datasets using Ro... | [] | Train |
24,881 | 24 | Title: Training Large Scale Polynomial CNNs for E2E Inference over Homomorphic Encryption
Abstract: Training large-scale CNNs that during inference can be run under Homomorphic Encryption (HE) is challenging due to the need to use only polynomial operations. This limits HE-based solutions adoption. We address this chal... | [
29873,
45652
] | Test |
24,882 | 27 | Title: Asynchronous Spatial Allocation Protocol for Trajectory Planning of Heterogeneous Multi-Agent Systems
Abstract: To plan the trajectories of a large and heterogeneous swarm, sequential or synchronous distributed methods usually become intractable, due to the lack of global connectivity and clock synchronization, ... | [] | Validation |
24,883 | 24 | Title: Learning from Multiple Sources for Data-to-Text and Text-to-Data
Abstract: Data-to-text (D2T) and text-to-data (T2D) are dual tasks that convert structured data, such as graphs or tables into fluent text, and vice versa. These tasks are usually handled separately and use corpora extracted from a single source. C... | [] | Train |
24,884 | 18 | Title: Roadmap for Unconventional Computing with Nanotechnology
Abstract: In the Beyond Moore Law era, with increasing edge intelligence, domain-specific computing embracing unconventional approaches will become increasingly prevalent. At the same time, the adoption of a wide variety of nanotechnologies will offer bene... | [
22952,
21333
] | Train |
24,885 | 30 | Title: RoPDA: Robust Prompt-based Data Augmentation for Low-Resource Named Entity Recognition
Abstract: Data augmentation has been widely used in low-resource NER tasks to tackle the problem of data sparsity. However, previous data augmentation methods have the disadvantages of disrupted syntactic structures, token-lab... | [] | Train |
24,886 | 30 | Title: How User Language Affects Conflict Fatality Estimates in ChatGPT
Abstract: OpenAI's ChatGPT language model has gained popularity as a powerful tool for complex problem-solving and information retrieval. However, concerns arise about the reproduction of biases present in the language-specific training data. In th... | [
17920,
38849,
40152,
39295
] | Train |
24,887 | 16 | Title: Scaling Open-Vocabulary Object Detection
Abstract: Open-vocabulary object detection has benefited greatly from pretrained vision-language models, but is still limited by the amount of available detection training data. While detection training data can be expanded by using Web image-text pairs as weak supervisio... | [
35,
37070,
27054,
16341,
25754
] | Validation |
24,888 | 28 | Title: Hybrid Successive Interference Cancellation and Power Adaptation: a Win-Win Strategy for Robust Uplink NOMA Transmission
Abstract: The aim of this paper is to reveal the importance of hybrid successive interference cancellation (SIC) and power adaptation (PA) for improving transmission robustness of uplink non-o... | [
32111
] | Validation |
24,889 | 16 | Title: STEERER: Resolving Scale Variations for Counting and Localization via Selective Inheritance Learning
Abstract: Scale variation is a deep-rooted problem in object counting, which has not been effectively addressed by existing scale-aware algorithms. An important factor is that they typically involve cooperative l... | [] | Train |
24,890 | 16 | Title: Multimodal Parameter-Efficient Few-Shot Class Incremental Learning
Abstract: Few-Shot Class Incremental Learning (FSCIL) is a challenging continual learning task, where limited training examples are available during several learning sessions. To succeed in this task, it is necessary to avoid over-fitting new cla... | [
13442,
39863
] | Test |
24,891 | 16 | Title: Advancing Incremental Few-shot Semantic Segmentation via Semantic-guided Relation Alignment and Adaptation
Abstract: Incremental few-shot semantic segmentation (IFSS) aims to incrementally extend a semantic segmentation model to novel classes according to only a few pixel-level annotated data, while preserving i... | [
7175
] | Test |
24,892 | 16 | Title: Efficient Transformer-based 3D Object Detection with Dynamic Token Halting
Abstract: Balancing efficiency and accuracy is a long-standing problem for deploying deep learning models. The trade-off is even more important for real-time safety-critical systems like autonomous vehicles. In this paper, we propose an e... | [
14601,
34804
] | Validation |
24,893 | 6 | Title: Influences of Displaying Permission-related Information on Web Single Sign-On Login Decisions
Abstract: Web users are increasingly presented with multiple login options, including password-based login and common web single sign-on (SSO) login options such as"Login with Google"and"Login with Facebook". There has ... | [] | Validation |
24,894 | 16 | Title: A Large-scale Study of Spatiotemporal Representation Learning with a New Benchmark on Action Recognition
Abstract: The goal of building a benchmark (suite of datasets) is to provide a unified protocol for fair evaluation and thus facilitate the evolution of a specific area. Nonetheless, we point out that existin... | [
8854
] | Train |
24,895 | 26 | Title: Decoding the Popularity of TV Series: A Network Analysis Perspective
Abstract: In this paper, we analyze the character networks extracted from three popular television series and explore the relationship between a TV show episode's character network metrics and its review from IMDB. Character networks are graphs... | [] | Test |
24,896 | 25 | Title: A Few-Shot Approach to Dysarthric Speech Intelligibility Level Classification Using Transformers
Abstract: Dysarthria is a speech disorder that hinders communication due to difficulties in articulating words. Detection of dysarthria is important for several reasons as it can be used to develop a treatment plan a... | [] | Validation |
24,897 | 24 | Title: An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects
Abstract: We propose a new causal inference framework to learn causal effects from multiple, decentralized data sources in a federated setting. We introduce an adaptive transfer algorithm that learns the similarities among the data... | [
24080,
891,
33148
] | Train |
24,898 | 16 | Title: Pedestrain detection for low-light vision proposal
Abstract: The demand for pedestrian detection has created a challenging problem for various visual tasks such as image fusion. As infrared images can capture thermal radiation information, image fusion between infrared and visible images could significantly impr... | [] | Test |
24,899 | 25 | Title: ZeroPrompt: Streaming Acoustic Encoders are Zero-Shot Masked LMs
Abstract: In this paper, we present ZeroPrompt (Figure 1-(a)) and the corresponding Prompt-and-Refine strategy (Figure 3), two simple but effective \textbf{training-free} methods to decrease the Token Display Time (TDT) of streaming ASR models \tex... | [] | Validation |
24,900 | 37 | Title: Semi-Oblivious Chase Termination for Linear Existential Rules: An Experimental Study
Abstract: The chase procedure is a fundamental algorithmic tool in databases that allows us to reason with constraints, such as existential rules, with a plethora of applications. It takes as input a database and a set of constr... | [] | Train |
24,901 | 30 | Title: C3: Zero-shot Text-to-SQL with ChatGPT
Abstract: This paper proposes a ChatGPT-based zero-shot Text-to-SQL method, dubbed C3, which achieves 82.3\% in terms of execution accuracy on the holdout test set of Spider and becomes the state-of-the-art zero-shot Text-to-SQL method on the Spider Challenge. C3 consists o... | [
36494,
1326,
19250,
9143,
26393
] | Train |
24,902 | 16 | Title: RIGID: Recurrent GAN Inversion and Editing of Real Face Videos
Abstract: GAN inversion is indispensable for applying the powerful editability of GAN to real images. However, existing methods invert video frames individually often leading to undesired inconsistent results over time. In this paper, we propose a un... | [] | Train |
24,903 | 6 | Title: Implementation of communication media around a mixed reality experience with HoloLens headset, as part of a digitalization of a nutrition workshop
Abstract: The release of Microsoft's HoloLens headset addresses new types of issues that would have been difficult to design without such a hardware. This semi-transp... | [] | Validation |
24,904 | 24 | Title: Multilevel Diffusion: Infinite Dimensional Score-Based Diffusion Models for Image Generation
Abstract: Score-based diffusion models (SBDM) have recently emerged as state-of-the-art approaches for image generation. Existing SBDMs are typically formulated in a finite-dimensional setting, where images are considere... | [
10872,
219,
20004
] | Train |
24,905 | 16 | Title: NeuManifold: Neural Watertight Manifold Reconstruction with Efficient and High-Quality Rendering Support
Abstract: We present a method for generating high-quality watertight manifold meshes from multi-view input images. Existing volumetric rendering methods are robust in optimization but tend to generate noisy m... | [] | Validation |
24,906 | 27 | Title: Advance Simulation Method for Wheel-Terrain Interactions of Space Rovers: A Case Study on the UAE Rashid Rover
Abstract: A thorough analysis of wheel-terrain interaction is critical to ensure the safe and efficient operation of space rovers on extraterrestrial surfaces like the Moon or Mars. This paper presents ... | [] | Train |
24,907 | 16 | Title: Self-supervised Learning of Event-guided Video Frame Interpolation for Rolling Shutter Frames
Abstract: This paper makes the first attempt to tackle the challenging task of recovering arbitrary frame rate latent global shutter (GS) frames from two consecutive rolling shutter (RS) frames, guided by the novel even... | [] | Train |
24,908 | 24 | Title: Restore Translation Using Equivariant Neural Networks
Abstract: Invariance to spatial transformations such as translations and rotations is a desirable property and a basic design principle for classification neural networks. However, the commonly used convolutional neural networks (CNNs) are actually very sensi... | [] | Test |
24,909 | 2 | Title: Effective Auxiliary Variables via Structured Reencoding
Abstract: Extended resolution shows that auxiliary variables are very powerful in theory. However, attempts to exploit this potential in practice have had limited success. One reasonably effective method in this regard is bounded variable addition (BVA), wh... | [
1641
] | Train |
24,910 | 34 | Title: Engineering Rank/Select Data Structures for Big-Alphabet Strings
Abstract: Big-alphabet strings are common in several scenarios such as information retrieval and natural-language processing. The efficient storage and processing of such strings usually introduces several challenges that are not witnessed in small... | [] | Train |
24,911 | 30 | Title: Denoising Bottleneck with Mutual Information Maximization for Video Multimodal Fusion
Abstract: Video multimodal fusion aims to integrate multimodal signals in videos, such as visual, audio and text, to make a complementary prediction with multiple modalities contents.However, unlike other image-text multimodal ... | [] | Train |
24,912 | 11 | Title: Research on Multi-Agent Communication and Collaborative Decision-Making Based on Deep Reinforcement Learning
Abstract: In a multi-agent environment, In order to overcome and alleviate the non-stationarity of the multi-agent environment, the mainstream method is to adopt the framework of Centralized Training Dece... | [] | Train |
24,913 | 24 | Title: On Influence Functions, Classification Influence, Relative Influence, Memorization and Generalization
Abstract: Machine learning systems such as large scale recommendation systems or natural language processing systems are usually trained on billions of training points and are associated with hundreds of billion... | [] | Validation |
24,914 | 27 | Title: Whole-Body Dynamic Telelocomotion: A Step-to-Step Dynamics Approach to Human Walking Reference Generation
Abstract: Teleoperated humanoid robots hold significant potential as physical avatars for humans in hazardous and inaccessible environments, with the goal of channeling human intelligence and sensorimotor sk... | [
12588,
39038,
31423
] | Train |
24,915 | 24 | Title: Investigating Navigation Strategies in the Morris Water Maze through Deep Reinforcement Learning
Abstract: Navigation is a complex skill with a long history of research in animals and humans. In this work, we simulate the Morris Water Maze in 2D to train deep reinforcement learning agents. We perform automatic c... | [] | Train |
24,916 | 30 | Title: Sentence-Level Relation Extraction via Contrastive Learning with Descriptive Relation Prompts
Abstract: Sentence-level relation extraction aims to identify the relation between two entities for a given sentence. The existing works mostly focus on obtaining a better entity representation and adopting a multi-labe... | [
31215
] | Test |
24,917 | 30 | Title: Bridging Continuous and Discrete Spaces: Interpretable Sentence Representation Learning via Compositional Operations
Abstract: Traditional sentence embedding models encode sentences into vector representations to capture useful properties such as the semantic similarity between sentences. However, in addition to... | [] | Test |
24,918 | 39 | Title: New Dynamic Programming Algorithm for the Multiobjective Minimum Spanning Tree Problem
Abstract: The Multiobjective Minimum Spanning Tree (MO-MST) problem is a variant of the Minimum Spanning Tree problem, in which the costs associated with every edge of the input graph are vectors. In this paper, we design a ne... | [] | Train |
24,919 | 28 | Title: Joint Activity Detection and Channel Estimation in Massive Machine-Type Communications with Low-Resolution ADC
Abstract: In massive machine-type communications, data transmission is usually considered sporadic, and thus inherently has a sparse structure. This paper focuses on the joint activity detection (AD) an... | [] | Test |
24,920 | 16 | Title: Hi-ResNet: A High-Resolution Remote Sensing Network for Semantic Segmentation
Abstract: High-resolution remote sensing (HRS) semantic segmentation extracts key objects from high-resolution coverage areas. However, objects of the same category within HRS images generally show significant differences in scale and ... | [] | Train |
24,921 | 38 | Title: Cluster Analysis of Open Research Data and a Case for Replication Metadata
Abstract: Research data are often released upon journal publication to enable result verification and reproducibility. For that reason, research dissemination infrastructures typically support diverse datasets coming from numerous discipl... | [] | Validation |
24,922 | 16 | Title: ContraNeRF: Generalizable Neural Radiance Fields for Synthetic-to-real Novel View Synthesis via Contrastive Learning
Abstract: Although many recent works have investigated generalizable NeRF-based novel view synthesis for unseen scenes, they seldom consider the synthetic-to-real generalization, which is desired ... | [
33845
] | Validation |
24,923 | 4 | Title: Automated Black-Box Testing of Mass Assignment Vulnerabilities in RESTful APIs
Abstract: Mass assignment is one of the most prominent vulnerabilities in RESTful APIs that originates from a misconfiguration in common web frameworks. This allows attackers to exploit naming convention and automatic binding to craft... | [] | Validation |
24,924 | 10 | Title: The Joint Weighted Average (JWA) Operator
Abstract: Information aggregation is a vital tool for human and machine decision making, especially in the presence of noise and uncertainty. Traditionally, approaches to aggregation broadly diverge into two categories, those which attribute a worth or weight to informat... | [] | Train |
24,925 | 30 | Title: AttenWalker: Unsupervised Long-Document Question Answering via Attention-based Graph Walking
Abstract: Annotating long-document question answering (long-document QA) pairs is time-consuming and expensive. To alleviate the problem, it might be possible to generate long-document QA pairs via unsupervised question ... | [] | Validation |
24,926 | 23 | Title: A Study of Static Warning Cascading Tools (Experience Paper)
Abstract: Static analysis is widely used for software assurance. However, static analysis tools can report an overwhelming number of warnings, many of which are false positives. Applying static analysis to a new version, a large number of warnings can ... | [] | Validation |
24,927 | 30 | Title: Structured Sentiment Analysis as Transition-based Dependency Parsing
Abstract: Structured sentiment analysis (SSA) aims to automatically extract people's opinions from a text in natural language and adequately represent that information in a graph structure. One of the most accurate methods for performing SSA wa... | [] | Train |
24,928 | 24 | Title: Linked Data Science Powered by Knowledge Graphs
Abstract: In recent years, we have witnessed a growing interest in data science not only from academia but particularly from companies investing in data science platforms to analyze large amounts of data. In this process, a myriad of data science artifacts, such as... | [
41448
] | Train |
24,929 | 30 | Title: Deep Learning Mental Health Dialogue System
Abstract: Mental health counseling remains a major challenge in modern society due to cost, stigma, fear, and unavailability. We posit that generative artificial intelligence (AI) models designed for mental health counseling could help improve outcomes by lowering barr... | [
14122
] | Train |
24,930 | 17 | Title: Variational Direct Modeling: A framework towards integration of parametric modeling and direct modeling in CAD
Abstract: nan | [] | Train |
24,931 | 30 | Title: Sentiment Analysis in the Era of Large Language Models: A Reality Check
Abstract: Sentiment analysis (SA) has been a long-standing research area in natural language processing. It can offer rich insights into human sentiments and opinions and has thus seen considerable interest from both academia and industry. W... | [
13345,
1050,
13700,
33220,
35580,
15049,
8436,
31956,
44758,
31832,
12602,
35388,
27482,
8894,
21375
] | Validation |
24,932 | 16 | Title: STHG: Spatial-Temporal Heterogeneous Graph Learning for Advanced Audio-Visual Diarization
Abstract: This report introduces our novel method named STHG for the Audio-Visual Diarization task of the Ego4D Challenge 2023. Our key innovation is that we model all the speakers in a video using a single, unified heterog... | [] | Train |
24,933 | 16 | Title: Structured State Space Models for Multiple Instance Learning in Digital Pathology
Abstract: Multiple instance learning is an ideal mode of analysis for histopathology data, where vast whole slide images are typically annotated with a single global label. In such cases, a whole slide image is modelled as a collec... | [] | Train |
24,934 | 13 | Title: Self-Replication, Spontaneous Mutations, and Exponential Genetic Drift in Neural Cellular Automata
Abstract: This paper reports on patterns exhibiting self-replication with spontaneous, inheritable mutations and exponential genetic drift in Neural Cellular Automata. Despite the models not being explicitly traine... | [] | Train |
24,935 | 30 | Title: Cited Text Spans for Citation Text Generation
Abstract: Automatic related work generation must ground their outputs to the content of the cited papers to avoid non-factual hallucinations, but due to the length of scientific documents, existing abstractive approaches have conditioned only on the cited paper \text... | [] | Test |
24,936 | 8 | Title: Cross-Media Wireless Made Easier: Tuning Media Interfaces with Flexible Metasurfaces
Abstract: Emerging wireless IoT applications increasingly venture beyond over-the-air communication, such as deep-tissue networking for implantable sensors, air-water communication for ocean monitoring, and soil sensing. These a... | [] | Validation |
24,937 | 34 | Title: Improved Algorithms for Integer Complexity
Abstract: The integer complexity $f(n)$ of a positive integer $n$ is defined as the minimum number of 1's needed to represent $n$, using additions, multiplications and parentheses. We present two simple and faster algorithms for computing the integer complexity: 1) A ne... | [] | Train |
24,938 | 24 | Title: Dynamical Isometry based Rigorous Fair Neural Architecture Search
Abstract: Recently, the weight-sharing technique has significantly speeded up the training and evaluation procedure of neural architecture search. However, most existing weight-sharing strategies are solely based on experience or observation, whic... | [] | Train |
24,939 | 6 | Title: Agreeing and Disagreeing in Collaborative Knowledge Graph Construction: An Analysis of Wikidata
Abstract: In this work, we study disagreement in discussions around Wikidata, an online knowledge community that builds the data backend of Wikipedia. Discussions are important in collaborative work as they can increa... | [] | Train |
24,940 | 8 | Title: Routing over QUIC: Bringing transport innovations to routing protocols
Abstract: By combining the security features of TLS with the reliability of TCP, QUIC opens new possibilities for many applications. We demonstrate the benefits that QUIC brings for routing protocols. Current Internet routing protocols use in... | [] | Train |
24,941 | 30 | Title: Aspect-oriented Opinion Alignment Network for Aspect-Based Sentiment Classification
Abstract: Aspect-based sentiment classification is a crucial problem in fine-grained sentiment analysis, which aims to predict the sentiment polarity of the given aspect according to its context. Previous works have made remarkab... | [] | Train |
24,942 | 8 | Title: Heuristic Algorithms for RIS-assisted Wireless Networks: Exploring Heuristic-aided Machine Learning
Abstract: Reconfigurable intelligent surfaces (RISs) are a promising technology to enable smart radio environments. However, integrating RISs into wireless networks also leads to substantial complexity for network... | [] | Train |
24,943 | 4 | Title: Forward Pass: On the Security Implications of Email Forwarding Mechanism and Policy
Abstract: The critical role played by email has led to a range of extension protocols (e.g., SPF, DKIM, DMARC) designed to protect against the spoofing of email sender domains. These protocols are complex as is, but are further c... | [] | Train |
24,944 | 10 | Title: Lightweight Online Learning for Sets of Related Problems in Automated Reasoning
Abstract: We present Self-Driven Strategy Learning ($\textit{sdsl}$), a lightweight online learning methodology for automated reasoning tasks that involve solving a set of related problems. $\textit{sdsl}$ does not require offline tr... | [] | Validation |
24,945 | 28 | Title: Spatial Network Calculus and Performance Guarantees in Wireless Networks
Abstract: This work develops a novel approach towards performance guarantees for all links in arbitrarily large wireless networks. It introduces spatial regulation properties for stationary spatial point processes and develops the first ste... | [] | Train |
24,946 | 4 | Title: PUF Probe: A PUF-based Hardware Authentication Equipment for IEDs
Abstract: Intelligent Electronic Devices (IEDs) are vital components in modern electrical substations, collectively responsible for monitoring electrical parameters and performing protective functions. As a result, ensuring the integrity of IEDs i... | [] | Train |
24,947 | 8 | Title: A Novel Channel-Constrained Model for 6G Vehicular Networks with Traffic Spikes
Abstract: Mobile Edge Computing (MEC) holds excellent potential in Congestion Management (CM) of 6G vehicular networks. A reasonable schedule of MEC ensures a more reliable and efficient CM system. Unfortunately, existing parallel an... | [] | Test |
24,948 | 23 | Title: Self-planning Code Generation with Large Language Model
Abstract: Although large language models have demonstrated impressive ability in code generation, they are still struggling to address the complicated intent provided by humans. It is widely acknowledged that humans typically employ planning to decompose co... | [
5254,
40071,
17815,
42523,
3355,
8103,
10023,
40368,
22578,
10165,
20794,
12603,
14148,
33220,
15952,
16855,
35807,
7648,
7531
] | Train |
24,949 | 33 | Title: Separating Automatic Relations
Abstract: We study the separability problem for automatic relations (i.e., relations on finite words definable by synchronous automata) in terms of recognizable relations (i.e., finite unions of products of regular languages). This problem takes as input two automatic relations $R$... | [] | Validation |
24,950 | 28 | Title: Goppa-like AG codes from Ca, b curves and their behaviour under squaring their dual
Abstract: In this paper, we introduce a family of codes that can be used in a McEliece cryptosystem, called Goppa--like AG codes. These codes generalize classical Goppa codes and can be constructed from any curve of genus $\mathf... | [] | Train |
24,951 | 24 | Title: Federated Generative Learning with Foundation Models
Abstract: Existing federated learning solutions focus on transmitting features, parameters or gadients between clients and server, which suffer from serious low-efficiency and privacy-leakage problems. Thanks to the emerging foundation generative models, we pr... | [
10624,
549,
10056,
29354,
22540,
5932,
33166,
32110,
45104,
23188
] | Train |
24,952 | 16 | Title: Few-shot Image Classification based on Gradual Machine Learning
Abstract: Few-shot image classification aims to accurately classify unlabeled images using only a few labeled samples. The state-of-the-art solutions are built by deep learning, which focuses on designing increasingly complex deep backbones. Unfortu... | [] | Train |
24,953 | 6 | Title: Real-Time Recognition of In-Place Body Actions and Head Gestures using Only a Head-Mounted Display
Abstract: Body actions and head gestures are natural interfaces for interaction in virtual environments. Existing methods for in-place body action recognition often require hardware more than a head-mounted display... | [] | Test |
24,954 | 30 | Title: SemEval-2023 Task 12: Sentiment Analysis for African Languages (AfriSenti-SemEval)
Abstract: We present the first Africentric SemEval Shared task, Sentiment Analysis for African Languages (AfriSenti-SemEval) - The dataset is available at https://github.com/afrisenti-semeval/afrisent-semeval-2023. AfriSenti-SemEv... | [
25665,
19714,
7906,
20226,
8037,
26921,
17835,
41743,
25521,
20214
] | Train |
24,955 | 30 | Title: A Frustratingly Simple Decoding Method for Neural Text Generation
Abstract: We introduce a frustratingly simple, super efficient and surprisingly effective decoding method, which we call Frustratingly Simple Decoding (FSD), for neural text generation. The idea behind FSD is straightforward: we build an anti-LM b... | [] | Validation |
24,956 | 24 | Title: A Boosted Machine Learning Framework for the Improvement of Phase and Crystal Structure Prediction of High Entropy Alloys Using Thermodynamic and Configurational Parameters
Abstract: The reason behind the remarkable properties of High-Entropy Alloys (HEAs) is rooted in the diverse phases and the crystal structur... | [] | Validation |
24,957 | 30 | Title: Does Manipulating Tokenization Aid Cross-Lingual Transfer? A Study on POS Tagging for Non-Standardized Languages
Abstract: One of the challenges with finetuning pretrained language models (PLMs) is that their tokenizer is optimized for the language(s) it was pretrained on, but brittle when it comes to previously... | [
21574
] | Test |
24,958 | 24 | Title: Unsupervised physics-informed neural network in reaction-diffusion biology models (Ulcerative colitis and Crohn's disease cases) A preliminary study
Abstract: We propose to explore the potential of physics-informed neural networks (PINNs) in solving a class of partial differential equations (PDEs) used to model ... | [] | Train |
24,959 | 27 | Title: Overview Analysis of Recent Developments on Self-Driving Electric Vehicles
Abstract: This paper provides a comprehensive overview of recent advancements in autonomous electric vehicles (AEVs) within the specified region. It elaborates on the progress and comparative analysis of diverse subsystems, including ener... | [
14969
] | Validation |
24,960 | 16 | Title: Integrating Listwise Ranking into Pairwise-based Image-Text Retrieval
Abstract: Image-Text Retrieval (ITR) is essentially a ranking problem. Given a query caption, the goal is to rank candidate images by relevance, from large to small. The current ITR datasets are constructed in a pairwise manner. Image-text pai... | [] | Train |
24,961 | 24 | Title: Federated Learning in UAV-Enhanced Networks: Joint Coverage and Convergence Time Optimization
Abstract: Federated learning (FL) involves several devices that collaboratively train a shared model without transferring their local data. FL reduces the communication overhead, making it a promising learning method in... | [
20244
] | Test |
24,962 | 16 | Title: Novel Class Discovery for Long-tailed Recognition
Abstract: While the novel class discovery has recently made great progress, existing methods typically focus on improving algorithms on class-balanced benchmarks. However, in real-world recognition tasks, the class distributions of their corresponding datasets ar... | [
39008
] | Train |
24,963 | 16 | Title: Predicting Class Distribution Shift for Reliable Domain Adaptive Object Detection
Abstract: Unsupervised Domain Adaptive Object Detection (UDA-OD) uses unlabelled data to improve the reliability of robotic vision systems in open-world environments. Previous approaches to UDA-OD based on self-training have been e... | [] | Validation |
24,964 | 30 | Title: Parameter-Efficient Language Model Tuning with Active Learning in Low-Resource Settings
Abstract: Pre-trained language models (PLMs) have ignited a surge in demand for effective fine-tuning techniques, particularly in low-resource domains and languages. Active learning (AL), a set of algorithms designed to decre... | [
32249
] | Validation |
24,965 | 29 | Title: Characterizing the Performance of Emerging Deep Learning, Graph, and High Performance Computing Workloads Under Interference
Abstract: Throughput-oriented computing via co-running multiple applications in the same machine has been widely adopted to achieve high hardware utilization and energy saving on modern su... | [] | Train |
24,966 | 30 | Title: EaSyGuide : ESG Issue Identification Framework leveraging Abilities of Generative Large Language Models
Abstract: This paper presents our participation in the FinNLP-2023 shared task on multi-lingual environmental, social, and corporate governance issue identification (ML-ESG). The task's objective is to classif... | [
2347,
29375
] | Train |
24,967 | 8 | Title: Caching Contents with Varying Popularity using Restless Bandits
Abstract: We study content caching in a wireless network in which the users are connected through a base station that is equipped with a finite-capacity cache. We assume a fixed set of contents whose popularity varies with time. Users' requests for ... | [] | Test |
24,968 | 34 | Title: Fully Dynamic Exact Edge Connectivity in Sublinear Time
Abstract: Given a simple $n$-vertex, $m$-edge graph $G$ undergoing edge insertions and deletions, we give two new fully dynamic algorithms for exactly maintaining the edge connectivity of $G$ in $\tilde{O}(n)$ worst-case update time and $\tilde{O}(m^{1-1/16... | [] | Validation |
24,969 | 24 | Title: Stochastic Ratios Tracking Algorithm for Large Scale Machine Learning Problems
Abstract: Many machine learning applications and tasks rely on the stochastic gradient descent (SGD) algorithm and its variants. Effective step length selection is crucial for the success of these algorithms, which has motivated the d... | [
15816
] | Train |
24,970 | 34 | Title: Structural Parameterizations of the Biclique-Free Vertex Deletion Problem
Abstract: In this work, we study the Biclique-Free Vertex Deletion problem: Given a graph $G$ and integers $k$ and $i \le j$, find a set of at most $k$ vertices that intersects every (not necessarily induced) biclique $K_{i, j}$ in $G$. Th... | [] | Test |
24,971 | 13 | Title: Learning and evolution: factors influencing an effective combination
Abstract: The mutual relationship between evolution and learning is a controversial argument among the artificial intelligence and neuro-evolution communities. After more than three decades, there is still no common agreement on the matter. In ... | [] | Train |
24,972 | 25 | Title: UNSSOR: Unsupervised Neural Speech Separation by Leveraging Over-determined Training Mixtures
Abstract: In reverberant conditions with multiple concurrent speakers, each microphone acquires a mixture signal of multiple speakers at a different location. In over-determined conditions where the microphones out-numb... | [] | Train |
24,973 | 11 | Title: The Benefits of Interaction Constraints in Distributed Autonomous Systems
Abstract: The design of distributed autonomous systems often omits consideration of the underlying network dynamics. Recent works in multi-agent systems and swarm robotics alike have highlighted the impact that the interactions between age... | [] | Train |
24,974 | 10 | Title: Meaningful Causal Aggregation and Paradoxical Confounding
Abstract: In aggregated variables the impact of interventions is typically ill-defined because different micro-realizations of the same macro-intervention can result in different changes of downstream macro-variables. We show that this ill-definedness of ... | [] | Train |
24,975 | 24 | Title: Great Models Think Alike: Improving Model Reliability via Inter-Model Latent Agreement
Abstract: Reliable application of machine learning is of primary importance to the practical deployment of deep learning methods. A fundamental challenge is that models are often unreliable due to overconfidence. In this paper... | [
21008,
37947,
12574
] | Train |
24,976 | 24 | Title: Designing an attack-defense game: how to increase robustness of financial transaction models via a competition
Abstract: Given the escalating risks of malicious attacks in the finance sector and the consequential severe damage, a thorough understanding of adversarial strategies and robust defense mechanisms for ... | [
5348
] | Test |
24,977 | 24 | Title: Alternating Local Enumeration (TnALE): Solving Tensor Network Structure Search with Fewer Evaluations
Abstract: Tensor network (TN) is a powerful framework in machine learning, but selecting a good TN model, known as TN structure search (TN-SS), is a challenging and computationally intensive task. The recent app... | [
43360,
31754,
38701
] | Test |
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