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
1307.2756	Secure and Policy-Private Resource Sharing in an Online Social Network	Providing functionalities that allow online social network users to manage in a secure and private way the publication of their information and/or resources is a relevant and far from trivial topic that has been under scrutiny from various research communities. In this work, we provide a framework that allows users to ...	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	25,740
2206.08738	Detecting Adversarial Examples in Batches -- a geometrical approach	Many deep learning methods have successfully solved complex tasks in computer vision and speech recognition applications. Nonetheless, the robustness of these models has been found to be vulnerable to perturbed inputs or adversarial examples, which are imperceptible to the human eye, but lead the model to erroneous out...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	303,274
1512.05212	Reality Mining with Mobile Big Data: Understanding the Impact of Network Structure on Propagation Dynamics	Information and epidemic propagation dynamics in complex networks is truly important to discover and control terrorist attack and disease spread. How to track, recognize and model such dynamics is a big challenge. With the popularity of intellectualization and the rapid development of Internet of Things (IoT), massive ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	50,205
2201.10656	MGA-VQA: Multi-Granularity Alignment for Visual Question Answering	Learning to answer visual questions is a challenging task since the multi-modal inputs are within two feature spaces. Moreover, reasoning in visual question answering requires the model to understand both image and question, and align them in the same space, rather than simply memorize statistics about the question-ans...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	277,062
2410.02197	Beyond Bradley-Terry Models: A General Preference Model for Language Model Alignment	Modeling human preferences is crucial for aligning foundation models with human values. Traditional reward modeling methods, such as the Bradley-Terry (BT) reward model, fall short in expressiveness, particularly in addressing intransitive preferences. In this paper, we introduce preference embedding, an approach that ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	494,160
2010.06009	An Auto-Generated Geometry-Based Discrete Finite Element Model for Damage Evolution in Composite Laminates with Arbitrary Stacking Sequence	Stiffness degradation and progressive failure of composite laminates are complex processes involving evolution and multi-mode interactions among fiber fractures, intra-ply matrix cracks and inter-ply delaminations. This paper presents a novel finite element model capable of explicitly treating such discrete failures in...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	200,327
1702.04927	Sensor scheduling with time, energy and communication constraints	In this paper we present new algorithms and analysis for the linear inverse sensor placement and scheduling problems over multiple time instances with power and communications constraints. The proposed algorithms, which deal directly with minimizing the mean squared error (MSE), are based on the convex relaxation appro...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	68,329
2412.18845	Enhancing Federated Graph Learning via Adaptive Fusion of Structural and Node Characteristics	Federated Graph Learning (FGL) has demonstrated the advantage of training a global Graph Neural Network (GNN) model across distributed clients using their local graph data. Unlike Euclidean data (\eg, images), graph data is composed of nodes and edges, where the overall node-edge connections determine the topological s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	520,601
2112.09345	A prototype of quantum von Neumann architecture	A modern computer system, based on the von Neumann architecture, is a complicated system with several interactive modular parts. Quantum computing, as the most generic usage of quantum information, follows a hybrid architecture so far, namely, quantum algorithms are stored and controlled classically, and mainly the exe...	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	true	272,119
2412.04279	Targeted Hard Sample Synthesis Based on Estimated Pose and Occlusion Error for Improved Object Pose Estimation	6D Object pose estimation is a fundamental component in robotics enabling efficient interaction with the environment. It is particularly challenging in bin-picking applications, where objects may be textureless and in difficult poses, and occlusion between objects of the same type may cause confusion even in well-train...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	514,338
1803.01358	Applied Erasure Coding in Networks and Distributed Storage	The amount of digital data is rapidly growing. There is an increasing use of a wide range of computer systems, from mobile devices to large-scale data centers, and important for reliable operation of all computer systems is mitigating the occurrence and the impact of errors in digital data. The demand for new ultra-fas...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	91,856
1902.10493	Multi-Variant Scheduling of Critical Time-Triggered Communication in Incremental Development Process: Application to FlexRay	The portfolio of models offered by car manufacturing groups often includes many variants (i.e., different car models and their versions). With such diversity in car models, variant management becomes a formidable task. Thus, there is an effort to keep the variants as close as possible. This simple requirement forms a b...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	122,697
2211.00075	Keywords for Bias	This work proposes to analyse some keywords for bias analysis. For this, we are using several NLP approaches and compare them based on their capability of detecting keywords to analyse bias. The overall findings show that our proposed approach gives comparable results with the state-of-the-art approaches on different b...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	327,742
2112.11312	Implicit Neural Video Compression	We propose a method to compress full-resolution video sequences with implicit neural representations. Each frame is represented as a neural network that maps coordinate positions to pixel values. We use a separate implicit network to modulate the coordinate inputs, which enables efficient motion compensation between fr...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	272,671
2103.05745	Content-Preserving Unpaired Translation from Simulated to Realistic Ultrasound Images	Interactive simulation of ultrasound imaging greatly facilitates sonography training. Although ray-tracing based methods have shown promising results, obtaining realistic images requires substantial modeling effort and manual parameter tuning. In addition, current techniques still result in a significant appearance gap...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	224,071
2401.08821	Surface-Enhanced Raman Spectroscopy and Transfer Learning Toward Accurate Reconstruction of the Surgical Zone	Raman spectroscopy, a photonic modality based on the inelastic backscattering of coherent light, is a valuable asset to the intraoperative sensing space, offering non-ionizing potential and highly-specific molecular fingerprint-like spectroscopic signatures that can be used for diagnosis of pathological tissue in the d...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	422,033
2210.12101	Neural Network Approximations of PDEs Beyond Linearity: A Representational Perspective	A burgeoning line of research leverages deep neural networks to approximate the solutions to high dimensional PDEs, opening lines of theoretical inquiry focused on explaining how it is that these models appear to evade the curse of dimensionality. However, most prior theoretical analyses have been limited to linear PDE...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	325,587
1809.07456	Towards Discrete Solution: A Sparse Preserving Method for Correspondence Problem	Many problems of interest in computer vision can be formulated as a problem of finding consistent correspondences between two feature sets. Feature correspondence (matching) problem with one-to-one mapping constraint is usually formulated as an Integral Quadratic Programming (IQP) problem with permutation (or orthogona...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	108,282
2305.06155	Leveraging Synthetic Targets for Machine Translation	In this work, we provide a recipe for training machine translation models in a limited resource setting by leveraging synthetic target data generated using a large pre-trained model. We show that consistently across different benchmarks in bilingual, multilingual, and speech translation setups, training models on synth...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	363,429
2202.03629	Survey of Hallucination in Natural Language Generation	Natural Language Generation (NLG) has improved exponentially in recent years thanks to the development of sequence-to-sequence deep learning technologies such as Transformer-based language models. This advancement has led to more fluent and coherent NLG, leading to improved development in downstream tasks such as abstr...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	279,280
2407.16181	Structural Optimization Ambiguity and Simplicity Bias in Unsupervised Neural Grammar Induction	Neural parameterization has significantly advanced unsupervised grammar induction. However, training these models with a traditional likelihood loss for all possible parses exacerbates two issues: 1) $\textit{structural optimization ambiguity}$ that arbitrarily selects one among structurally ambiguous optimal grammars ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	475,493
2209.14250	B2B Advertising: Joint Dynamic Scoring of Account and Users	When a business sells to another business (B2B), the buying business is represented by a group of individuals, termed account, who collectively decide whether to buy. The seller advertises to each individual and interacts with them, mostly by digital means. The sales cycle is long, most often over a few months. There i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	320,187
2311.12006	A Novel Secure NFC-based Approach for BMS Monitoring and Diagnostic Readout	In modern systems that rely on the use of Battery Management Systems (BMS), longevity and the re-use of battery packs have always been important topics of discussion. These battery packs would be stored inside warehouses where they would need to be properly monitored and configured before their re-integration into the ...	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	true	409,161
2502.08544	Moment of Untruth: Dealing with Negative Queries in Video Moment Retrieval	Video Moment Retrieval is a common task to evaluate the performance of visual-language models - it involves localising start and end times of moments in videos from query sentences. The current task formulation assumes that the queried moment is present in the video, resulting in false positive moment predictions when ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	533,051
1701.02560	Time Complexity Analysis of a Distributed Stochastic Optimization in a Non-Stationary Environment	In this paper, we consider a distributed stochastic optimization problem where the goal is to minimize the time average of a cost function subject to a set of constraints on the time averages of related stochastic processes called penalties. We assume that the state of the system is evolving in an independent and non-s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	66,569
2108.07935	Learning Implicit User Profiles for Personalized Retrieval-Based Chatbot	In this paper, we explore the problem of developing personalized chatbots. A personalized chatbot is designed as a digital chatting assistant for a user. The key characteristic of a personalized chatbot is that it should have a consistent personality with the corresponding user. It can talk the same way as the user whe...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	251,067
1703.01671	Controlling for Unobserved Confounds in Classification Using Correlational Constraints	As statistical classifiers become integrated into real-world applications, it is important to consider not only their accuracy but also their robustness to changes in the data distribution. In this paper, we consider the case where there is an unobserved confounding variable $z$ that influences both the features $\math...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	69,411
2305.07269	Meta-Optimization for Higher Model Generalizability in Single-Image Depth Prediction	Model generalizability to unseen datasets, concerned with in-the-wild robustness, is less studied for indoor single-image depth prediction. We leverage gradient-based meta-learning for higher generalizability on zero-shot cross-dataset inference. Unlike the most-studied image classification in meta-learning, depth is p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	363,831
2210.06909	HoechstGAN: Virtual Lymphocyte Staining Using Generative Adversarial Networks	The presence and density of specific types of immune cells are important to understand a patient's immune response to cancer. However, immunofluorescence staining required to identify T cell subtypes is expensive, time-consuming, and rarely performed in clinical settings. We present a framework to virtually stain Hoech...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	323,499
2501.16981	Modulating CNN Features with Pre-Trained ViT Representations for Open-Vocabulary Object Detection	Owing to large-scale image-text contrastive training, pre-trained vision language model (VLM) like CLIP shows superior open-vocabulary recognition ability. Most existing open-vocabulary object detectors attempt to utilize the pre-trained VLM to attain generative representation. F-ViT uses the pre-trained visual encoder...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	528,174
2207.14036	Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem	Recently different evolutionary computation approaches have been developed that generate sets of high quality diverse solutions for a given optimisation problem. Many studies have considered diversity 1) as a mean to explore niches in behavioural space (quality diversity) or 2) to increase the structural differences of...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	310,471
2501.02855	Synthetic Fungi Datasets: A Time-Aligned Approach	Fungi undergo dynamic morphological transformations throughout their lifecycle, forming intricate networks as they transition from spores to mature mycelium structures. To support the study of these time-dependent processes, we present a synthetic, time-aligned image dataset that models key stages of fungal growth. Thi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	522,665
2312.10219	The Complexity of Optimizing Atomic Congestion	Atomic congestion games are a classic topic in network design, routing, and algorithmic game theory, and are capable of modeling congestion and flow optimization tasks in various application areas. While both the price of anarchy for such games as well as the computational complexity of computing their Nash equilibria ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	416,067
2010.02313	Multi-Objective Approach for Optimal Size and Location of DGs in Distribution Systems	In the recent years, due to the economic and environmental requirements, the use of distributed generations (DGs) has increased. If DGs have the optimal size and are located at the optimal locations, they are capable of enhancing the voltage profile and reducing the power loss. This paper proposes a new approach to obt...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	198,960
2007.11755	History Repeats Itself: Human Motion Prediction via Motion Attention	Human motion prediction aims to forecast future human poses given a past motion. Whether based on recurrent or feed-forward neural networks, existing methods fail to model the observation that human motion tends to repeat itself, even for complex sports actions and cooking activities. Here, we introduce an attention-ba...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	188,628
2406.18346	AI Alignment through Reinforcement Learning from Human Feedback? Contradictions and Limitations	This paper critically evaluates the attempts to align Artificial Intelligence (AI) systems, especially Large Language Models (LLMs), with human values and intentions through Reinforcement Learning from Feedback (RLxF) methods, involving either human feedback (RLHF) or AI feedback (RLAIF). Specifically, we show the shor...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	467,976
2007.06106	Unsupervised Feature Selection for Tumor Profiles using Autoencoders and Kernel Methods	Molecular data from tumor profiles is high dimensional. Tumor profiles can be characterized by tens of thousands of gene expression features. Due to the size of the gene expression feature set machine learning methods are exposed to noisy variables and complexity. Tumor types present heterogeneity and can be subdivided...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	186,899
2008.00250	Deep Reinforcement Learning Based Mobile Edge Computing for Intelligent Internet of Things	In this paper, we investigate mobile edge computing (MEC) networks for intelligent internet of things (IoT), where multiple users have some computational tasks assisted by multiple computational access points (CAPs). By offloading some tasks to the CAPs, the system performance can be improved through reducing the laten...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	189,956
0807.0087	Path lengths in tree-child time consistent hybridization networks	Hybridization networks are representations of evolutionary histories that allow for the inclusion of reticulate events like recombinations, hybridizations, or lateral gene transfers. The recent growth in the number of hybridization network reconstruction algorithms has led to an increasing interest in the definition of...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	2,021
1601.03958	Real-Time Community Detection in Large Social Networks on a Laptop	For a broad range of research, governmental and commercial applications it is important to understand the allegiances, communities and structure of key players in society. One promising direction towards extracting this information is to exploit the rich relational data in digital social networks (the social graph). As...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	50,965
2309.16670	Decaf: Monocular Deformation Capture for Face and Hand Interactions	Existing methods for 3D tracking from monocular RGB videos predominantly consider articulated and rigid objects. Modelling dense non-rigid object deformations in this setting remained largely unaddressed so far, although such effects can improve the realism of the downstream applications such as AR/VR and avatar commun...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	395,442
2409.18102	MALPOLON: A Framework for Deep Species Distribution Modeling	This paper describes a deep-SDM framework, MALPOLON. Written in Python and built upon the PyTorch library, this framework aims to facilitate training and inferences of deep species distribution models (deep-SDM) and sharing for users with only general Python language skills (e.g., modeling ecologists) who are intereste...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	492,105
2111.07465	Decoding Causality by Fictitious VAR Modeling	In modeling multivariate time series for either forecast or policy analysis, it would be beneficial to have figured out the cause-effect relations within the data. Regression analysis, however, is generally for correlation relation, and very few researches have focused on variance analysis for causality discovery. We f...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	266,382
2406.00226	Entangled Relations: Leveraging NLI and Meta-analysis to Enhance Biomedical Relation Extraction	Recent research efforts have explored the potential of leveraging natural language inference (NLI) techniques to enhance relation extraction (RE). In this vein, we introduce MetaEntail-RE, a novel adaptation method that harnesses NLI principles to enhance RE performance. Our approach follows past works by verbalizing r...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	459,752
2112.03865	Universalizing Weak Supervision	Weak supervision (WS) frameworks are a popular way to bypass hand-labeling large datasets for training data-hungry models. These approaches synthesize multiple noisy but cheaply-acquired estimates of labels into a set of high-quality pseudolabels for downstream training. However, the synthesis technique is specific to ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	270,361
2310.12795	Self-triggered Consensus Control of Multi-agent Systems from Data	This paper considers self-triggered consensus control of unknown linear multi-agent systems (MASs). Self-triggering mechanisms (STMs) are widely used in MASs, thanks to their advantages in avoiding continuous monitoring and saving computing and communication resources. However, existing results require the knowledge of...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	401,152
1710.07394	Recognizing Explicit and Implicit Hate Speech Using a Weakly Supervised Two-path Bootstrapping Approach	In the wake of a polarizing election, social media is laden with hateful content. To address various limitations of supervised hate speech classification methods including corpus bias and huge cost of annotation, we propose a weakly supervised two-path bootstrapping approach for an online hate speech detection model le...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	82,928
2312.00950	Improve Supervised Representation Learning with Masked Image Modeling	Training visual embeddings with labeled data supervision has been the de facto setup for representation learning in computer vision. Inspired by recent success of adopting masked image modeling (MIM) in self-supervised representation learning, we propose a simple yet effective setup that can easily integrate MIM into e...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	412,244
2309.13214	Assessing the Impact of Personality on Affective States from Video Game Communication	Individual differences in personality determine our preferences, traits and values, which should similarly hold for the way we express ourselves. With current advancements and transformations of technology and society, text-based communication has become ordinary and often even surpasses natural voice conversations -- ...	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	394,106
2001.03103	Supervised Discriminative Sparse PCA with Adaptive Neighbors for Dimensionality Reduction	Dimensionality reduction is an important operation in information visualization, feature extraction, clustering, regression, and classification, especially for processing noisy high dimensional data. However, most existing approaches preserve either the global or the local structure of the data, but not both. Approache...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	159,885
2108.08513	Fast Passage Re-ranking with Contextualized Exact Term Matching and Efficient Passage Expansion	BERT-based information retrieval models are expensive, in both time (query latency) and computational resources (energy, hardware cost), making many of these models impractical especially under resource constraints. The reliance on a query encoder that only performs tokenization and on the pre-processing of passage rep...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	251,282
2408.08074	A Survey on Integrated Sensing, Communication, and Computation	The forthcoming generation of wireless technology, 6G, aims to usher in an era of ubiquitous intelligent services, where everything is interconnected and intelligent. This vision requires the seamless integration of three fundamental modules: Sensing for information acquisition, communication for information sharing, a...	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	false	480,846
2408.08862	Visual Agents as Fast and Slow Thinkers	Achieving human-level intelligence requires refining cognitive distinctions between System 1 and System 2 thinking. While contemporary AI, driven by large language models, demonstrates human-like traits, it falls short of genuine cognition. Transitioning from structured benchmarks to real-world scenarios presents chall...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	481,183
2311.00094	A Tractable Inference Perspective of Offline RL	A popular paradigm for offline Reinforcement Learning (RL) tasks is to first fit the offline trajectories to a sequence model, and then prompt the model for actions that lead to high expected return. In addition to obtaining accurate sequence models, this paper highlights that tractability, the ability to exactly and e...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	404,505
2011.07733	Gram Regularization for Multi-view 3D Shape Retrieval	How to obtain the desirable representation of a 3D shape is a key challenge in 3D shape retrieval task. Most existing 3D shape retrieval methods focus on capturing shape representation with different neural network architectures, while the learning ability of each layer in the network is neglected. A common and tough i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	206,654
2208.04608	Using Sentence Embeddings and Semantic Similarity for Seeking Consensus when Assessing Trustworthy AI	Assessing the trustworthiness of artificial intelligence systems requires knowledge from many different disciplines. These disciplines do not necessarily share concepts between them and might use words with different meanings, or even use the same words differently. Additionally, experts from different disciplines migh...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	312,168
1809.03937	MIMO Mutli-Cell Processing: Optimal Precoding and Power Allocation	We investigate the optimal power allocation and optimal precoding for a cluster of two BSs which cooperate to jointly maximize the achievable rate for two users connecting to each BS in a MCP framework. This framework is modeled by a virtual network MIMO channel due to the framework of full cooperation. In particular, ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	107,433
2312.01771	IMProv: Inpainting-based Multimodal Prompting for Computer Vision Tasks	In-context learning allows adapting a model to new tasks given a task description at test time. In this paper, we present IMProv - a generative model that is able to in-context learn visual tasks from multimodal prompts. Given a textual description of a visual task (e.g. "Left: input image, Right: foreground segmentati...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	412,587
1910.07186	Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation	Infinite horizon off-policy policy evaluation is a highly challenging task due to the excessively large variance of typical importance sampling (IS) estimators. Recently, Liu et al. (2018a) proposed an approach that significantly reduces the variance of infinite-horizon off-policy evaluation by estimating the stationar...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	149,544
2110.06636	Unique on Facebook: Formulation and Evidence of (Nano)targeting Individual Users with non-PII Data	The privacy of an individual is bounded by the ability of a third party to reveal their identity. Certain data items such as a passport ID or a mobile phone number may be used to uniquely identify a person. These are referred to as Personal Identifiable Information (PII) items. Previous literature has also reported tha...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	260,695
2502.13514	Shall Your Data Strategy Work? Perform a Swift Study	This work presents a swift method to assess the efficacy of particular types of instruction-tuning data, utilizing just a handful of probe examples and eliminating the need for model retraining. This method employs the idea of gradient-based data influence estimation, analyzing the gradient projections of probe example...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	535,400
2401.02974	Efficacy of Utilizing Large Language Models to Detect Public Threat Posted Online	This paper examines the efficacy of utilizing large language models (LLMs) to detect public threats posted online. Amid rising concerns over the spread of threatening rhetoric and advance notices of violence, automated content analysis techniques may aid in early identification and moderation. Custom data collection to...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	419,911
2405.01924	Semi-Parametric Retrieval via Binary Token Index	The landscape of information retrieval has broadened from search services to a critical component in various advanced applications, where indexing efficiency, cost-effectiveness, and freshness are increasingly important yet remain less explored. To address these demands, we introduce Semi-parametric Vocabulary Disentan...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	451,561
2312.04008	Natural-language-driven Simulation Benchmark and Copilot for Efficient Production of Object Interactions in Virtual Road Scenes	We advocate the idea of the natural-language-driven(NLD) simulation to efficiently produce the object interactions between multiple objects in the virtual road scenes, for teaching and testing the autonomous driving systems that should take quick action to avoid collision with obstacles with unpredictable motions. The ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	413,505
2308.16307	Implementation Of MNIST Dataset Learning Using Analog Circuit	There have been many attempts to implement neural networks in the analog circuit. Most of them had a lot of input terms, and most studies implemented neural networks in the analog circuit through a circuit simulation program called Spice to avoid the need to design chips at a high cost and implement circuits directly t...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	388,941
2010.11931	Brain-Inspired Learning on Neuromorphic Substrates	Neuromorphic hardware strives to emulate brain-like neural networks and thus holds the promise for scalable, low-power information processing on temporal data streams. Yet, to solve real-world problems, these networks need to be trained. However, training on neuromorphic substrates creates significant challenges due to...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	202,482
1709.06030	N2N Learning: Network to Network Compression via Policy Gradient Reinforcement Learning	While bigger and deeper neural network architectures continue to advance the state-of-the-art for many computer vision tasks, real-world adoption of these networks is impeded by hardware and speed constraints. Conventional model compression methods attempt to address this problem by modifying the architecture manually ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	81,009
1910.03467	Overcoming the Rare Word Problem for Low-Resource Language Pairs in Neural Machine Translation	Among the six challenges of neural machine translation (NMT) coined by (Koehn and Knowles, 2017), rare-word problem is considered the most severe one, especially in translation of low-resource languages. In this paper, we propose three solutions to address the rare words in neural machine translation systems. First, we...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	148,497
2410.16069	Rolling the DICE on Idiomaticity: How LLMs Fail to Grasp Context	Human processing of idioms relies on understanding the contextual sentences in which idioms occur, as well as language-intrinsic features such as frequency and speaker-intrinsic factors like familiarity. While LLMs have shown high performance on idiomaticity detection tasks, this success may be attributed to reasoning ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	500,859
1708.01236	Multiscale mixing patterns in networks	Assortative mixing in networks is the tendency for nodes with the same attributes, or metadata, to link to each other. It is a property often found in social networks manifesting as a higher tendency of links occurring between people with the same age, race, or political belief. Quantifying the level of assortativity o...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	78,355
2406.04520	NATURAL PLAN: Benchmarking LLMs on Natural Language Planning	We introduce NATURAL PLAN, a realistic planning benchmark in natural language containing 3 key tasks: Trip Planning, Meeting Planning, and Calendar Scheduling. We focus our evaluation on the planning capabilities of LLMs with full information on the task, by providing outputs from tools such as Google Flights, Google M...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	461,714
2411.02714	Game Plot Design with an LLM-powered Assistant: An Empirical Study with Game Designers	We introduce GamePlot, an LLM-powered assistant that supports game designers in crafting immersive narratives for turn-based games, and allows them to test these games through a collaborative game play and refine the plot throughout the process. Our user study with 14 game designers shows high levels of both satisfacti...	true	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	505,628
2402.09398	Get More with LESS: Synthesizing Recurrence with KV Cache Compression for Efficient LLM Inference	Many computational factors limit broader deployment of large language models. In this paper, we focus on a memory bottleneck imposed by the key-value (KV) cache, a computational shortcut that requires storing previous KV pairs during decoding. While existing KV cache methods approach this problem by pruning or evicting...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	429,502
2405.03481	AnchorGT: Efficient and Flexible Attention Architecture for Scalable Graph Transformers	Graph Transformers (GTs) have significantly advanced the field of graph representation learning by overcoming the limitations of message-passing graph neural networks (GNNs) and demonstrating promising performance and expressive power. However, the quadratic complexity of self-attention mechanism in GTs has limited the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	452,199
2305.05222	FishRecGAN: An End to End GAN Based Network for Fisheye Rectification and Calibration	We propose an end-to-end deep learning approach to rectify fisheye images and simultaneously calibrate camera intrinsic and distortion parameters. Our method consists of two parts: a Quick Image Rectification Module developed with a Pix2Pix GAN and Wasserstein GAN (W-Pix2PixGAN), and a Calibration Module with a CNN arc...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	363,058
2412.08661	GeoConformal prediction: a model-agnostic framework of measuring the uncertainty of spatial prediction	Spatial prediction is a fundamental task in geography. In recent years, with advances in geospatial artificial intelligence (GeoAI), numerous models have been developed to improve the accuracy of geographic variable predictions. Beyond achieving higher accuracy, it is equally important to obtain predictions with uncert...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	516,194
2409.14988	Beyond Fine-tuning: Unleashing the Potential of Continuous Pretraining for Clinical LLMs	Large Language Models (LLMs) have demonstrated significant potential in transforming clinical applications. In this study, we investigate the efficacy of four techniques in adapting LLMs for clinical use-cases: continuous pretraining, instruct fine-tuning, NEFTune, and prompt engineering. We employ these methods on Mis...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	490,713
2206.00238	Transferable Reward Learning by Dynamics-Agnostic Discriminator Ensemble	Recovering reward function from expert demonstrations is a fundamental problem in reinforcement learning. The recovered reward function captures the motivation of the expert. Agents can imitate experts by following these reward functions in their environment, which is known as apprentice learning. However, the agents m...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	300,042
2209.06257	A computational framework for physics-informed symbolic regression with straightforward integration of domain knowledge	Discovering a meaningful symbolic expression that explains experimental data is a fundamental challenge in many scientific fields. We present a novel, open-source computational framework called Scientist-Machine Equation Detector (SciMED), which integrates scientific discipline wisdom in a scientist-in-the-loop approac...	true	true	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	317,331
2301.04339	Topics in Contextualised Attention Embeddings	Contextualised word vectors obtained via pre-trained language models encode a variety of knowledge that has already been exploited in applications. Complementary to these language models are probabilistic topic models that learn thematic patterns from the text. Recent work has demonstrated that conducting clustering on...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	340,031
2102.11928	Investigating Moral Foundations from Web Trending Topics	Moral foundations theory helps understand differences in morality across cultures. In this paper, we propose a model to predict moral foundations (MF) from social media trending topics. We also investigate whether differences in MF influence emotional traits. Our results are promising and leave room for future research...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	221,562
2212.01350	Improving Iterative Text Revision by Learning Where to Edit from Other Revision Tasks	Iterative text revision improves text quality by fixing grammatical errors, rephrasing for better readability or contextual appropriateness, or reorganizing sentence structures throughout a document. Most recent research has focused on understanding and classifying different types of edits in the iterative revision pro...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	334,395
2008.03347	Linear Parameter-Varying Subspace Identification: A Unified Framework	In this paper, we establish a unified framework for subspace identification (SID) of linear parameter-varying (LPV) systems to estimate LPV state-space (SS) models in innovation form. This framework enables us to derive novel LPV SID schemes that are extensions of existing linear time-invariant (LTI) methods. More spec...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	190,869
2403.00742	Dialect prejudice predicts AI decisions about people's character, employability, and criminality	Hundreds of millions of people now interact with language models, with uses ranging from serving as a writing aid to informing hiring decisions. Yet these language models are known to perpetuate systematic racial prejudices, making their judgments biased in problematic ways about groups like African Americans. While pr...	false	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	434,079
2411.07529	Evaluating ChatGPT-3.5 Efficiency in Solving Coding Problems of Different Complexity Levels: An Empirical Analysis	ChatGPT and other large language models (LLMs) promise to revolutionize software development by automatically generating code from program specifications. We assess the performance of ChatGPT's GPT-3.5-turbo model on LeetCode, a popular platform with algorithmic coding challenges for technical interview practice, acros...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	507,567
2004.03324	Windowing Models for Abstractive Summarization of Long Texts	Neural summarization models suffer from the fixed-size input limitation: if text length surpasses the model's maximal number of input tokens, some document content (possibly summary-relevant) gets truncated Independently summarizing windows of maximal input size disallows for information flow between windows and leads ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	171,512
2201.07990	Effect of Human Involvement on Work Performance and Fluency in Human-Robot Collaboration for Recycling	Human-robot collaboration has significant potential in recycling due to the wide variation in the composition of recyclable products. Six participants performed a recyclable item sorting task collaborating with a robot arm equipped with a vision system. The effect of three different levels of human involvement or assis...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	276,195
2406.13925	GenderAlign: An Alignment Dataset for Mitigating Gender Bias in Large Language Models	Large Language Models (LLMs) are prone to generating content that exhibits gender biases, raising significant ethical concerns. Alignment, the process of fine-tuning LLMs to better align with desired behaviors, is recognized as an effective approach to mitigate gender biases. Although proprietary LLMs have made signifi...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	466,062
2407.03791	M5 -- A Diverse Benchmark to Assess the Performance of Large Multimodal Models Across Multilingual and Multicultural Vision-Language Tasks	Since the release of ChatGPT, the field of Natural Language Processing has experienced rapid advancements, particularly in Large Language Models (LLMs) and their multimodal counterparts, Large Multimodal Models (LMMs). Despite their impressive capabilities, LLMs often exhibit significant performance disparities across ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	470,292
2412.12227	EDformer: Embedded Decomposition Transformer for Interpretable Multivariate Time Series Predictions	Time series forecasting is a crucial challenge with significant applications in areas such as weather prediction, stock market analysis, and scientific simulations. This paper introduces an embedded decomposed transformer, 'EDformer', for multivariate time series forecasting tasks. Without altering the fundamental elem...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	517,807
2208.09595	The Saddle-Point Accountant for Differential Privacy	We introduce a new differential privacy (DP) accountant called the saddle-point accountant (SPA). SPA approximates privacy guarantees for the composition of DP mechanisms in an accurate and fast manner. Our approach is inspired by the saddle-point method -- a ubiquitous numerical technique in statistics. We prove rigor...	false	false	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	313,753
2309.03004	A Theoretical Explanation of Activation Sparsity through Flat Minima and Adversarial Robustness	A recent empirical observation (Li et al., 2022b) of activation sparsity in MLP blocks offers an opportunity to drastically reduce computation costs for free. Although having attributed it to training dynamics, existing theoretical explanations of activation sparsity are restricted to shallow networks, small training s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	390,237
1911.09267	Semantic Hierarchy Emerges in Deep Generative Representations for Scene Synthesis	Despite the success of Generative Adversarial Networks (GANs) in image synthesis, there lacks enough understanding on what generative models have learned inside the deep generative representations and how photo-realistic images are able to be composed of the layer-wise stochasticity introduced in recent GANs. In this w...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	154,454
2404.05648	Resistive Memory-based Neural Differential Equation Solver for Score-based Diffusion Model	Human brains image complicated scenes when reading a novel. Replicating this imagination is one of the ultimate goals of AI-Generated Content (AIGC). However, current AIGC methods, such as score-based diffusion, are still deficient in terms of rapidity and efficiency. This deficiency is rooted in the difference between...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	true	445,159
1511.06656	A Study of Age and Gender seen through Mobile Phone Usage Patterns in Mexico	Mobile phone usage provides a wealth of information, which can be used to better understand the demographic structure of a population. In this paper we focus on the population of Mexican mobile phone users. Our first contribution is an observational study of mobile phone usage according to gender and age groups. We wer...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	49,299
2111.10135	Grounded Situation Recognition with Transformers	Grounded Situation Recognition (GSR) is the task that not only classifies a salient action (verb), but also predicts entities (nouns) associated with semantic roles and their locations in the given image. Inspired by the remarkable success of Transformers in vision tasks, we propose a GSR model based on a Transformer e...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	267,219
2210.06790	Deep Gesture Generation for Social Robots Using Type-Specific Libraries	Body language such as conversational gesture is a powerful way to ease communication. Conversational gestures do not only make a speech more lively but also contain semantic meaning that helps to stress important information in the discussion. In the field of robotics, giving conversational agents (humanoid robots or v...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	323,450
1709.06895	Optimized Structured Sparse Sensing Matrices for Compressive Sensing	We consider designing a robust structured sparse sensing matrix consisting of a sparse matrix with a few non-zero entries per row and a dense base matrix for capturing signals efficiently We design the robust structured sparse sensing matrix through minimizing the distance between the Gram matrix of the equivalent dict...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	81,189
1510.06916	NXgraph: An Efficient Graph Processing System on a Single Machine	Recent studies show that graph processing systems on a single machine can achieve competitive performance compared with cluster-based graph processing systems. In this paper, we present NXgraph, an efficient graph processing system on a single machine. With the abstraction of vertex intervals and edge sub-shards, we pr...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	48,153
1602.06365	Distributed Power Control in Interference Channels with QoS Constraints and RF Energy Harvesting: A Game-Theoretic Approach	This paper develops a new distributed power control scheme for a power splitting-based interference channel (IFC) with simultaneous wireless information and power transfer (SWIPT). The considered IFC consists of multiple source-destination pairs. Each destination splits its received signal into two parts for informatio...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	52,352

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