node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
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|---|---|---|---|---|
31,178 | 34 | Title: Fast Algorithms for Directed Graph Partitioning Using Flows and Reweighted Eigenvalues
Abstract: We consider a new semidefinite programming relaxation for directed edge expansion, which is obtained by adding triangle inequalities to the reweighted eigenvalue formulation. Applying the matrix multiplicative weight... | [
17035
] | Validation |
31,179 | 13 | Title: Evolving Constrained Reinforcement Learning Policy
Abstract: Evolutionary algorithms have been used to evolve a population of actors to generate diverse experiences for training reinforcement learning agents, which helps to tackle the temporal credit assignment problem and improves the exploration efficiency. Ho... | [] | Train |
31,180 | 24 | Title: Operating data of a specific Aquatic Center as a Benchmark for dynamic model learning: search for a valid prediction model over an 8-hour horizon
Abstract: This article presents an identification benchmark based on data from a public swimming pool in operation. Such a system is both a complex process and easily ... | [] | Train |
31,181 | 30 | Title: A Human Subject Study of Named Entity Recognition in Conversational Music Recommendation Queries
Abstract: We conducted a human subject study of named entity recognition on a noisy corpus of conversational music recommendation queries, with many irregular and novel named entities. We evaluated the human NER ling... | [] | Train |
31,182 | 9 | Title: Deterministic identity testing paradigms for bounded top-fanin depth-4 circuits
Abstract: Polynomial Identity Testing (PIT) is a fundamental computational problem. The famous depth-4 reduction (Agrawal & Vinay, FOCS'08) has made PIT for depth-4 circuits, an enticing pursuit. The largely open special-cases of sum... | [] | Train |
31,183 | 28 | Title: Deep Reinforcement Learning Based Power Allocation for Minimizing AoI and Energy Consumption in MIMO-NOMA IoT Systems
Abstract: Multi-input multi-out and non-orthogonal multiple access (MIMO-NOMA) internet-of-things (IoT) systems can improve channel capacity and spectrum efficiency distinctly to support the real... | [] | Train |
31,184 | 28 | Title: Explicit Construction of q-ary 2-deletion Correcting Codes with Low Redundancy
Abstract: We consider the problem of efficient construction of q-ary 2-deletion correcting codes with low redundancy. We show that our construction requires less redundancy than any existing efficiently encodable q-ary 2-deletion corr... | [] | Train |
31,185 | 30 | Title: Songs Across Borders: Singable and Controllable Neural Lyric Translation
Abstract: The development of general-domain neural machine translation (NMT) methods has advanced significantly in recent years, but the lack of naturalness and musical constraints in the outputs makes them unable to produce singable lyric ... | [
15580
] | Train |
31,186 | 26 | Title: Exact Community Recovery in the Geometric SBM
Abstract: We study the problem of exact community recovery in the Geometric Stochastic Block Model (GSBM), where each vertex has an unknown community label as well as a known position, generated according to a Poisson point process in $\mathbb{R}^d$. Edges are formed... | [] | Train |
31,187 | 30 | Title: Understanding Counterspeech for Online Harm Mitigation
Abstract: Counterspeech offers direct rebuttals to hateful speech by challenging perpetrators of hate and showing support to targets of abuse. It provides a promising alternative to more contentious measures, such as content moderation and deplatforming, by ... | [
24764,
8644
] | Train |
31,188 | 24 | Title: An Efficient Approach to Mitigate Numerical Instability in Backpropagation for 16-bit Neural Network Training
Abstract: In this research, we delve into the intricacies of the numerical instability observed in 16-bit computations of machine learning models, particularly when employing popular optimization algorit... | [
8036
] | Train |
31,189 | 30 | Title: Zero-Shot Information Extraction via Chatting with ChatGPT
Abstract: Zero-shot information extraction (IE) aims to build IE systems from the unannotated text. It is challenging due to involving little human intervention. Challenging but worthwhile, zero-shot IE reduces the time and effort that data labeling take... | [
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... | Train |
31,190 | 30 | Title: Scaling laws for language encoding models in fMRI
Abstract: Representations from transformer-based unidirectional language models are known to be effective at predicting brain responses to natural language. However, most studies comparing language models to brains have used GPT-2 or similarly sized language mode... | [
38338,
13700
] | Validation |
31,191 | 16 | Title: A Correct-and-Certify Approach to Self-Supervise Object Pose Estimators via Ensemble Self-Training
Abstract: Real-world robotics applications demand object pose estimation methods that work reliably across a variety of scenarios. Modern learning-based approaches require large labeled datasets and tend to perform... | [
998
] | Train |
31,192 | 24 | Title: Text-Conditioned Sampling Framework for Text-to-Image Generation with Masked Generative Models
Abstract: Token-based masked generative models are gaining popularity for their fast inference time with parallel decoding. While recent token-based approaches achieve competitive performance to diffusion-based models,... | [
28532
] | Validation |
31,193 | 26 | Title: On the graph theory of majority illusions
Abstract: The popularity of an opinion in one's direct circles is not necessarily a good indicator of its popularity in one's entire community. For instance, when confronted with a majority of opposing opinions in one's circles, one might get the impression that one belo... | [] | Train |
31,194 | 30 | Title: Symbol tuning improves in-context learning in language models
Abstract: We present symbol tuning - finetuning language models on in-context input-label pairs where natural language labels (e.g.,"positive/negative sentiment") are replaced with arbitrary symbols (e.g.,"foo/bar"). Symbol tuning leverages the intuit... | [
33220,
43327,
3398,
25192,
9610,
6255,
3795,
45973,
24087,
37310,
4639
] | Train |
31,195 | 28 | Title: Cubature Kalman filter Based on generalized minimum error entropy with fiducial point
Abstract: In real applications, non-Gaussian distributions are frequently caused by outliers and impulsive disturbances, and these will impair the performance of the classical cubature Kalman filter (CKF) algorithm. In this let... | [] | Train |
31,196 | 10 | Title: From Probabilistic Programming to Complexity-based Programming
Abstract: The paper presents the main characteristics and a preliminary implementation of a novel computational framework named CompLog. Inspired by probabilistic programming systems like ProbLog, CompLog builds upon the inferential mechanisms propos... | [] | Train |
31,197 | 21 | Title: Exploring the use of Eye Tracking Technology to improve Website Usability
Abstract: This study investigates the capability blessings of the use of eye-monitoring technology to beautify the usability of web sites. With the upward thrust of on-line interactions, website usability has turn out to be increasingly im... | [] | Train |
31,198 | 27 | Title: Height Change Feature Based Free Space Detection
Abstract: In the context of autonomous forklifts, ensuring non-collision during travel, pick, and place operations is crucial. To accomplish this, the forklift must be able to detect and locate areas of free space and potential obstacles in its environment. Howeve... | [] | Validation |
31,199 | 4 | Title: Full Transparency in DBI frameworks
Abstract: Following the increasing trends of malicious applications or cyber threats in general, program analysis has become a ubiquitous technique in extracting relevant features. The current state-of-the-art solutions seem to fall behind new techniques. For instance, dynamic... | [] | Train |
31,200 | 16 | Title: BOSS: Bones, Organs and Skin Shape Model
Abstract: A virtual anatomical model of a patient can be a valuable tool for enhancing clinical tasks such as workflow automation, patient-specific X-ray dose optimization, markerless tracking, positioning, and navigation assistance in image-guided interventions. For thes... | [] | Test |
31,201 | 24 | Title: On the Robustness of Split Learning against Adversarial Attacks
Abstract: Split learning enables collaborative deep learning model training while preserving data privacy and model security by avoiding direct sharing of raw data and model details (i.e., sever and clients only hold partial sub-networks and exchang... | [] | Test |
31,202 | 34 | Title: Fitting Tree Metrics with Minimum Disagreements
Abstract: In the $L_0$ Fitting Tree Metrics problem, we are given all pairwise distances among the elements of a set $V$ and our output is a tree metric on $V$. The goal is to minimize the number of pairwise distance disagreements between the input and the output. ... | [] | Validation |
31,203 | 27 | Title: Neural-Network-Driven Method for Optimal Path Planning via High-Accuracy Region Prediction
Abstract: Sampling-based path planning algorithms suffer from heavy reliance on uniform sampling, which accounts for unreliable and time-consuming performance, especially in complex environments. Recently, neural-network-d... | [] | Train |
31,204 | 2 | Title: Nominal Sets in Agda - A Fresh and Immature Mechanization
Abstract: In this paper we present our current development on a new formalization of nominal sets in Agda. Our first motivation in having another formalization was to understand better nominal sets and to have a playground for testing type systems based o... | [] | Test |
31,205 | 16 | Title: Memory-Efficient Graph Convolutional Networks for Object Classification and Detection with Event Cameras
Abstract: Recent advances in event camera research emphasize processing data in its original sparse form, which allows the use of its unique features such as high temporal resolution, high dynamic range, low ... | [
23280
] | Validation |
31,206 | 6 | Title: Effect of Mindfulness and Mindful Art on Beginners and Experienced Meditators
Abstract: Mindfulness meditation has been proven to be effective in treating a range of mental and physical conditions. Mindful Art is a type of mindfulness meditation that comprises sessions of drawing, painting and sculpturing with m... | [] | Train |
31,207 | 1 | Title: Green video complexity analysis for efficient encoding in Adaptive Video Streaming
Abstract: For adaptive streaming applications, low-complexity and accurate video complexity features are necessary to analyze the video content in real time, which ensures fast and compression-efficient video streaming without dis... | [
39714,
42851,
18036
] | Train |
31,208 | 16 | Title: A Similarity Alignment Model for Video Copy Segment Matching
Abstract: With the development of multimedia technology, Video Copy Detection has been a crucial problem for social media platforms. Meta AI hold Video Similarity Challenge on CVPR 2023 to push the technology forward. In this report, we share our winne... | [
23417
] | Train |
31,209 | 27 | Title: CBAGAN-RRT: Convolutional Block Attention Generative Adversarial Network for Sampling-Based Path Planning
Abstract: Sampling-based path planning algorithms play an important role in autonomous robotics. However, a common problem among the RRT-based algorithms is that the initial path generated is not optimal and... | [] | Test |
31,210 | 27 | Title: A LiDAR-Inertial SLAM Tightly-Coupled with Dropout-Tolerant GNSS Fusion for Autonomous Mine Service Vehicles
Abstract: Multi-modal sensor integration has become a crucial prerequisite for the real-world navigation systems. Recent studies have reported successful deployment of such system in many fields. However,... | [] | Train |
31,211 | 13 | Title: GI Software with fewer Data Cache Misses
Abstract: By their very name caches are often overlooked and yet play a vital role in the performance of modern and indeed future hardware. Using MAGPIE (Machine Automated General Performance Improvement via Evolution of software) we show genetic improvement GI can reduce... | [] | Train |
31,212 | 30 | Title: Knowledge Authoring for Rules and Actions
Abstract:
Knowledge representation and reasoning (KRR) systems describe and reason with complex concepts and relations in the form of facts and rules. Unfortunately, wide deployment of KRR systems runs into the problem that domain experts have great difficulty construc... | [] | Test |
31,213 | 16 | Title: Zero-shot performance of the Segment Anything Model (SAM) in 2D medical imaging: A comprehensive evaluation and practical guidelines
Abstract: Segmentation in medical imaging is a critical component for the diagnosis, monitoring, and treatment of various diseases and medical conditions. Presently, the medical se... | [
12704,
16440,
35263
] | Train |
31,214 | 30 | Title: Semantic Tokenizer for Enhanced Natural Language Processing
Abstract: Traditionally, NLP performance improvement has been focused on improving models and increasing the number of model parameters. NLP vocabulary construction has remained focused on maximizing the number of words represented through subword regul... | [] | Train |
31,215 | 30 | Title: Unifying Large Language Models and Knowledge Graphs: A Roadmap
Abstract: Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the field of natural language processing and artificial intelligence, due to their emergent ability and generalizability. However, LLMs are black-box models, wh... | [
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41473,
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44606,
8769,
45131,
22097,
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9685,
16725,
19159,
31320,
11612,
... | Train |
31,216 | 15 | Title: ASMCap: An Approximate String Matching Accelerator for Genome Sequence Analysis Based on Capacitive Content Addressable Memory
Abstract: Genome sequence analysis is a powerful tool in medical and scientific research. Considering the inevitable sequencing errors and genetic variations, approximate string matching... | [] | Validation |
31,217 | 30 | Title: Interactive Text Generation
Abstract: Users interact with text, image, code, or other editors on a daily basis. However, machine learning models are rarely trained in the settings that reflect the interactivity between users and their editor. This is understandable as training AI models with real users is not on... | [] | Train |
31,218 | 30 | Title: HuaTuo: Tuning LLaMA Model with Chinese Medical Knowledge
Abstract: Large Language Models (LLMs), such as the LLaMA model, have demonstrated their effectiveness in various general-domain natural language processing (NLP) tasks. Nevertheless, LLMs have not yet performed optimally in biomedical domain tasks due to... | [
13700,
22547,
31382,
24087,
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19230,
31012,
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32184,
30266,
7996,
11592,
15818,
8530,
39638,
32600,
11619,
33779,
1270,
40440
] | Train |
31,219 | 30 | Title: Benchmarking Arabic AI with Large Language Models
Abstract: With large Foundation Models (FMs), language technologies (AI in general) are entering a new paradigm: eliminating the need for developing large-scale task-specific datasets and supporting a variety of tasks through set-ups ranging from zero-shot to few... | [
33220,
13510,
19083,
46029,
43566,
21778,
8436,
24629,
14966,
37177,
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35580
] | Train |
31,220 | 24 | Title: Fairness in KI-Systemen
Abstract: The more AI-assisted decisions affect people's lives, the more important the fairness of such decisions becomes. In this chapter, we provide an introduction to research on fairness in machine learning. We explain the main fairness definitions and strategies for achieving fairnes... | [
44082
] | Train |
31,221 | 27 | Title: Enabling Astronaut Self-Scheduling using a Robust Advanced Modelling and Scheduling system: an assessment during a Mars analogue mission
Abstract: Human long duration exploration missions (LDEMs) raise a number of technological challenges. This paper addresses the question of the crew autonomy: as the distances ... | [] | Test |
31,222 | 38 | Title: Open Access: Who are the Ghost Readers?
Abstract: To develop a funding model for Open Access journal publication, it is necessary first to understand who benefits. This is a difficult task, because, in Open Access, no credentials are needed to read a journal article, and, thus, those people who access journal ar... | [] | Test |
31,223 | 24 | Title: A semantic backdoor attack against Graph Convolutional Networks
Abstract: Graph convolutional networks (GCNs) have been very effective in addressing the issue of various graph-structured related tasks. However, recent research has shown that GCNs are vulnerable to a new type of threat called a backdoor attack, w... | [] | Test |
31,224 | 15 | Title: ReDSEa: Automated Acceleration of Triangular Solver on Supercloud Heterogeneous Systems
Abstract: When utilized effectively, Supercloud heterogeneous systems have the potential to significantly enhance performance. Our ReDSEa tool-chain automates the mapping, load balancing, scheduling, parallelism, and overlapp... | [] | Train |
31,225 | 16 | Title: Tracking Anything with Decoupled Video Segmentation
Abstract: Training data for video segmentation are expensive to annotate. This impedes extensions of end-to-end algorithms to new video segmentation tasks, especially in large-vocabulary settings. To 'track anything' without training on video data for every ind... | [
6560,
17633,
18112,
3782,
14504,
34955,
28141,
23570,
31346,
11894,
14168
] | Test |
31,226 | 26 | Title: Text-aided Group Decision-making Process Observation Method (x-GDP): A novel methodology for observing the joint decision-making process of travel choices
Abstract: Joint travel decisions, particularly related to social activities remain poorly explained in traditional behavioral models. A key reason for this is... | [] | Train |
31,227 | 30 | Title: A Symbolic Framework for Systematic Evaluation of Mathematical Reasoning with Transformers
Abstract: Whether Transformers can learn to apply symbolic rules and generalise to out-of-distribution examples is an open research question. In this paper, we devise a data generation method for producing intricate mathem... | [
38406,
1546,
12881,
23924,
44246
] | Test |
31,228 | 3 | Title: Understanding Idea Creation in Collaborative Discourse through Networks: The Joint Attention-Interaction-Creation (AIC) Framework
Abstract: In Computer-Supported Collaborative Learning, ideas generated through collaborative discourse are informative indicators of students' learning and collaboration. Idea creati... | [] | Train |
31,229 | 24 | Title: Diffusion Probabilistic Models for Structured Node Classification
Abstract: This paper studies structured node classification on graphs, where the predictions should consider dependencies between the node labels. In particular, we focus on solving the problem for partially labeled graphs where it is essential to... | [] | Test |
31,230 | 14 | Title: Reduction-Based Creative Telescoping for Definite Summation of D-finite Functions
Abstract: Creative telescoping is an algorithmic method initiated by Zeilberger to compute definite sums by synthesizing summands that telescope, called certificates. We describe a creative telescoping algorithm that computes teles... | [] | Test |
31,231 | 33 | Title: Duality of lattices associated to left and right quotients
Abstract: We associate lattices to the sets of unions and intersections of left and right quotients of a regular language. For both unions and intersections, we show that the lattices we produce using left and right quotients are dual to each other. We a... | [] | Test |
31,232 | 30 | Title: Towards Answering Climate Questionnaires from Unstructured Climate Reports
Abstract: The topic of Climate Change (CC) has received limited attention in NLP despite its urgency. Activists and policymakers need NLP tools to effectively process the vast and rapidly growing unstructured textual climate reports into ... | [] | Train |
31,233 | 34 | Title: Sketch-Flip-Merge: Mergeable Sketches for Private Distinct Counting
Abstract: Data sketching is a critical tool for distinct counting, enabling multisets to be represented by compact summaries that admit fast cardinality estimates. Because sketches may be merged to summarize multiset unions, they are a basic bui... | [
9000,
11074
] | Train |
31,234 | 23 | Title: Quantum Software Engineering Challenges from Developers' Perspective: Mapping Research Challenges to the Proposed Workflow Model
Abstract: Despite the increasing interest in quantum computing, the aspect of development to achieve cost-effective and reliable quantum software applications has been slow. One barrie... | [] | Test |
31,235 | 6 | Title: Young Humans Make Change, Young Users Click: Creating Youth-Centered Networked Social Movements
Abstract: From the urbanists' perspective, the everyday experience of young people, as an underrepresented group in the design of public spaces, includes tactics they use to challenge the strategies which rule over ur... | [] | Train |
31,236 | 31 | Title: Feature Representation Learning for Click-through Rate Prediction: A Review and New Perspectives
Abstract: Representation learning has been a critical topic in machine learning. In Click-through Rate Prediction, most features are represented as embedding vectors and learned simultaneously with other parameters i... | [
6656
] | Train |
31,237 | 34 | Title: A Cover Time Study of a non-Markovian Algorithm
Abstract: Given a traversal algorithm, cover time is the expected number of steps needed to visit all nodes in a given graph. A smaller cover time means a higher exploration efficiency of traversal algorithm. Although random walk algorithms have been studied extens... | [] | Train |
31,238 | 30 | Title: Emotionally Numb or Empathetic? Evaluating How LLMs Feel Using EmotionBench
Abstract: Recently, the community has witnessed the advancement of Large Language Models (LLMs), which have shown remarkable performance on various downstream tasks. Led by powerful models like ChatGPT and Claude, LLMs are revolutionizin... | [
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25924,
33220,
13510,
40006,
33477,
981,
21593,
729,
7648,
40561,
43641,
39295
] | Train |
31,239 | 3 | Title: How learners produce data from text in classifying clickbait
Abstract: Text provides a compelling example of unstructured data that can be used to motivate and explore classification problems. Challenges arise regarding the representation of features of text and student linkage between text representations as ch... | [] | Train |
31,240 | 16 | Title: Correspondence-Free Domain Alignment for Unsupervised Cross-Domain Image Retrieval
Abstract: Cross-domain image retrieval aims at retrieving images across different domains to excavate cross-domain classificatory or correspondence relationships. This paper studies a less-touched problem of cross-domain image ret... | [] | Train |
31,241 | 24 | Title: Learning to Forecast Aleatoric and Epistemic Uncertainties over Long Horizon Trajectories
Abstract: Giving autonomous agents the ability to forecast their own outcomes and uncertainty will allow them to communicate their competencies and be used more safely. We accomplish this by using a learned world model of t... | [
8922
] | Train |
31,242 | 16 | Title: Pedestrian detection with high-resolution event camera
Abstract: Despite the dynamic development of computer vision algorithms, the implementation of perception and control systems for autonomous vehicles such as drones and self-driving cars still poses many challenges. A video stream captured by traditional cam... | [] | Train |
31,243 | 16 | Title: TextManiA: Enriching Visual Feature by Text-driven Manifold Augmentation
Abstract: We propose TextManiA, a text-driven manifold augmentation method that semantically enriches visual feature spaces, regardless of class distribution. TextManiA augments visual data with intra-class semantic perturbation by exploiti... | [
32377,
11906,
38927
] | Test |
31,244 | 26 | Title: Opinion-aware Influence Maximization in Online Social Networks
Abstract: Influence maximization (IM) aims to find seed users on an online social network to maximize the spread of information about a target product through word-of-mouth propagation among all users. Prior IM methods mostly focus on maximizing the ... | [] | Train |
31,245 | 30 | Title: A mixed policy to improve performance of language models on math problems
Abstract: When to solve math problems, most language models take a sampling strategy to predict next word according conditional probabilities. In the math reasoning step, it may generate wrong answer. Considering math problems are determin... | [
10293
] | Train |
31,246 | 10 | Title: Inductive Learning of Declarative Domain-Specific Heuristics for ASP
Abstract: Domain-specific heuristics are a crucial technique for the efficient solving of problems that are large or computationally hard. Answer Set Programming (ASP) systems support declarative specifications of domain-specific heuristics to ... | [] | Train |
31,247 | 16 | Title: Beyond the Prior Forgery Knowledge: Mining Critical Clues for General Face Forgery Detection
Abstract: Face forgery detection is essential in combating malicious digital face attacks. Previous methods mainly rely on prior expert knowledge to capture specific forgery clues, such as noise patterns, blending bounda... | [
18735
] | Train |
31,248 | 24 | Title: Comprehensive Assessment of the Performance of Deep Learning Classifiers Reveals a Surprising Lack of Robustness
Abstract: Reliable and robust evaluation methods are a necessary first step towards developing machine learning models that are themselves robust and reliable. Unfortunately, current evaluation protoc... | [
39968,
42176,
33414,
29799,
40233,
36809,
43021,
23727,
28053
] | Train |
31,249 | 4 | Title: Deep Cross-Modal Steganography Using Neural Representations
Abstract: Steganography is the process of embedding secret data into another message or data, in such a way that it is not easily noticeable. With the advancement of deep learning, Deep Neural Networks (DNNs) have recently been utilized in steganography... | [] | Train |
31,250 | 30 | Title: ARIES: A Corpus of Scientific Paper Edits Made in Response to Peer Reviews
Abstract: Revising scientific papers based on peer feedback is a challenging task that requires not only deep scientific knowledge and reasoning, but also the ability to recognize the implicit requests in high-level feedback and to choose... | [
39016,
35834,
14635,
39594
] | Train |
31,251 | 22 | Title: Amortized Analysis via Coinduction
Abstract: Amortized analysis is a program cost analysis technique for data structures in which the cost of operations is specified in aggregate, under the assumption of continued sequential use. Typically, amortized analyses are presented inductively, in terms of finite sequenc... | [
7950
] | Train |
31,252 | 16 | Title: Reliability in Semantic Segmentation: Are we on the Right Track?
Abstract: Motivated by the increasing popularity of transformers in computer vision, in recent times there has been a rapid development of novel architectures. While in-domain performance follows a constant, upward trend, properties like robustness... | [
14448,
13866,
29605
] | Train |
31,253 | 24 | Title: RAFEN - Regularized Alignment Framework for Embeddings of Nodes
Abstract: Learning representations of nodes has been a crucial area of the graph machine learning research area. A well-defined node embedding model should reflect both node features and the graph structure in the final embedding. In the case of dyn... | [] | Train |
31,254 | 6 | Title: Improving the State of the Art for Training Human-AI Teams: Technical Report #1 - Results of Subject-Matter Expert Knowledge Elicitation Survey
Abstract: A consensus report produced for the Air Force Research Laboratory by the National Academies of Sciences, Engineering, and Mathematics documented a prevalent an... | [] | Test |
31,255 | 33 | Title: Computational Power of Particle Methods
Abstract: The computational power of a compute model determines the class of problems it can solve. Automata theory allows describing the computational power of abstract machines (automata) and the problems they can solve. At the top of the Chomsky hierarchy of formal lang... | [] | Train |
31,256 | 30 | Title: Accelerating Large Language Model Decoding with Speculative Sampling
Abstract: We present speculative sampling, an algorithm for accelerating transformer decoding by enabling the generation of multiple tokens from each transformer call. Our algorithm relies on the observation that the latency of parallel scoring... | [
30081,
22978,
33953,
20411,
30331,
31976,
425,
38217,
528,
42993,
5522,
33363,
37008,
1141,
4475,
30044,
40413
] | Validation |
31,257 | 4 | Title: BlockChain and Decentralized Apps
Abstract: Blockchain, the backbone of Bitcoin, has recently gained a lot of attention. Blockchain functions as an immutable record that enables decentralized transactions. Blockchain-based applications are sprouting up in a variety of industries, including financial services, re... | [] | Train |
31,258 | 16 | Title: Delicate Textured Mesh Recovery from NeRF via Adaptive Surface Refinement
Abstract: Neural Radiance Fields (NeRF) have constituted a remarkable breakthrough in image-based 3D reconstruction. However, their implicit volumetric representations differ significantly from the widely-adopted polygonal meshes and lack ... | [
22464,
11206,
1895,
3672,
11450,
36030,
9599
] | Train |
31,259 | 30 | Title: 2*n is better than n2: Decomposing Event Coreference Resolution into Two Tractable Problems
Abstract: Event Coreference Resolution (ECR) is the task of linking mentions of the same event either within or across documents. Most mention pairs are not coreferent, yet many that are coreferent can be identified throu... | [
31613
] | Train |
31,260 | 8 | Title: XRP-NDN overlay: Improving the Communication Efficiency of Consensus-Validation based Blockchains with an NDN Overlay
Abstract: With growing adoption of Distributed Ledger Technologies, their networks must scale while maintaining efficient communication for the underlying consensus and replication mechanisms. Ne... | [] | Train |
31,261 | 10 | Title: Act for Your Duties but Maintain Your Rights
Abstract: Most of the synthesis literature has focused on studying how to synthesize a strategy to fulfill a task. This task is a duty for the agent. In this paper, we argue that intelligent agents should also be equipped with rights, that is, tasks that the agent its... | [] | Train |
31,262 | 13 | Title: Noise-Resilient Designs for Optical Neural Networks
Abstract: All analog signal processing is fundamentally subject to noise, and this is also the case in modern implementations of Optical Neural Networks (ONNs). Therefore, to mitigate noise in ONNs, we propose two designs that are constructed from a given, poss... | [] | Test |
31,263 | 23 | Title: Consolidation of Ground Truth Sets for Weakness Detection in Smart Contracts
Abstract: Smart contracts are small programs on the blockchain that often handle valuable assets. Vulnerabilities in smart contracts can be costly, as time has shown over and over again. Countermeasures are high in demand and include be... | [] | Train |
31,264 | 30 | Title: Boosting Language Models Reasoning with Chain-of-Knowledge Prompting
Abstract: Recently, Chain-of-Thought (CoT) prompting has delivered success on complex reasoning tasks, which aims at designing a simple prompt like ``Let's think step by step'' or multiple in-context exemplars with well-designed rationales to e... | [
43906,
13700,
32552,
6963,
10165,
38262,
33817,
634
] | Train |
31,265 | 10 | Title: Question-Answering System Extracts Information on Injection Drug Use from Clinical Progress Notes
Abstract: Injection drug use (IDU) is a dangerous health behavior that increases mortality and morbidity. Identifying IDU early and initiating harm reduction interventions can benefit individuals at risk. However, e... | [
42060,
38454
] | Validation |
31,266 | 15 | Title: Minimizing the Motion-to-Photon-delay (MPD) in Virtual Reality Systems
Abstract: With the advent of low-power ultra-fast hardware and GPUs, virtual reality (VR) has gained a lot of prominence in the last few years and is being used in various areas such as education, entertainment, scientific visualization, and ... | [] | Train |
31,267 | 16 | Title: Video Diffusion Models with Local-Global Context Guidance
Abstract: Diffusion models have emerged as a powerful paradigm in video synthesis tasks including prediction, generation, and interpolation. Due to the limitation of the computational budget, existing methods usually implement conditional diffusion models... | [
42587
] | Train |
31,268 | 10 | Title: Case-Based Reasoning with Language Models for Classification of Logical Fallacies
Abstract: The ease and speed of spreading misinformation and propaganda on the Web motivate the need to develop trustworthy technology for detecting fallacies in natural language arguments. However, state-of-the-art language modeli... | [
9527
] | Validation |
31,269 | 23 | Title: Visually Analyzing Company-wide Software Service Dependencies: An Industrial Case Study
Abstract: Managing dependencies between software services is a crucial task for any company operating cloud applications. Visualizations can help to understand and maintain these complex dependencies. In this paper, we presen... | [] | Validation |
31,270 | 30 | Title: VacancySBERT: the approach for representation of titles and skills for semantic similarity search in the recruitment domain
Abstract: The paper focuses on deep learning semantic search algorithms applied in the HR domain. The aim of the article is developing a novel approach to training a Siamese network to link... | [] | Train |
31,271 | 31 | Title: Black-box Adversarial Attacks against Dense Retrieval Models: A Multi-view Contrastive Learning Method
Abstract: Neural ranking models (NRMs) and dense retrieval (DR) models have given rise to substantial improvements in overall retrieval performance. In addition to their effectiveness, and motivated by the prov... | [
14888,
41033
] | Train |
31,272 | 16 | Title: Uncertainty estimation in Deep Learning for Panoptic segmentation
Abstract: As deep learning-based computer vision algorithms continue to improve and advance the state of the art, their robustness to real-world data continues to lag their performance on datasets. This makes it difficult to bring an algorithm fro... | [] | Test |
31,273 | 16 | Title: Parameter and Computation Efficient Transfer Learning for Vision-Language Pre-trained Models
Abstract: With ever increasing parameters and computation, vision-language pre-trained (VLP) models exhibit prohibitive expenditure in downstream task adaption. Recent endeavors mainly focus on parameter efficient transf... | [
38796
] | Test |
31,274 | 10 | Title: The Promise and Peril of Artificial Intelligence - Violet Teaming Offers a Balanced Path Forward
Abstract: Artificial intelligence (AI) promises immense benefits across sectors, yet also poses risks from dual-use potentials, biases, and unintended behaviors. This paper reviews emerging issues with opaque and unc... | [
32944,
13510
] | Validation |
31,275 | 24 | Title: A Privacy-Preserving Hybrid Federated Learning Framework for Financial Crime Detection
Abstract: The recent decade witnessed a surge of increase in financial crimes across the public and private sectors, with an average cost of scams of $102m to financial institutions in 2022. Developing a mechanism for battling... | [
30320,
24485
] | Train |
31,276 | 16 | Title: Achieving RGB-D level Segmentation Performance from a Single ToF Camera
Abstract: Depth is a very important modality in computer vision, typically used as complementary information to RGB, provided by RGB-D cameras. In this work, we show that it is possible to obtain the same level of accuracy as RGB-D cameras o... | [] | Train |
31,277 | 24 | Title: Normality Learning-based Graph Anomaly Detection via Multi-Scale Contrastive Learning
Abstract: Graph anomaly detection (GAD) has attracted increasing attention in machine learning and data mining. Recent works have mainly focused on how to capture richer information to improve the quality of node embeddings for... | [
24286
] | Validation |
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