Split (2)

train · 433k rows

id stringlengths 9 16	title stringlengths 4 278	abstract stringlengths 3 4.08k	cs.HC bool 2 classes	cs.CE bool 2 classes	cs.SD bool 2 classes	cs.SI bool 2 classes	cs.AI bool 2 classes	cs.IR bool 2 classes	cs.LG bool 2 classes	cs.RO bool 2 classes	cs.CL bool 2 classes	cs.IT bool 2 classes	cs.SY bool 2 classes	cs.CV bool 2 classes	cs.CR bool 2 classes	cs.CY bool 2 classes	cs.MA bool 2 classes	cs.NE bool 2 classes	cs.DB bool 2 classes	Other bool 2 classes	__index_level_0__ int64 0 541k
2410.09412	FB-Bench: A Fine-Grained Multi-Task Benchmark for Evaluating LLMs' Responsiveness to Human Feedback	Human feedback is crucial in the interactions between humans and Large Language Models (LLMs). However, existing research primarily focuses on benchmarking LLMs in single-turn dialogues. Even in benchmarks designed for multi-turn dialogues, the user inputs are often independent, neglecting the nuanced and complex natur...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	497,584
2408.05025	Rag and Roll: An End-to-End Evaluation of Indirect Prompt Manipulations in LLM-based Application Frameworks	Retrieval Augmented Generation (RAG) is a technique commonly used to equip models with out of distribution knowledge. This process involves collecting, indexing, retrieving, and providing information to an LLM for generating responses. Despite its growing popularity due to its flexibility and low cost, the security imp...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	479,621
2408.08754	Self-Explainable Graph Transformer for Link Sign Prediction	Signed Graph Neural Networks (SGNNs) have been shown to be effective in analyzing complex patterns in real-world situations where positive and negative links coexist. However, SGNN models suffer from poor explainability, which limit their adoptions in critical scenarios that require understanding the rationale behind p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	481,138
1711.08833	Deep Learning for Real-Time Crime Forecasting and its Ternarization	Real-time crime forecasting is important. However, accurate prediction of when and where the next crime will happen is difficult. No known physical model provides a reasonable approximation to such a complex system. Historical crime data are sparse in both space and time and the signal of interests is weak. In this wor...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	85,280
2404.09486	MMCode: Benchmarking Multimodal Large Language Models for Code Generation with Visually Rich Programming Problems	Programming often involves converting detailed and complex specifications into code, a process during which developers typically utilize visual aids to more effectively convey concepts. While recent developments in Large Multimodal Models have demonstrated remarkable abilities in visual reasoning and mathematical tasks...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	true	446,696
cmp-lg/9410013	Automatic Error Detection in Part of Speech Tagging	A technique for detecting errors made by Hidden Markov Model taggers is described, based on comparing observable values of the tagging process with a threshold. The resulting approach allows the accuracy of the tagger to be improved by accepting a lower efficiency, defined as the proportion of words which are tagged. E...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,195
1907.03381	Travel Time Estimation without Road Networks: An Urban Morphological Layout Representation Approach	Travel time estimation is a crucial task for not only personal travel scheduling but also city planning. Previous methods focus on modeling toward road segments or sub-paths, then summing up for a final prediction, which have been recently replaced by deep neural models with end-to-end training. Usually, these methods ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	137,846
2304.00242	GLT-T++: Global-Local Transformer for 3D Siamese Tracking with Ranking Loss	Siamese trackers based on 3D region proposal network (RPN) have shown remarkable success with deep Hough voting. However, using a single seed point feature as the cue for voting fails to produce high-quality 3D proposals. Additionally, the equal treatment of seed points in the voting process, regardless of their signif...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	355,613
2010.15347	Distance Invariant Sparse Autoencoder for Wireless Signal Strength Mapping	Wireless signal strength based localization can enable robust localization for robots using inexpensive sensors. For this, a location-to-signal-strength map has to be learned for each access point in the environment. Due to the ubiquity of Wireless networks in most environments, this can result in tens or hundreds of m...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	203,738
2405.04026	Federated Control in Markov Decision Processes	We study problems of federated control in Markov Decision Processes. To solve an MDP with large state space, multiple learning agents are introduced to collaboratively learn its optimal policy without communication of locally collected experience. In our settings, these agents have limited capabilities, which means the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	452,412
2101.08248	Data-to-text Generation by Splicing Together Nearest Neighbors	We propose to tackle data-to-text generation tasks by directly splicing together retrieved segments of text from "neighbor" source-target pairs. Unlike recent work that conditions on retrieved neighbors but generates text token-by-token, left-to-right, we learn a policy that directly manipulates segments of neighbor te...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	216,269
2306.03293	Towards Fairness in Personalized Ads Using Impression Variance Aware Reinforcement Learning	Variances in ad impression outcomes across demographic groups are increasingly considered to be potentially indicative of algorithmic bias in personalized ads systems. While there are many definitions of fairness that could be applicable in the context of personalized systems, we present a framework which we call the V...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	371,263
2208.09818	Rate-Splitting Multiple Access for Intelligent Reflecting Surface-Aided Secure Transmission	In this letter, we study a rate-splitting multiple access (RSMA)-based intelligent reflecting surface (IRS)-aided multi-user multiple-input single-output (MISO) secure communication system with a potential eavesdropper (Eve). Aiming to maximize the minimum secrecy rate (SR) among all the legitimate users (LUs), a desig...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	313,845
1601.04460	Consequences of nonconformist behaviors in a continuous opinion model	We investigate opinion formation in a kinetic exchange opinion model, where opinions are represented by numbers in the real interval $[-1,1]$ and agents are typified by the individual degree of conviction about the opinion that they support. Opinions evolve through pairwise interactions governed by competitive positive...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	51,020
2402.04616	Beyond Answers: Transferring Reasoning Capabilities to Smaller LLMs Using Multi-Teacher Knowledge Distillation	Transferring the reasoning capability from stronger large language models (LLMs) to smaller ones has been quite appealing, as smaller LLMs are more flexible to deploy with less expense. Among the existing solutions, knowledge distillation stands out due to its outstanding efficiency and generalization. However, existin...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	427,528
2210.12216	Feature Engineering and Classification Models for Partial Discharge in Power Transformers	To ensure reliability, power transformers are monitored for partial discharge (PD) events, which are symptoms of transformer failure. Since failures can have catastrophic cascading consequences, it is critical to preempt them as early as possible. Our goal is to classify PDs as corona, floating, particle, or void, to g...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	325,635
1810.08438	Coordinated exploration for labyrinthine environments with application to the Pursuit-Evasion problem	This paper introduces a multirobot cooperation approach to solve the "pursuit evasion" problem for mobile robots that have omnidirectional vision sensors. The main characteristic of this approach is to implement a real cooperation between robots based on knowledge sharing and makes them work as a team. A complete algor...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	110,826
2210.10562	Research on Hermitian self-dual codes, GRS codes and EGRS codes	MDS self-dual codes have nice algebraic structures, theoretical significance and practical implications. In this paper, we present three classes of $q^2$-ary Hermitian self-dual (extended) generalized Reed-Solomon codes with different code locators. Combining the results in Ball et al. (Designs, Codes and Cryptography,...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	324,970
1610.07365	Introduction: Cognitive Issues in Natural Language Processing	This special issue is dedicated to get a better picture of the relationships between computational linguistics and cognitive science. It specifically raises two questions: "what is the potential contribution of computational language modeling to cognitive science?" and conversely: "what is the influence of cognitive sc...	true	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	62,777
1110.2724	Information Transfer in Social Media	Recent research has explored the increasingly important role of social media by examining the dynamics of individual and group behavior, characterizing patterns of information diffusion, and identifying influential individuals. In this paper we suggest a measure of causal relationships between nodes based on the inform...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	12,604
2009.02752	Simultaneous Energy Harvesting and Gait Recognition using Piezoelectric Energy Harvester	Piezoelectric energy harvester, which generates electricity from stress or vibrations, is gaining increasing attention as a viable solution to extend battery life in wearables. Recent research further reveals that, besides generating energy, PEH can also serve as a passive sensor to detect human gait power-efficiently ...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	194,649
2004.09036	Gated Convolutional Bidirectional Attention-based Model for Off-topic Spoken Response Detection	Off-topic spoken response detection, the task aiming at predicting whether a response is off-topic for the corresponding prompt, is important for an automated speaking assessment system. In many real-world educational applications, off-topic spoken response detectors are required to achieve high recall for off-topic re...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	173,237
2310.13203	A Study of Fitness Gains in Evolving Finite State Machines	Among the wide variety of evolutionary computing models, Finite State Machines (FSMs) have several attractions for fundamental research. They are easy to understand in concept and can be visualised clearly in simple cases. They have a ready fitness criterion through their relationship with Regular Languages. They have ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	401,333
2412.01709	Query Performance Explanation through Large Language Model for HTAP Systems	In hybrid transactional and analytical processing (HTAP) systems, users often struggle to understand why query plans from one engine (OLAP or OLTP) perform significantly slower than those from another. Although optimizers provide plan details via the EXPLAIN function, these explanations are frequently too technical for...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	513,227
2403.12223	HRI in Indian Education: Challenges Opportunities	With the recent advancements in the field of robotics and the increased focus on having general-purpose robots widely available to the general public, it has become increasingly necessary to pursue research into Human-robot interaction (HRI). While there have been a lot of works discussing frameworks for teaching HRI i...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	439,085
2412.02802	Flattering to Deceive: The Impact of Sycophantic Behavior on User Trust in Large Language Model	Sycophancy refers to the tendency of a large language model to align its outputs with the user's perceived preferences, beliefs, or opinions, in order to look favorable, regardless of whether those statements are factually correct. This behavior can lead to undesirable consequences, such as reinforcing discriminatory b...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	513,683
2205.08001	Towards Debiasing Translation Artifacts	Cross-lingual natural language processing relies on translation, either by humans or machines, at different levels, from translating training data to translating test sets. However, compared to original texts in the same language, translations possess distinct qualities referred to as translationese. Previous research ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	296,785
2309.04085	ECoDe: A Sample-Efficient Method for Co-Design of Robotic Agents	Co-designing autonomous robotic agents involves simultaneously optimizing the controller and physical design of the agent. Its inherent bi-level optimization formulation necessitates an outer loop design optimization driven by an inner loop control optimization. This can be challenging when the design space is large an...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	390,608
1804.10855	Evaluation of Feature Detector-Descriptor for Real Object Matching under Various Conditions of Ilumination and Affine Transformation	This study attempts to provide explanations, descriptions and evaluations of some most popular and current combinations of description and descriptor frameworks, namely SIFT, SURF, MSER, and BRISK for keypoint extractors and SIFT, SURF, BRISK, and FREAK for descriptors. Evaluations are made based on the number of match...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	96,246
1703.07216	The Effect of Phasor Measurement Units on the Accuracy of the Network Estimated Variables	The most commonly used weighted least square state estimator in power industry is nonlinear and formulated by using conventional measurements such as line flow and injection measurements. PMUs (Phasor Measurement Units) are gradually adding them to improve the state estimation process. In this paper the way of corporat...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	70,355
2402.08255	Distal Interference: Exploring the Limits of Model-Based Continual Learning	Continual learning is the sequential learning of different tasks by a machine learning model. Continual learning is known to be hindered by catastrophic interference or forgetting, i.e. rapid unlearning of earlier learned tasks when new tasks are learned. Despite their practical success, artificial neural networks (ANN...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	429,033
2005.01663	A second-order face-centred finite volume method on general meshes with automatic mesh adaptation	A second-order face-centred finite volume strategy on general meshes is proposed. The method uses a mixed formulation in which a constant approximation of the unknown is computed on the faces of the mesh. Such information is then used to solve a set of problems, independent cell-by-cell, to retrieve the local values of...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	175,647
2004.05768	Sequential Weakly Labeled Multi-Activity Localization and Recognition on Wearable Sensors using Recurrent Attention Networks	With the popularity and development of the wearable devices such as smartphones, human activity recognition (HAR) based on sensors has become as a key research area in human computer interaction and ubiquitous computing. The emergence of deep learning leads to a recent shift in the research of HAR, which requires massi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	172,305
1810.08727	Condition Number Analysis of Logistic Regression, and its Implications for Standard First-Order Solution Methods	Logistic regression is one of the most popular methods in binary classification, wherein estimation of model parameters is carried out by solving the maximum likelihood (ML) optimization problem, and the ML estimator is defined to be the optimal solution of this problem. It is well known that the ML estimator exists wh...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	110,898
2003.00214	Channel Equilibrium Networks for Learning Deep Representation	Convolutional Neural Networks (CNNs) are typically constructed by stacking multiple building blocks, each of which contains a normalization layer such as batch normalization (BN) and a rectified linear function such as ReLU. However, this work shows that the combination of normalization and rectified linear function le...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	166,228
1807.08998	Cross-lingual Argumentation Mining: Machine Translation (and a bit of Projection) is All You Need!	Argumentation mining (AM) requires the identification of complex discourse structures and has lately been applied with success monolingually. In this work, we show that the existing resources are, however, not adequate for assessing cross-lingual AM, due to their heterogeneity or lack of complexity. We therefore create...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	103,642
1711.10742	Pipeline Generative Adversarial Networks for Facial Images Generation with Multiple Attributes	Generative Adversarial Networks are proved to be efficient on various kinds of image generation tasks. However, it is still a challenge if we want to generate images precisely. Many researchers focus on how to generate images with one attribute. But image generation under multiple attributes is still a tough work. In t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	85,661
2308.06672	A practical PINN framework for multi-scale problems with multi-magnitude loss terms	For multi-scale problems, the conventional physics-informed neural networks (PINNs) face some challenges in obtaining available predictions. In this paper, based on PINNs, we propose a practical deep learning framework for multi-scale problems by reconstructing the loss function and associating it with special neural n...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	385,219
2109.08829	Self-Adaptive Partial Domain Adaptation	Partial Domain adaptation (PDA) aims to solve a more practical cross-domain learning problem that assumes target label space is a subset of source label space. However, the mismatched label space causes significant negative transfer. A traditional solution is using soft weights to increase weights of source shared doma...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	256,034
2008.01139	Characterizing Communities of Hashtag Usage on Twitter During the 2020 COVID-19 Pandemic by Multi-view Clustering	The COVID-19 pandemic has produced a flurry of online activity on social media sites. As such, analysis of social media data during the COVID-19 pandemic can produce unique insights into discussion topics and how those topics evolve over the course of the pandemic. In this study, we propose analyzing discussion topics ...	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	190,205
2407.05213	BadCLM: Backdoor Attack in Clinical Language Models for Electronic Health Records	The advent of clinical language models integrated into electronic health records (EHR) for clinical decision support has marked a significant advancement, leveraging the depth of clinical notes for improved decision-making. Despite their success, the potential vulnerabilities of these models remain largely unexplored. ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	470,871
2003.06009	Isochronous Architecture-Based Voltage-Active Power Droop for Multi-Inverter Systems	Advanced microgrids consisting of distributed energy resources interfaced with multi-inverter systems are becoming more common. Consequently, the effectiveness of voltage and frequency regulation in microgrids using conventional droop-based methodologies is challenged by uncertainty in the sizeand schedule of loads. Th...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	168,004
2103.13372	Affective Processes: stochastic modelling of temporal context for emotion and facial expression recognition	Temporal context is key to the recognition of expressions of emotion. Existing methods, that rely on recurrent or self-attention models to enforce temporal consistency, work on the feature level, ignoring the task-specific temporal dependencies, and fail to model context uncertainty. To alleviate these issues, we build...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	226,466
2303.05581	Open World Classification with Adaptive Negative Samples	Open world classification is a task in natural language processing with key practical relevance and impact. Since the open or {\em unknown} category data only manifests in the inference phase, finding a model with a suitable decision boundary accommodating for the identification of known classes and discrimination of t...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	350,515
2212.03029	AbHE: All Attention-based Homography Estimation	Homography estimation is a basic computer vision task, which aims to obtain the transformation from multi-view images for image alignment. Unsupervised learning homography estimation trains a convolution neural network for feature extraction and transformation matrix regression. While the state-of-theart homography met...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	334,972
2402.02139	Using Deep Ensemble Forest for High Resolution Mapping of PM2.5 from MODIS MAIAC AOD in Tehran, Iran	High resolution mapping of PM2.5 concentration over Tehran city is challenging because of the complicated behavior of numerous sources of pollution and the insufficient number of ground air quality monitoring stations. Alternatively, high resolution satellite Aerosol Optical Depth (AOD) data can be employed for high re...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	426,402
2203.03917	An Analysis of Measure-Valued Derivatives for Policy Gradients	Reinforcement learning methods for robotics are increasingly successful due to the constant development of better policy gradient techniques. A precise (low variance) and accurate (low bias) gradient estimator is crucial to face increasingly complex tasks. Traditional policy gradient algorithms use the likelihood-ratio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	284,276
2011.00697	Time Series Forecasting with Stacked Long Short-Term Memory Networks	Long Short-Term Memory (LSTM) networks are often used to capture temporal dependency patterns. By stacking multi-layer LSTM networks, it can capture even more complex patterns. This paper explores the effectiveness of applying stacked LSTM networks in the time series prediction domain, specifically, the traffic volume ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	204,332
2502.12366	ScriptoriumWS: A Code Generation Assistant for Weak Supervision	Weak supervision is a popular framework for overcoming the labeled data bottleneck: the need to obtain labels for training data. In weak supervision, multiple noisy-but-cheap sources are used to provide guesses of the label and are aggregated to produce high-quality pseudolabels. These sources are often expressed as sm...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	534,824
2206.07767	Kantorovich Strikes Back! Wasserstein GANs are not Optimal Transport?	Wasserstein Generative Adversarial Networks (WGANs) are the popular generative models built on the theory of Optimal Transport (OT) and the Kantorovich duality. Despite the success of WGANs, it is still unclear how well the underlying OT dual solvers approximate the OT cost (Wasserstein-1 distance, $\mathbb{W}_{1}$) an...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	302,875
2408.03946	Prompting for products: Investigating design space exploration strategies for text-to-image generative models	Text-to-image models are enabling efficient design space exploration, rapidly generating images from text prompts. However, many generative AI tools are imperfect for product design applications as they are not built for the goals and requirements of product design. The unclear link between text input and image output ...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	479,205
2009.05161	Multi-Goal Multi-Agent Path Finding via Decoupled and Integrated Goal Vertex Ordering	We introduce multi-goal multi agent path finding (MAPF$^{MG}$) which generalizes the standard discrete multi-agent path finding (MAPF) problem. While the task in MAPF is to navigate agents in an undirected graph from their starting vertices to one individual goal vertex per agent, MAPF$^{MG}$ assigns each agent multipl...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	195,238
2209.13569	Exploring Low Rank Training of Deep Neural Networks	Training deep neural networks in low rank, i.e. with factorised layers, is of particular interest to the community: it offers efficiency over unfactorised training in terms of both memory consumption and training time. Prior work has focused on low rank approximations of pre-trained networks and training in low rank sp...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	319,950
2009.07691	Hardware-Assisted Detection of Firmware Attacks in Inverter-Based Cyberphysical Microgrids	The electric grid modernization effort relies on the extensive deployment of microgrid (MG) systems. MGs integrate renewable resources and energy storage systems, allowing to generate economic and zero-carbon footprint electricity, deliver sustainable energy to communities using local energy resources, and enhance grid...	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	196,016
2401.05566	Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training	Humans are capable of strategically deceptive behavior: behaving helpfully in most situations, but then behaving very differently in order to pursue alternative objectives when given the opportunity. If an AI system learned such a deceptive strategy, could we detect it and remove it using current state-of-the-art safet...	false	false	false	false	true	false	true	false	true	false	false	false	true	false	false	false	false	true	420,830
2203.07908	Panoptic SwiftNet: Pyramidal Fusion for Real-time Panoptic Segmentation	Dense panoptic prediction is a key ingredient in many existing applications such as autonomous driving, automated warehouses or remote sensing. Many of these applications require fast inference over large input resolutions on affordable or even embedded hardware. We propose to achieve this goal by trading off backbone ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	285,602
2110.12370	Team Enigma at ArgMining-EMNLP 2021: Leveraging Pre-trained Language Models for Key Point Matching	We present the system description for our submission towards the Key Point Analysis Shared Task at ArgMining 2021. Track 1 of the shared task requires participants to develop methods to predict the match score between each pair of arguments and keypoints, provided they belong to the same topic under the same stance. We...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	262,823
1906.10282	Saliency-driven Word Alignment Interpretation for Neural Machine Translation	Despite their original goal to jointly learn to align and translate, Neural Machine Translation (NMT) models, especially Transformer, are often perceived as not learning interpretable word alignments. In this paper, we show that NMT models do learn interpretable word alignments, which could only be revealed with proper...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	136,398
1908.05030	Computing and Communicating Functions in Disorganized Wireless Networks	For future wireless networks, enormous numbers of interconnections are required, creating a disorganized topology and leading to a great challenge in data aggregation. Instead of collecting data individually, a more efficient technique, computation over multi-access channels (CoMAC), has emerged to compute functions by...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	141,629
2001.11691	Self-Adversarial Learning with Comparative Discrimination for Text Generation	Conventional Generative Adversarial Networks (GANs) for text generation tend to have issues of reward sparsity and mode collapse that affect the quality and diversity of generated samples. To address the issues, we propose a novel self-adversarial learning (SAL) paradigm for improving GANs' performance in text generati...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	162,137
2502.02487	Hier-EgoPack: Hierarchical Egocentric Video Understanding with Diverse Task Perspectives	Our comprehension of video streams depicting human activities is naturally multifaceted: in just a few moments, we can grasp what is happening, identify the relevance and interactions of objects in the scene, and forecast what will happen soon, everything all at once. To endow autonomous systems with such a holistic pe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	530,341
1208.3700	Synthetic Aperture Radar Imaging and Motion Estimation via Robust Principle Component Analysis	We consider the problem of synthetic aperture radar (SAR) imaging and motion estimation of complex scenes. By complex we mean scenes with multiple targets, stationary and in motion. We use the usual setup with one moving antenna emitting and receiving signals. We address two challenges: (1) the detection of moving targ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	18,129
2203.12224	Efficient Few-Shot Object Detection via Knowledge Inheritance	Few-shot object detection (FSOD), which aims at learning a generic detector that can adapt to unseen tasks with scarce training samples, has witnessed consistent improvement recently. However, most existing methods ignore the efficiency issues, e.g., high computational complexity and slow adaptation speed. Notably, eff...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	287,189
2409.03028	Rigid-Body Attitude Control on $\mathsf{SO(3)}$ using Nonlinear Dynamic Inversion	This paper presents a cascaded control architecture, based on nonlinear dynamic inversion (NDI), for rigid body attitude control. The proposed controller works directly with the rotation matrix parameterization, that is, with elements of the Special Orthogonal Group $\mathsf{SO(3)}$, and avoids problems related to sing...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	485,898
2001.01596	Deep learning for brake squeal: vibration detection, characterization and prediction	Despite significant advances in modeling of friction-induced vibrations and brake squeal, the majority of industrial research and design is still conducted experimentally, since many aspects of squeal and its mechanisms involved remain unknown. We report here for the first time on novel strategies for handling data-int...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	159,529
2402.14158	TOOLVERIFIER: Generalization to New Tools via Self-Verification	Teaching language models to use tools is an important milestone towards building general assistants, but remains an open problem. While there has been significant progress on learning to use specific tools via fine-tuning, language models still struggle with learning how to robustly use new tools from only a few demons...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	431,552
1404.7734	Compact Argumentation Frameworks	Abstract argumentation frameworks (AFs) are one of the most studied formalisms in AI. In this work, we introduce a certain subclass of AFs which we call compact. Given an extension-based semantics, the corresponding compact AFs are characterized by the feature that each argument of the AF occurs in at least one extensi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	32,718
2012.08496	Spectral Methods for Data Science: A Statistical Perspective	Spectral methods have emerged as a simple yet surprisingly effective approach for extracting information from massive, noisy and incomplete data. In a nutshell, spectral methods refer to a collection of algorithms built upon the eigenvalues (resp. singular values) and eigenvectors (resp. singular vectors) of some prope...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	211,779
2206.13374	Stability Verification of Neural Network Controllers using Mixed-Integer Programming	We propose a framework for the stability verification of Mixed-Integer Linear Programming (MILP) representable control policies. This framework compares a fixed candidate policy, which admits an efficient parameterization and can be evaluated at a low computational cost, against a fixed baseline policy, which is known ...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	304,935
2009.14082	Attentional Feature Fusion	Feature fusion, the combination of features from different layers or branches, is an omnipresent part of modern network architectures. It is often implemented via simple operations, such as summation or concatenation, but this might not be the best choice. In this work, we propose a uniform and general scheme, namely a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	197,929
1908.01767	Exploring Neural Net Augmentation to BERT for Question Answering on SQUAD 2.0	Enhancing machine capabilities to answer questions has been a topic of considerable focus in recent years of NLP research. Language models like Embeddings from Language Models (ELMo)[1] and Bidirectional Encoder Representations from Transformers (BERT) [2] have been very successful in developing general purpose languag...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	140,843
2103.10426	Using latent space regression to analyze and leverage compositionality in GANs	In recent years, Generative Adversarial Networks have become ubiquitous in both research and public perception, but how GANs convert an unstructured latent code to a high quality output is still an open question. In this work, we investigate regression into the latent space as a probe to understand the compositional pr...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	225,448
1910.12521	On the Global Convergence of (Fast) Incremental Expectation Maximization Methods	The EM algorithm is one of the most popular algorithm for inference in latent data models. The original formulation of the EM algorithm does not scale to large data set, because the whole data set is required at each iteration of the algorithm. To alleviate this problem, Neal and Hinton have proposed an incremental ver...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	151,116
2206.14614	AGENT: An Adaptive Grouping Entrapping Method of Flocking Systems	This study proposes a distributed algorithm that makes agents' adaptive grouping entrap multiple targets via automatic decision making, smooth flocking, and well-distributed entrapping. Agents make their own decisions about which targets to surround based on environmental information. An improved artificial potential f...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	305,343
2409.07195	Perceptive Pedipulation with Local Obstacle Avoidance	Pedipulation leverages the feet of legged robots for mobile manipulation, eliminating the need for dedicated robotic arms. While previous works have showcased blind and task-specific pedipulation skills, they fail to account for static and dynamic obstacles in the environment. To address this limitation, we introduce a...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	487,425
2405.20397	Explainable Data-driven Modeling of Adsorption Energy in Heterogeneous Catalysis	The increasing popularity of machine learning (ML) in catalysis has spurred interest in leveraging these techniques to enhance catalyst design. Our study aims to bridge the gap between physics-based studies and data-driven methodologies by integrating ML techniques with eXplainable AI (XAI). Specifically, we employ two...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	459,323
2009.06538	Answering Multi-Dimensional Range Queries under Local Differential Privacy	In this paper, we tackle the problem of answering multi-dimensional range queries under local differential privacy. There are three key technical challenges: capturing the correlations among attributes, avoiding the curse of dimensionality, and dealing with the large domains of attributes. None of the existing approach...	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	true	195,678
2202.05163	Machine Learning and Data Science: Foundations, Concepts, Algorithms, and Tools	Today, data is a fuel for businesses to gain important insights and improve their performance. There is no industry in the world today that does not use data. But who will get this insight? Who processes all the raw data? Everything is done by a data analyst or a data scientist.	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	279,786
2010.02047	Discovering Object-Centric Petri Nets	Techniques to discover Petri nets from event data assume precisely one case identifier per event. These case identifiers are used to correlate events, and the resulting discovered Petri net aims to describe the life-cycle of individual cases. In reality, there is not one possible case notion, but multiple intertwined c...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	198,890
2401.00271	HybridGait: A Benchmark for Spatial-Temporal Cloth-Changing Gait Recognition with Hybrid Explorations	Existing gait recognition benchmarks mostly include minor clothing variations in the laboratory environments, but lack persistent changes in appearance over time and space. In this paper, we propose the first in-the-wild benchmark CCGait for cloth-changing gait recognition, which incorporates diverse clothing changes, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	418,934
2207.04585	A multi-level interpretable sleep stage scoring system by infusing experts' knowledge into a deep network architecture	In recent years, deep learning has shown potential and efficiency in a wide area including computer vision, image and signal processing. Yet, translational challenges remain for user applications due to a lack of interpretability of algorithmic decisions and results. This black box problem is particularly problematic f...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	307,244
1203.5612	Closed-Form Critical Conditions of Subharmonic Oscillations for Buck Converters	A general critical condition of subharmonic oscillation in terms of the loop gain is derived. Many closed-form critical conditions for various control schemes in terms of converter parameters are also derived. Some previously known critical conditions become special cases in the generalized framework. Given an arbitrar...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	15,122
1009.2464	Various virtual structures on single file system	The article provides a new approach to creating hierarchical structure of file system. First, it gives overview of the existing ways of storing files in current operating systems. Second, it describes the new way of building structures of a file system. This approach allows creating various structures by different attr...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	7,538
2004.10349	Textual Visual Semantic Dataset for Text Spotting	Text Spotting in the wild consists of detecting and recognizing text appearing in images (e.g. signboards, traffic signals or brands in clothing or objects). This is a challenging problem due to the complexity of the context where texts appear (uneven backgrounds, shading, occlusions, perspective distortions, etc.). On...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	173,612
2312.09806	Improving Biomedical Entity Linking with Retrieval-enhanced Learning	Biomedical entity linking (BioEL) has achieved remarkable progress with the help of pre-trained language models. However, existing BioEL methods usually struggle to handle rare and difficult entities due to long-tailed distribution. To address this limitation, we introduce a new scheme $k$NN-BioEL, which provides a Bio...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	415,892
2310.08084	Volumetric Medical Image Segmentation via Scribble Annotations and Shape Priors	Recently, weakly-supervised image segmentation using weak annotations like scribbles has gained great attention in computer vision and medical image analysis, since such annotations are much easier to obtain compared to time-consuming and labor-intensive labeling at the pixel/voxel level. However, due to a lack of stru...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	399,255
2408.01946	Masked Angle-Aware Autoencoder for Remote Sensing Images	To overcome the inherent domain gap between remote sensing (RS) images and natural images, some self-supervised representation learning methods have made promising progress. However, they have overlooked the diverse angles present in RS objects. This paper proposes the Masked Angle-Aware Autoencoder (MA3E) to perceive ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	478,433
1706.09770	New Lower Bounds on the Generalized Hamming Weights of AG Codes	A sharp upper bound for the maximum integer not belonging to an ideal of a numerical semigroup is given and the ideals attaining this bound are characterized. Then the result is used, through the so-called Feng-Rao numbers, to bound the generalized Hamming weights of algebraic-geometry codes. This is further developed ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	76,195
1507.03060	LooseCut: Interactive Image Segmentation with Loosely Bounded Boxes	One popular approach to interactively segment the foreground object of interest from an image is to annotate a bounding box that covers the foreground object. Then, a binary labeling is performed to achieve a refined segmentation. One major issue of the existing algorithms for such interactive image segmentation is the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	45,045
2412.03256	Electrode and electroactive polymer layout design using topology optimization	When electrically stimulated, electroactive polymers (EAPs) respond with mechanical deformation. The goal of this work is to design electrode and EAP layouts simultaneously in structures by using density-based, multi-material topology optimization. In this novel approach the layout of electrodes and EAP material are no...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	513,887
1304.5212	Object Tracking in Videos: Approaches and Issues	Mobile object tracking has an important role in the computer vision applications. In this paper, we use a tracked target-based taxonomy to present the object tracking algorithms. The tracked targets are divided into three categories: points of interest, appearance and silhouette of mobile objects. Advantages and limita...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	24,066
1208.1290	Scaling Behaviors of Wireless Device-to-Device Communications with Distributed Caching	We analyze a novel architecture for caching popular video content to enable wireless device-to-device collaboration. We focus on the asymptotic scaling characteristics and show how they depends on video content popularity statistics. We identify a fundamental conflict between collaboration distance and interference and...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	17,967
2403.05368	Exploring the Links between the Fundamental Lemma and Kernel Regression	Generalizations and variations of the fundamental lemma by Willems et al. are an active topic of recent research. In this note, we explore and formalize the links between kernel regression and some known nonlinear extensions of the fundamental lemma. Applying a transformation to the usual linear equation in Hankel matr...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	435,980
cs/9709101	Towards Flexible Teamwork	Many AI researchers are today striving to build agent teams for complex, dynamic multi-agent domains, with intended applications in arenas such as education, training, entertainment, information integration, and collective robotics. Unfortunately, uncertainties in these complex, dynamic domains obstruct coherent teamwo...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	540,366
1503.06087	The RatioLog Project: Rational Extensions of Logical Reasoning	Higher-level cognition includes logical reasoning and the ability of question answering with common sense. The RatioLog project addresses the problem of rational reasoning in deep question answering by methods from automated deduction and cognitive computing. In a first phase, we combine techniques from information ret...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	41,308
1807.11293	Improving Spatiotemporal Self-Supervision by Deep Reinforcement Learning	Self-supervised learning of convolutional neural networks can harness large amounts of cheap unlabeled data to train powerful feature representations. As surrogate task, we jointly address ordering of visual data in the spatial and temporal domain. The permutations of training samples, which are at the core of self-sup...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	104,153
1308.4786	An Investigation On Fuzzy Logic Controllers (TAKAGI-SUGENO & MAMDANI) In Inverse Pendulum System	The concept of controlling non-linear systems is one the significant fields in scientific researches for the purpose of which intelligent approaches can provide desirable applicability. Fuzzy systems are systems with ambiguous definition and fuzzy control is an especial type of non-linear control. Inverse pendulum syst...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	26,565
2110.07322	Modeling dynamic target deformation in camera calibration	Most approaches to camera calibration rely on calibration targets of well-known geometry. During data acquisition, calibration target and camera system are typically moved w.r.t. each other, to allow image coverage and perspective versatility. We show that moving the target can lead to small temporary deformations of t...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	260,941
2202.00569	Arrhythmia Classification using CGAN-augmented ECG Signals	ECG databases are usually highly imbalanced due to the abundance of Normal ECG and scarcity of abnormal cases. As such, deep learning classifiers trained on imbalanced datasets usually perform poorly, especially on minor classes. One solution is to generate realistic synthetic ECG signals using Generative Adversarial N...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	278,190
1511.04898	Fast clustering for scalable statistical analysis on structured images	The use of brain images as markers for diseases or behavioral differences is challenged by the small effects size and the ensuing lack of power, an issue that has incited researchers to rely more systematically on large cohorts. Coupled with resolution increases, this leads to very large datasets. A striking example in...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	48,964

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