node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
values |
|---|---|---|---|---|
29,578 | 10 | Title: Explanation Through Reward Model Reconciliation using POMDP Tree Search
Abstract: As artificial intelligence (AI) algorithms are increasingly used in mission-critical applications, promoting user-trust of these systems will be essential to their success. Ensuring users understand the models over which algorithms... | [
36307
] | Train |
29,579 | 24 | Title: Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees
Abstract: Gradient clipping is a popular modification to standard (stochastic) gradient descent, at every iteration limiting the gradient norm to a certain value $c>0$. It is widely used for example for stabilizing the training of dee... | [
19684
] | Train |
29,580 | 34 | Title: Hypergraph Diffusions and Resolvents for Norm-Based Hypergraph Laplacians
Abstract: The development of simple and fast hypergraph spectral methods has been hindered by the lack of numerical algorithms for simulating heat diffusions and computing fundamental objects, such as Personalized PageRank vectors, over hy... | [] | Train |
29,581 | 16 | Title: Video Generation Beyond a Single Clip
Abstract: We tackle the long video generation problem, i.e.~generating videos beyond the output length of video generation models. Due to the computation resource constraints, video generation models can only generate video clips that are relatively short compared with the l... | [] | Train |
29,582 | 16 | Title: Zero-shot Visual Relation Detection via Composite Visual Cues from Large Language Models
Abstract: Pretrained vision-language models, such as CLIP, have demonstrated strong generalization capabilities, making them promising tools in the realm of zero-shot visual recognition. Visual relation detection (VRD) is a ... | [
32960,
20940
] | Train |
29,583 | 10 | Title: Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations
Abstract: Causal abstraction is a promising theoretical framework for explainable artificial intelligence that defines when an interpretable high-level causal model is a faithful simplification of a low-level deep le... | [
29792,
13955,
29414,
43560,
26161,
37553,
43667,
22133,
46109
] | Test |
29,584 | 24 | Title: A proof of convergence of inverse reinforcement learning for multi-objective optimization
Abstract: We show the convergence of Wasserstein inverse reinforcement learning for multi-objective optimizations with the projective subgradient method by formulating an inverse problem of the multi-objective optimization ... | [] | Train |
29,585 | 16 | Title: Learning Dynamic Query Combinations for Transformer-based Object Detection and Segmentation
Abstract: Transformer-based detection and segmentation methods use a list of learned detection queries to retrieve information from the transformer network and learn to predict the location and category of one specific ob... | [
31634,
13893
] | Train |
29,586 | 16 | Title: Practical Edge Detection via Robust Collaborative Learning
Abstract: Edge detection, as a core component in a wide range of visionoriented tasks, is to identify object boundaries and prominent edges in natural images. An edge detector is desired to be both efficient and accurate for practical use. To achieve the... | [] | Train |
29,587 | 24 | Title: Sample-efficient Adversarial Imitation Learning
Abstract: Imitation learning, in which learning is performed by demonstration, has been studied and advanced for sequential decision-making tasks in which a reward function is not predefined. However, imitation learning methods still require numerous expert demonst... | [] | Train |
29,588 | 5 | Title: Honeycomb: ordered key-value store acceleration on an FPGA-based SmartNIC
Abstract: In-memory ordered key-value stores are an important building block in modern distributed applications. We present Honeycomb, a hybrid software-hardware system for accelerating read-dominated workloads on ordered key-value stores ... | [] | Train |
29,589 | 4 | Title: An End-To-End Encrypted Cache System with Time-Dependent Access Control
Abstract: Due to the increasing use of encrypted communication, such as Transport Layer Security (TLS), encrypted cache systems are a promising approach for providing communication efficiency and privacy. Cache-22 is an encrypted cache syste... | [] | Validation |
29,590 | 4 | Title: Canary in Twitter Mine: Collecting Phishing Reports from Experts and Non-experts
Abstract: The rise in phishing attacks via e-mail and short message service (SMS) has not slowed down at all. The first thing we need to do to combat the ever-increasing number of phishing attacks is to collect and characterize more... | [
30608
] | Train |
29,591 | 27 | Title: Learning Multiple Gaits within Latent Space for Quadruped Robots
Abstract: Learning multiple gaits is non-trivial for legged robots, especially when encountering different terrains and velocity commands. In this work, we present an end-to-end training framework for learning multiple gaits for quadruped robots, t... | [
4990
] | Test |
29,592 | 6 | Title: Design Characterization for Black-and-White Textures in Visualization
Abstract: We investigate the use of 2D black-and-white textures for the visualization of categorical data and contribute a summary of texture attributes, and the results of three experiments that elicited design strategies as well as aesthetic... | [
42383
] | Validation |
29,593 | 24 | Title: A Blackbox Approach to Best of Both Worlds in Bandits and Beyond
Abstract: Best-of-both-worlds algorithms for online learning which achieve near-optimal regret in both the adversarial and the stochastic regimes have received growing attention recently. Existing techniques often require careful adaptation to ever... | [
28794,
2732,
1726,
39631
] | Train |
29,594 | 9 | Title: Parameterised distance to local irregularity
Abstract: A graph $G$ is \emph{locally irregular} if no two of its adjacent vertices have the same degree. In [Fioravantes et al. Complexity of finding maximum locally irregular induced subgraph. {\it SWAT}, 2022], the authors introduced and studied the problem of fin... | [] | Validation |
29,595 | 16 | Title: ReactFace: Multiple Appropriate Facial Reaction Generation in Dyadic Interactions
Abstract: In dyadic interaction, predicting the listener's facial reactions is challenging as different reactions may be appropriate in response to the same speaker's behaviour. This paper presents a novel framework called ReactFac... | [
31912,
28121,
25059
] | Validation |
29,596 | 31 | Title: Personalized Search Via Neural Contextual Semantic Relevance Ranking
Abstract: Existing neural relevance models do not give enough consideration for query and item context information which diversifies the search results to adapt for personal preference. To bridge this gap, this paper presents a neural learning ... | [] | Test |
29,597 | 21 | Title: Choose Your Weapon: Survival Strategies for Depressed AI Academics
Abstract: Are you an AI researcher at an academic institution? Are you anxious you are not coping with the current pace of AI advancements? Do you feel you have no (or very limited) access to the computational and human resources required for an ... | [
34215,
32450,
4822,
26335
] | Test |
29,598 | 30 | Title: Biomedical Entity Linking with Triple-aware Pre-Training
Abstract: Linking biomedical entities is an essential aspect in biomedical natural language processing tasks, such as text mining and question answering. However, a difficulty of linking the biomedical entities using current large language models (LLM) tra... | [] | Train |
29,599 | 24 | Title: Neuron Sensitivity Guided Test Case Selection for Deep Learning Testing
Abstract: Deep Neural Networks~(DNNs) have been widely deployed in software to address various tasks~(e.g., autonomous driving, medical diagnosis). However, they could also produce incorrect behaviors that result in financial losses and even... | [] | Test |
29,600 | 27 | Title: Leveraging Multi-modal Sensing for Robotic Insertion Tasks in R&D Laboratories
Abstract: Performing a large volume of experiments in Chemistry labs creates repetitive actions costing researchers time, automating these routines is highly desirable. Previous experiments in robotic chemistry have performed high num... | [
33209
] | Train |
29,601 | 4 | Title: MIRA: a Digital Signature Scheme based on the MinRank problem and the MPC-in-the-Head paradigm
Abstract: We exploit the idea of [Fen22] which proposes to build an efficient signature scheme based on a zero-knowledge proof of knowledge of a solution of a MinRank instance. The scheme uses the MPCitH paradigm, whic... | [
22294,
30111
] | Validation |
29,602 | 30 | Title: mCPT at SemEval-2023 Task 3: Multilingual Label-Aware Contrastive Pre-Training of Transformers for Few- and Zero-shot Framing Detection
Abstract: This paper presents the winning system for the zero-shot Spanish framing detection task, which also achieves competitive places in eight additional languages. The chal... | [
34530,
8949
] | Train |
29,603 | 24 | Title: MLHOps: Machine Learning for Healthcare Operations
Abstract: Machine Learning Health Operations (MLHOps) is the combination of processes for reliable, efficient, usable, and ethical deployment and maintenance of machine learning models in healthcare settings. This paper provides both a survey of work in this are... | [
33823,
32135
] | Train |
29,604 | 30 | Title: Large Language Models as Tax Attorneys: A Case Study in Legal Capabilities Emergence
Abstract: Better understanding of Large Language Models' (LLMs) legal analysis abilities can contribute to improving the efficiency of legal services, governing artificial intelligence, and leveraging LLMs to identify inconsiste... | [
37252,
32966,
31431,
18777,
26984,
16619,
7470,
9518,
9614,
28752,
402,
5138,
8436,
1401,
12602
] | Validation |
29,605 | 24 | Title: PseudoCal: A Source-Free Approach to Unsupervised Uncertainty Calibration in Domain Adaptation
Abstract: Unsupervised domain adaptation (UDA) has witnessed remarkable advancements in improving the accuracy of models for unlabeled target domains. However, the calibration of predictive uncertainty in the target do... | [
31252
] | Train |
29,606 | 30 | Title: Interpretable Unified Language Checking
Abstract: Despite recent concerns about undesirable behaviors generated by large language models (LLMs), including non-factual, biased, and hateful language, we find LLMs are inherent multi-task language checkers based on their latent representations of natural and social ... | [
38764,
37360,
38900,
28886,
22422,
7962
] | Train |
29,607 | 24 | Title: Sample Complexity for Quadratic Bandits: Hessian Dependent Bounds and Optimal Algorithms
Abstract: In stochastic zeroth-order optimization, a problem of practical relevance is understanding how to fully exploit the local geometry of the underlying objective function. We consider a fundamental setting in which th... | [] | Train |
29,608 | 2 | Title: Formalizing two-level type theory with cofibrant exo-nat
Abstract: This study provides some results about two-level type-theoretic notions in a way that the proofs are fully formalizable in a proof assistant implementing two-level type theory such as Agda. The difference from prior works is that these proofs do ... | [] | Train |
29,609 | 16 | Title: SCA-PVNet: Self-and-Cross Attention Based Aggregation of Point Cloud and Multi-View for 3D Object Retrieval
Abstract: To address 3D object retrieval, substantial efforts have been made to generate highly discriminative descriptors of 3D objects represented by a single modality, e.g., voxels, point clouds or mult... | [] | Validation |
29,610 | 24 | Title: Intelligent sampling for surrogate modeling, hyperparameter optimization, and data analysis
Abstract: nan | [
31584,
13819,
16831
] | Train |
29,611 | 8 | Title: Network Error Logging: HTTP Archive Analysis
Abstract: Network Error Logging helps web server operators detect operational problems in real-time to provide fast and reliable services. HTTP Archive provides detail information of historical data on HTTP requests. This paper leverages the data and provides a long t... | [
11228
] | Train |
29,612 | 10 | Title: Large Language Models as General Pattern Machines
Abstract: We observe that pre-trained large language models (LLMs) are capable of autoregressively completing complex token sequences -- from arbitrary ones procedurally generated by probabilistic context-free grammars (PCFG), to more rich spatial patterns found ... | [
17153,
43906,
5772,
7198,
4385,
19492,
13223,
24105,
33455,
35250,
26293,
23102,
26562,
38083,
3526,
39114,
18767,
3793,
26578,
7913,
9324,
37742,
22518,
13564
] | Test |
29,613 | 4 | Title: Generic Decoding of Restricted Errors
Abstract: Several recently proposed code-based cryptosystems base their security on a slightly generalized version of the classical (syndrome) decoding problem. Namely, in the so-called restricted (syndrome) decoding problem, the error values stem from a restricted set. In t... | [] | Train |
29,614 | 16 | Title: AD-CLIP: Adapting Domains in Prompt Space Using CLIP
Abstract: Although deep learning models have shown impressive performance on supervised learning tasks, they often struggle to generalize well when the training (source) and test (target) domains differ. Unsupervised domain adaptation (DA) has emerged as a pop... | [
8664,
3658,
13763
] | Train |
29,615 | 16 | Title: SigSegment: A Signal-Based Segmentation Algorithm for Identifying Anomalous Driving Behaviours in Naturalistic Driving Videos
Abstract: In recent years, distracted driving has garnered considerable attention as it continues to pose a significant threat to public safety on the roads. This has increased the need f... | [
42585,
20834,
3372
] | Validation |
29,616 | 6 | Title: A Comparative Study of the Perceptual Sensitivity of Topological Visualizations to Feature Variations
Abstract: Color maps are a commonly used visualization technique in which data are mapped to optical properties, e.g., color or opacity. Color maps, however, do not explicitly convey structures (e.g., positions ... | [
4173
] | Train |
29,617 | 6 | Title: The Utility of Large Language Models and Generative AI for Education Research
Abstract: The use of natural language processing (NLP) techniques in engineering education can provide valuable insights into the underlying processes involved in generating text. While accessing these insights can be labor-intensive i... | [
6942
] | Train |
29,618 | 23 | Title: Run-time Failure Detection via Non-intrusive Event Analysis in a Large-Scale Cloud Computing Platform
Abstract: nan | [] | Validation |
29,619 | 27 | Title: Autonomous Strawberry Picking Robotic System (Robofruit)
Abstract: Challenges in strawberry picking made selective harvesting robotic technology very demand-ing. However, the selective harvesting of strawberries is a complicated robotic task forming a few scientific research questions. Most available solutions on... | [
2435,
31469
] | Train |
29,620 | 24 | Title: Does AI for science need another ImageNet Or totally different benchmarks? A case study of machine learning force fields
Abstract: AI for science (AI4S) is an emerging research field that aims to enhance the accuracy and speed of scientific computing tasks using machine learning methods. Traditional AI benchmark... | [] | Validation |
29,621 | 24 | Title: Joint Age-based Client Selection and Resource Allocation for Communication-Efficient Federated Learning over NOMA Networks
Abstract: In federated learning (FL), distributed clients can collaboratively train a shared global model while retaining their own training data locally. Nevertheless, the performance of FL... | [] | Train |
29,622 | 16 | Title: Cross-Dimensional Refined Learning for Real-Time 3D Visual Perception from Monocular Video
Abstract: We present a novel real-time capable learning method that jointly perceives a 3D scene's geometry structure and semantic labels. Recent approaches to real-time 3D scene reconstruction mostly adopt a volumetric sc... | [] | Test |
29,623 | 15 | Title: SCV-GNN: Sparse Compressed Vector-based Graph Neural Network Aggregation
Abstract: Graph neural networks (GNNs) have emerged as a powerful tool to process graph-based data in fields like communication networks, molecular interactions, chemistry, social networks, and neuroscience. GNNs are characterized by the ul... | [] | Validation |
29,624 | 6 | Title: Large-Scale Collaborative Writing: Technical Challenges and Recommendations
Abstract: Collaborative writing is essential for teams that create documents together. Creating documents in large-scale collaborations is a challenging task that requires an efficient workflow. The design of such a workflow has received... | [] | Train |
29,625 | 24 | Title: HireVAE: An Online and Adaptive Factor Model Based on Hierarchical and Regime-Switch VAE
Abstract: Factor model is a fundamental investment tool in quantitative investment, which can be empowered by deep learning to become more flexible and efficient in practical complicated investing situations. However, it is ... | [] | Test |
29,626 | 27 | Title: LIW-OAM: Lidar-Inertial-Wheel Odometry and Mapping
Abstract: LiDAR-inertial odometry and mapping (LIOAM), which fuses complementary information of a LiDAR and an Inertial Measurement Unit (IMU), is an attractive solution for pose estimation and mapping. In LI-OAM, both pose and velocity are regarded as state var... | [
20180
] | Test |
29,627 | 16 | Title: Benchmarking Robustness to Adversarial Image Obfuscations
Abstract: Automated content filtering and moderation is an important tool that allows online platforms to build striving user communities that facilitate cooperation and prevent abuse. Unfortunately, resourceful actors try to bypass automated filters in a... | [
40066
] | Test |
29,628 | 28 | Title: The Dynamic Behavior of Frameless ALOHA: Drift Analysis, Throughput, and Age of Information
Abstract: We study the dynamic behavior of frameless ALOHA, both in terms of throughput and age of information (AoI). In particular, differently from previous studies, our analysis accounts for the fact that the number of... | [] | Train |
29,629 | 17 | Title: Interactive Design and Optics-Based Visualization of Arbitrary Non-Euclidean Kaleidoscopic Orbifolds
Abstract: Orbifolds are a modern mathematical concept that arises in the research of hyperbolic geometry with applications in computer graphics and visualization. In this paper, we make use of rooms with mirrors ... | [] | Train |
29,630 | 24 | Title: Automating Nearest Neighbor Search Configuration with Constrained Optimization
Abstract: The approximate nearest neighbor (ANN) search problem is fundamental to efficiently serving many real-world machine learning applications. A number of techniques have been developed for ANN search that are efficient, accurat... | [] | Train |
29,631 | 23 | Title: Role-playing software architecture styles
Abstract: Software Architecture, from definition to maintenance and evolution, is a complex aspect of software development and, consequently, a challenging subject when it comes to teaching it, and learning it.Many research efforts have been devoted to designing teaching... | [] | Train |
29,632 | 16 | Title: CROVIA: Seeing Drone Scenes from Car Perspective via Cross-View Adaptation
Abstract: Understanding semantic scene segmentation of urban scenes captured from the Unmanned Aerial Vehicles (UAV) perspective plays a vital role in building a perception model for UAV. With the limitations of large-scale densely labele... | [] | Train |
29,633 | 2 | Title: Choose your Colour: Tree Interpolation for Quantified Formulas in SMT
Abstract: We present a generic tree-interpolation algorithm in the SMT context with quantifiers. The algorithm takes a proof of unsatisfiability using resolution and quantifier instantiation and computes interpolants (which may contain quantif... | [] | Train |
29,634 | 16 | Title: Attention-based Graph Convolution Fusing Latent Structures and Multiple Features for Graph Neural Networks
Abstract: We present an attention-based spatial graph convolution (AGC) for graph neural networks (GNNs). Existing AGCs focus on only using node-wise features and utilizing one type of attention function wh... | [] | Train |
29,635 | 16 | Title: ALR-GAN: Adaptive Layout Refinement for Text-to-Image Synthesis
Abstract: We propose a novel Text-to-Image Generation Network, Adaptive Layout Refinement Generative Adversarial Network (ALR-GAN), to adaptively refine the layout of synthesized images without any auxiliary information. The ALR-GAN includes an Adap... | [] | Validation |
29,636 | 16 | Title: Data-Centric Diet: Effective Multi-center Dataset Pruning for Medical Image Segmentation
Abstract: This paper seeks to address the dense labeling problems where a significant fraction of the dataset can be pruned without sacrificing much accuracy. We observe that, on standard medical image segmentation benchmark... | [] | Train |
29,637 | 33 | Title: Dimension-Minimality and Primality of Counter Nets
Abstract: A $k$-Counter Net ($k$-CN) is a finite-state automaton equipped with $k$ integer counters that are not allowed to become negative, but do not have explicit zero tests. This language-recognition model can be thought of as labelled vector addition system... | [
20461
] | Train |
29,638 | 16 | Title: SF-FSDA: Source-Free Few-Shot Domain Adaptive Object Detection with Efficient Labeled Data Factory
Abstract: Domain adaptive object detection aims to leverage the knowledge learned from a labeled source domain to improve the performance on an unlabeled target domain. Prior works typically require the access to t... | [] | Train |
29,639 | 24 | Title: Skill Transformer: A Monolithic Policy for Mobile Manipulation
Abstract: We present Skill Transformer, an approach for solving long-horizon robotic tasks by combining conditional sequence modeling and skill modularity. Conditioned on egocentric and proprioceptive observations of a robot, Skill Transformer is tra... | [] | Train |
29,640 | 8 | Title: Experimental Demonstration of ML-Based DWDM System Margin Estimation
Abstract: SNR margins between partially and fully loaded DWDM systems are estimated without detailed knowledge of the network. The ML model, trained on simulation data, achieves accurate predictions on experimental data with an RMSE of 0.16 dB. | [
46
] | Train |
29,641 | 10 | Title: Minimizing Age of Information for Mobile Edge Computing Systems: A Nested Index Approach
Abstract: Exploiting the computational heterogeneity of mobile devices and edge nodes, mobile edge computation (MEC) provides an efficient approach to achieving real-time applications that are sensitive to information freshn... | [] | Train |
29,642 | 10 | Title: Improving LaCAM for Scalable Eventually Optimal Multi-Agent Pathfinding
Abstract: This study extends the recently-developed LaCAM algorithm for multi-agent pathfinding (MAPF). LaCAM is a sub-optimal search-based algorithm that uses lazy successor generation to dramatically reduce the planning effort. We present ... | [
1685,
1359
] | Train |
29,643 | 27 | Title: Reinforcement Learning in Robotic Motion Planning by Combined Experience-based Planning and Self-Imitation Learning
Abstract: High-quality and representative data is essential for both Imitation Learning (IL)- and Reinforcement Learning (RL)-based motion planning tasks. For real robots, it is challenging to coll... | [
19814
] | Validation |
29,644 | 4 | Title: RowPress: Amplifying Read Disturbance in Modern DRAM Chips
Abstract: Memory isolation is critical for system reliability, security, and safety. Unfortunately, read disturbance can break memory isolation in modern DRAM chips. For example, RowHammer is awell-studied read-disturb phenomenon where repeatedly opening... | [
12482,
5339,
7108,
34174
] | Train |
29,645 | 6 | Title: PromptCrafter: Crafting Text-to-Image Prompt through Mixed-Initiative Dialogue with LLM
Abstract: Text-to-image generation model is able to generate images across a diverse range of subjects and styles based on a single prompt. Recent works have proposed a variety of interaction methods that help users understan... | [] | Train |
29,646 | 16 | Title: STU-Net: Scalable and Transferable Medical Image Segmentation Models Empowered by Large-Scale Supervised Pre-training
Abstract: Large-scale models pre-trained on large-scale datasets have profoundly advanced the development of deep learning. However, the state-of-the-art models for medical image segmentation are... | [
42022,
22713,
19907,
37070
] | Validation |
29,647 | 36 | Title: Bicriteria Multidimensional Mechanism Design with Side Information
Abstract: We develop a versatile new methodology for multidimensional mechanism design that incorporates side information about agent types with the bicriteria goal of generating high social welfare and high revenue simultaneously. Side informati... | [
33496
] | Train |
29,648 | 24 | Title: Distributed Extra-gradient with Optimal Complexity and Communication Guarantees
Abstract: We consider monotone variational inequality (VI) problems in multi-GPU settings where multiple processors/workers/clients have access to local stochastic dual vectors. This setting includes a broad range of important proble... | [] | Test |
29,649 | 16 | Title: Vision Transformer Pruning Via Matrix Decomposition
Abstract: This is a further development of Vision Transformer Pruning via matrix decomposition. The purpose of the Vision Transformer Pruning is to prune the dimension of the linear projection of the dataset by learning their associated importance score in orde... | [
45783
] | Train |
29,650 | 30 | Title: Why Does Zero-Shot Cross-Lingual Generation Fail? An Explanation and a Solution
Abstract: Zero-shot cross-lingual transfer is when a multilingual model is trained to perform a task in one language and then is applied to another language. Although the zero-shot cross-lingual transfer approach has achieved success... | [] | Test |
29,651 | 30 | Title: Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages
Abstract: While impressive performance has been achieved on the task of Answer Sentence Selection (AS2) for English, the same does not hold for languages that lack large labeled datasets. In this work, we propose Cross-L... | [] | Train |
29,652 | 24 | Title: Language Models for Novelty Detection in System Call Traces
Abstract: Due to the complexity of modern computer systems, novel and unexpected behaviors frequently occur. Such deviations are either normal occurrences, such as software updates and new user activities, or abnormalities, such as misconfigurations, la... | [] | Validation |
29,653 | 17 | Title: Scalable Hypergraph Visualization
Abstract: Hypergraph visualization has many applications in network data analysis. Recently, a polygon-based representation for hypergraphs has been proposed with demonstrated benefits. However, the polygon-based layout often suffers from excessive self-intersections when the in... | [] | Train |
29,654 | 24 | Title: Predicting Out-of-Distribution Error with Confidence Optimal Transport
Abstract: Out-of-distribution (OOD) data poses serious challenges in deployed machine learning models as even subtle changes could incur significant performance drops. Being able to estimate a model's performance on test data is important in ... | [
7782
] | Train |
29,655 | 24 | Title: Twice Regularized Markov Decision Processes: The Equivalence between Robustness and Regularization
Abstract: Robust Markov decision processes (MDPs) aim to handle changing or partially known system dynamics. To solve them, one typically resorts to robust optimization methods. However, this significantly increase... | [] | Train |
29,656 | 16 | Title: StageInteractor: Query-based Object Detector with Cross-stage Interaction
Abstract: Previous object detectors make predictions based on dense grid points or numerous preset anchors. Most of these detectors are trained with one-to-many label assignment strategies. On the contrary, recent query-based object detect... | [
41765,
26231
] | Train |
29,657 | 24 | Title: Decoupled Rationalization with Asymmetric Learning Rates: A Flexible Lipschitz Restraint
Abstract: A self-explaining rationalization model is generally constructed by a cooperative game where a generator selects the most human-intelligible pieces from the input text as rationales, followed by a predictor that ma... | [
25309
] | Train |
29,658 | 4 | Title: Correlated Pseudorandomness from the Hardness of Quasi-Abelian Decoding
Abstract: Secure computation often benefits from the use of correlated randomness to achieve fast, non-cryptographic online protocols. A recent paradigm put forth by Boyle $\textit{et al.}$ (CCS 2018, Crypto 2019) showed how pseudorandom cor... | [
8627
] | Train |
29,659 | 27 | Title: Sim-on-Wheels: Physical World in the Loop Simulation for Self-Driving
Abstract: We present Sim-on-Wheels, a safe, realistic, and vehicle-in-loop framework to test autonomous vehicles' performance in the real world under safety-critical scenarios. Sim-on-wheels runs on a self-driving vehicle operating in the phys... | [] | Test |
29,660 | 28 | Title: Quantized-Constraint Concatenation and the Covering Radius of Constrained Systems
Abstract: We introduce a novel framework for implementing error-correction in constrained systems. The main idea of our scheme, called Quantized-Constraint Concatenation (QCC), is to employ a process of embedding the codewords of a... | [] | Train |
29,661 | 24 | Title: Model-to-Circuit Cross-Approximation For Printed Machine Learning Classifiers
Abstract: Printed electronics (PE) promises on-demand fabrication, low non-recurring engineering costs, and sub-cent fabrication costs. It also allows for high customization that would be infeasible in silicon, and bespoke architecture... | [
19577
] | Train |
29,662 | 30 | Title: AMOM: Adaptive Masking over Masking for Conditional Masked Language Model
Abstract: Transformer-based autoregressive (AR) methods have achieved appealing performance for varied sequence-to-sequence generation tasks, e.g., neural machine translation, summarization, and code generation, but suffer from low inferen... | [] | Test |
29,663 | 16 | Title: Neural World Models for Computer Vision
Abstract: Humans navigate in their environment by learning a mental model of the world through passive observation and active interaction. Their world model allows them to anticipate what might happen next and act accordingly with respect to an underlying objective. Such w... | [
8084,
29415
] | Test |
29,664 | 30 | Title: Investigating Pre-trained Language Models on Cross-Domain Datasets, a Step Closer to General AI
Abstract: Pre-trained language models have recently emerged as a powerful tool for fine-tuning a variety of language tasks. Ideally, when models are pre-trained on large amount of data, they are expected to gain impli... | [] | Test |
29,665 | 27 | Title: VERF: Runtime Monitoring of Pose Estimation with Neural Radiance Fields
Abstract: We present VERF, a collection of two methods (VERF-PnP and VERF-Light) for providing runtime assurance on the correctness of a camera pose estimate of a monocular camera without relying on direct depth measurements. We leverage the... | [
42504,
27173,
4526
] | Validation |
29,666 | 5 | Title: Testing Spreading Behavior in Networks with Arbitrary Topologies
Abstract: Inspired by the works of Goldreich and Ron (J. ACM, 2017) and Nakar and Ron (ICALP, 2021), we initiate the study of property testing in dynamic environments with arbitrary topologies. Our focus is on the simplest non-trivial rule that can... | [
28754
] | Train |
29,667 | 10 | Title: Clarifying System 1 & 2 through the Common Model of Cognition
Abstract: There have been increasing challenges to dual-system descriptions of System-1 and System-2, critiquing them as imprecise and fostering misconceptions. We address these issues here by way of Dennett's appeal to use computational thinking as a... | [] | Validation |
29,668 | 28 | Title: STAR-RIS-UAV Aided Coordinated Multipoint Cellular System for Multi-user Networks
Abstract: Different from conventional reconfigurable intelligent surfaces (RIS), simultaneous transmitting and reflecting RIS (STAR-RIS) can reflect and transmit signals to the receiver. In this paper, to serve more ground users an... | [] | Train |
29,669 | 24 | Title: ADLER - An efficient Hessian-based strategy for adaptive learning rate
Abstract: We derive a sound positive semi-definite approximation of the Hessian of deep models for which Hessian-vector products are easily computable. This enables us to provide an adaptive SGD learning rate strategy based on the minimizatio... | [] | Train |
29,670 | 16 | Title: A systematic study of the foreground-background imbalance problem in deep learning for object detection
Abstract: The class imbalance problem in deep learning has been explored in several studies, but there has yet to be a systematic analysis of this phenomenon in object detection. Here, we present comprehensive... | [] | Train |
29,671 | 24 | Title: A Combinatorial Characterization of Online Learning Games with Bounded Losses
Abstract: We study the online learnability of hypothesis classes with respect to arbitrary, but bounded, loss functions. We give a new scale-sensitive combinatorial dimension, named the sequential Minimax dimension, and show that it gi... | [
39953,
35812,
8950,
9703
] | Validation |
29,672 | 10 | Title: Top-Down Network Combines Back-Propagation with Attention
Abstract: Cortical processing, in vision and other domains, combines bottom-up (BU) with extensive top-down (TD) processing. Two primary goals attributed to TD processing are learning and directing attention. These two roles are accomplished in current ne... | [
16688
] | Train |
29,673 | 27 | Title: IMU-based Online Multi-lidar Calibration
Abstract: Modern autonomous systems typically use several sensors for perception. For best performance, accurate and reliable extrinsic calibration is necessary. In this research, we propose a reliable technique for the extrinsic calibration of several lidars on a vehicle... | [] | Train |
29,674 | 27 | Title: GelSight Svelte: A Human Finger-shaped Single-camera Tactile Robot Finger with Large Sensing Coverage and Proprioceptive Sensing
Abstract: Camera-based tactile sensing is a low-cost, popular approach to obtain highly detailed contact geometry information. However, most existing camera-based tactile sensors are f... | [
28542
] | Train |
29,675 | 3 | Title: Can Telematics Improve Driving Style? The Use of Behavioural Data in Motor Insurance
Abstract: The use of behavioural data in insurance is loaded with promises and unresolved issues. This paper explores the related opportunities and challenges analysing the use of telematics data in third-party liability motor i... | [] | Train |
29,676 | 27 | Title: AI-based Agents for Automated Robotic Endovascular Guidewire Manipulation
Abstract: An endovascular guidewire manipulation is essential for minimally-invasive clinical applications; Percutaneous Coronary Intervention (PCI) is used to open narrowed coronary arteries and restore arterial blood flow to heart tissue... | [] | Train |
29,677 | 30 | Title: Interpretable Bangla Sarcasm Detection using BERT and Explainable AI
Abstract: A positive phrase or a sentence with an underlying negative motive is usually defined as sarcasm that is widely used in today's social media platforms such as Facebook, Twitter, Reddit, etc. In recent times active users in social medi... | [] | Train |
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