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
2302.00270	Internally Rewarded Reinforcement Learning	We study a class of reinforcement learning problems where the reward signals for policy learning are generated by an internal reward model that is dependent on and jointly optimized with the policy. This interdependence between the policy and the reward model leads to an unstable learning process because reward signals...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	343,164
1307.8182	POMDPs Make Better Hackers: Accounting for Uncertainty in Penetration Testing	Penetration Testing is a methodology for assessing network security, by generating and executing possible hacking attacks. Doing so automatically allows for regular and systematic testing. A key question is how to generate the attacks. This is naturally formulated as planning under uncertainty, i.e., under incomplete k...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	26,170
2106.03787	Concave Utility Reinforcement Learning: the Mean-Field Game Viewpoint	Concave Utility Reinforcement Learning (CURL) extends RL from linear to concave utilities in the occupancy measure induced by the agent's policy. This encompasses not only RL but also imitation learning and exploration, among others. Yet, this more general paradigm invalidates the classical Bellman equations, and calls...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	239,452
2301.05729	GAR: Generalized Autoregression for Multi-Fidelity Fusion	In many scientific research and engineering applications where repeated simulations of complex systems are conducted, a surrogate is commonly adopted to quickly estimate the whole system. To reduce the expensive cost of generating training examples, it has become a promising approach to combine the results of low-fidel...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	340,427
1910.04483	Tree-Wasserstein Barycenter for Large-Scale Multilevel Clustering and Scalable Bayes	We study in this paper a variant of Wasserstein barycenter problem, which we refer to as tree-Wasserstein barycenter, by leveraging a specific class of ground metrics, namely tree metrics, for Wasserstein distance. Drawing on the tree structure, we propose an efficient algorithmic approach to solve the tree-Wasserstein...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	148,781
1703.00754	RGBDTAM: A Cost-Effective and Accurate RGB-D Tracking and Mapping System	Simultaneous Localization and Mapping using RGB-D cameras has been a fertile research topic in the latest decade, due to the suitability of such sensors for indoor robotics. In this paper we propose a direct RGB-D SLAM algorithm with state-of-the-art accuracy and robustness at a los cost. Our experiments in the RGB-D T...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	69,220
2409.11552	Multi-Domain Data Aggregation for Axon and Myelin Segmentation in Histology Images	Quantifying axon and myelin properties (e.g., axon diameter, myelin thickness, g-ratio) in histology images can provide useful information about microstructural changes caused by neurodegenerative diseases. Automatic tissue segmentation is an important tool for these datasets, as a single stained section can contain up...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	489,208
2201.04185	Equilibration Analysis and Control of Coordinating Decision-Making Populations	Whether a population of decision-making individuals will reach a state of satisfactory decisions is a fundamental problem in studying collective behaviors. In the framework of evolutionary game theory and by means of potential functions, researchers have established equilibrium convergence under different update rules,...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	275,033
2309.11722	Efficient Core-selecting Incentive Mechanism for Data Sharing in Federated Learning	Federated learning is a distributed machine learning system that uses participants' data to train an improved global model. In federated learning, participants cooperatively train a global model, and they will receive the global model and payments. Rational participants try to maximize their individual utility, and the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	393,516
2310.17836	Positional Encoding-based Resident Identification in Multi-resident Smart Homes	We propose a novel resident identification framework to identify residents in a multi-occupant smart environment. The proposed framework employs a feature extraction model based on the concepts of positional encoding. The feature extraction model considers the locations of homes as a graph. We design a novel algorithm ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	403,307
2308.15952	Benchmarking Multilabel Topic Classification in the Kyrgyz Language	Kyrgyz is a very underrepresented language in terms of modern natural language processing resources. In this work, we present a new public benchmark for topic classification in Kyrgyz, introducing a dataset based on collected and annotated data from the news site 24.KG and presenting several baseline models for news cl...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	388,859
2001.10130	Interpreting Cloud Computer Vision Pain-Points: A Mining Study of Stack Overflow	Intelligent services are becoming increasingly more pervasive; application developers want to leverage the latest advances in areas such as computer vision to provide new services and products to users, and large technology firms enable this via RESTful APIs. While such APIs promise an easy-to-integrate on-demand machi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	161,746
2406.04929	Protein pathways as a catalyst to directed evolution of the topology of artificial neural networks	In the present article, we propose a paradigm shift on evolving Artificial Neural Networks (ANNs) towards a new bio-inspired design that is grounded on the structural properties, interactions, and dynamics of protein networks (PNs): the Artificial Protein Network (APN). This introduces several advantages previously unr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	461,915
2009.09241	Word class flexibility: A deep contextualized approach	Word class flexibility refers to the phenomenon whereby a single word form is used across different grammatical categories. Extensive work in linguistic typology has sought to characterize word class flexibility across languages, but quantifying this phenomenon accurately and at scale has been fraught with difficulties...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	196,510
2108.13686	Knowledge-Grounded Dialogue with Reward-Driven Knowledge Selection	Knowledge-grounded dialogue is a task of generating a fluent and informative response based on both conversation context and a collection of external knowledge, in which knowledge selection plays an important role and attracts more and more research interest. However, most existing models either select only one knowled...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	252,875
2410.15244	Extensions on low-complexity DCT approximations for larger blocklengths based on minimal angle similarity	The discrete cosine transform (DCT) is a central tool for image and video coding because it can be related to the Karhunen-Lo\`eve transform (KLT), which is the optimal transform in terms of retained transform coefficients and data decorrelation. In this paper, we introduce 16-, 32-, and 64-point low-complexity DCT app...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	500,438
2306.02597	Early Rumor Detection Using Neural Hawkes Process with a New Benchmark Dataset	Little attention has been paid on \underline{EA}rly \underline{R}umor \underline{D}etection (EARD), and EARD performance was evaluated inappropriately on a few datasets where the actual early-stage information is largely missing. To reverse such situation, we construct BEARD, a new \underline{B}enchmark dataset for \un...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	370,973
1806.07592	Deep Similarity Metric Learning for Real-Time Pedestrian Tracking	Tracking by detection is a common approach to solving the Multiple Object Tracking problem. In this paper we show how learning a deep similarity metric can improve three key aspects of pedestrian tracking on a multiple object tracking benchmark. We train a convolutional neural network to learn an embedding function in ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	100,972
2408.08535	CommunityKG-RAG: Leveraging Community Structures in Knowledge Graphs for Advanced Retrieval-Augmented Generation in Fact-Checking	Despite advancements in Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems, their effectiveness is often hindered by a lack of integration with entity relationships and community structures, limiting their ability to provide contextually rich and accurate information retrieval for fact-checki...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	481,030
2006.09461	Robust Compressed Sensing using Generative Models	The goal of compressed sensing is to estimate a high dimensional vector from an underdetermined system of noisy linear equations. In analogy to classical compressed sensing, here we assume a generative model as a prior, that is, we assume the vector is represented by a deep generative model $G: \mathbb{R}^k \rightarrow...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	182,546
1111.1426	SLIQ: Simple Linear Inequalities for Efficient Contig Scaffolding	Scaffolding is an important subproblem in "de novo" genome assembly in which mate pair data are used to construct a linear sequence of contigs separated by gaps. Here we present SLIQ, a set of simple linear inequalities derived from the geometry of contigs on the line that can be used to predict the relative positions ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	12,931
2302.00892	Quantum Graph Learning: Frontiers and Outlook	Quantum theory has shown its superiority in enhancing machine learning. However, facilitating quantum theory to enhance graph learning is in its infancy. This survey investigates the current advances in quantum graph learning (QGL) from three perspectives, i.e., underlying theories, methods, and prospects. We first loo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	343,393
1804.09460	Analytical Modeling of Vanishing Points and Curves in Catadioptric Cameras	Vanishing points and vanishing lines are classical geometrical concepts in perspective cameras that have a lineage dating back to 3 centuries. A vanishing point is a point on the image plane where parallel lines in 3D space appear to converge, whereas a vanishing line passes through 2 or more vanishing points. While su...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	95,974
2402.07945	ScreenAgent: A Vision Language Model-driven Computer Control Agent	Existing Large Language Models (LLM) can invoke a variety of tools and APIs to complete complex tasks. The computer, as the most powerful and universal tool, could potentially be controlled directly by a trained LLM agent. Powered by the computer, we can hopefully build a more generalized agent to assist humans in vari...	true	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	428,909
1605.06650	Latent Tree Models for Hierarchical Topic Detection	We present a novel method for hierarchical topic detection where topics are obtained by clustering documents in multiple ways. Specifically, we model document collections using a class of graphical models called hierarchical latent tree models (HLTMs). The variables at the bottom level of an HLTM are observed binary va...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	56,165
1807.09913	Advanced iterative procedures for solving the implicit Colebrook equation for fluid flow friction	Empirical Colebrook equation from 1939 is still accepted as an informal standard to calculate friction factor during the turbulent flow through pipes from smooth with almost negligible relative roughness to the very rough inner surface. The Colebrook equation contains flow friction factor in implicit logarithmic form w...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	103,822
1301.7047	Link prediction for partially observed networks	Link prediction is one of the fundamental problems in network analysis. In many applications, notably in genetics, a partially observed network may not contain any negative examples of absent edges, which creates a difficulty for many existing supervised learning approaches. We develop a new method which treats the obs...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	21,580
2311.01526	ATGNN: Audio Tagging Graph Neural Network	Deep learning models such as CNNs and Transformers have achieved impressive performance for end-to-end audio tagging. Recent works have shown that despite stacking multiple layers, the receptive field of CNNs remains severely limited. Transformers on the other hand are able to map global context through self-attention,...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	405,076
2407.14796	PASSION: Towards Effective Incomplete Multi-Modal Medical Image Segmentation with Imbalanced Missing Rates	Incomplete multi-modal image segmentation is a fundamental task in medical imaging to refine deployment efficiency when only partial modalities are available. However, the common practice that complete-modality data is visible during model training is far from realistic, as modalities can have imbalanced missing rates ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	474,913
2501.06066	Distilling Calibration via Conformalized Credal Inference	Deploying artificial intelligence (AI) models on edge devices involves a delicate balance between meeting stringent complexity constraints, such as limited memory and energy resources, and ensuring reliable performance in sensitive decision-making tasks. One way to enhance reliability is through uncertainty quantificat...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	523,822
1910.10857	Selective Attention Based Graph Convolutional Networks for Aspect-Level Sentiment Classification	Aspect-level sentiment classification aims to identify the sentiment polarity towards a specific aspect term in a sentence. Most current approaches mainly consider the semantic information by utilizing attention mechanisms to capture the interactions between the context and the aspect term. In this paper, we propose to...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	150,607
2102.05132	Using Deep LSD to build operators in GANs latent space with meaning in real space	Generative models rely on the key idea that data can be represented in terms of latent variables which are uncorrelated by definition. Lack of correlation is important because it suggests that the latent space manifold is simpler to understand and manipulate. Generative models are widely used in deep learning, e.g., va...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	219,330
1802.09990	Deep Learning Architectures for Face Recognition in Video Surveillance	Face recognition (FR) systems for video surveillance (VS) applications attempt to accurately detect the presence of target individuals over a distributed network of cameras. In video-based FR systems, facial models of target individuals are designed a priori during enrollment using a limited number of reference still i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	91,439
2308.12270	Language Reward Modulation for Pretraining Reinforcement Learning	Using learned reward functions (LRFs) as a means to solve sparse-reward reinforcement learning (RL) tasks has yielded some steady progress in task-complexity through the years. In this work, we question whether today's LRFs are best-suited as a direct replacement for task rewards. Instead, we propose leveraging the cap...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	387,478
2403.07514	Uncertainty-guided Contrastive Learning for Single Source Domain Generalisation	In the context of single domain generalisation, the objective is for models that have been exclusively trained on data from a single domain to demonstrate strong performance when confronted with various unfamiliar domains. In this paper, we introduce a novel model referred to as Contrastive Uncertainty Domain Generalis...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	436,914
2212.01519	Beyond ADMM: A Unified Client-variance-reduced Adaptive Federated Learning Framework	As a novel distributed learning paradigm, federated learning (FL) faces serious challenges in dealing with massive clients with heterogeneous data distribution and computation and communication resources. Various client-variance-reduction schemes and client sampling strategies have been respectively introduced to impro...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	334,459
2209.13953	ArNLI: Arabic Natural Language Inference for Entailment and Contradiction Detection	Natural Language Inference (NLI) is a hot topic research in natural language processing, contradiction detection between sentences is a special case of NLI. This is considered a difficult NLP task which has a big influence when added as a component in many NLP applications, such as Question Answering Systems, text Summ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	320,084
0707.1452	Clusters, Graphs, and Networks for Analysing Internet-Web-Supported Communication within a Virtual Community	The proposal is to use clusters, graphs and networks as models in order to analyse the Web structure. Clusters, graphs and networks provide knowledge representation and organization. Clusters were generated by co-site analysis. The sample is a set of academic Web sites from the countries belonging to the European Union...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	413
2409.03198	RoomDiffusion: A Specialized Diffusion Model in the Interior Design Industry	Recent advancements in text-to-image diffusion models have significantly transformed visual content generation, yet their application in specialized fields such as interior design remains underexplored. In this paper, we present RoomDiffusion, a pioneering diffusion model meticulously tailored for the interior design i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	485,955
2010.00633	Discontinuous Constituent Parsing as Sequence Labeling	This paper reduces discontinuous parsing to sequence labeling. It first shows that existing reductions for constituent parsing as labeling do not support discontinuities. Second, it fills this gap and proposes to encode tree discontinuities as nearly ordered permutations of the input sequence. Third, it studies whether...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	198,340
2311.06613	Computer Vision for Particle Size Analysis of Coarse-Grained Soils	Particle size analysis (PSA) is a fundamental technique for evaluating the physical characteristics of soils. However, traditional methods like sieving can be time-consuming and labor-intensive. In this study, we present a novel approach that utilizes computer vision (CV) and the Python programming language for PSA of ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	407,006
1703.06324	Deep Tensor Encoding	Learning an encoding of feature vectors in terms of an over-complete dictionary or a information geometric (Fisher vectors) construct is wide-spread in statistical signal processing and computer vision. In content based information retrieval using deep-learning classifiers, such encodings are learnt on the flattened la...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	70,212
2305.07751	Private and Communication-Efficient Algorithms for Entropy Estimation	Modern statistical estimation is often performed in a distributed setting where each sample belongs to a single user who shares their data with a central server. Users are typically concerned with preserving the privacy of their samples, and also with minimizing the amount of data they must transmit to the server. We g...	false	false	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	364,011
2301.13013	RFPose-OT: RF-Based 3D Human Pose Estimation via Optimal Transport Theory	This paper introduces a novel framework, i.e., RFPose-OT, to enable the 3D human pose estimation from Radio Frequency (RF) signals. Different from existing methods that predict human poses from RF signals on the signal level directly, we consider the structure difference between the RF signals and the human poses, prop...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	342,754
0707.2090	A Training based Distributed Non-Coherent Space-Time Coding Strategy	Unitary space-time modulation is known to be an efficient means to communicate over non-coherent Multiple Input Multiple Output (MIMO) channels. In this letter, differential unitary space-time coding and non-coherent space-time coding for the training based approach of Kim and Tarokh are addressed. For this approach, n...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	432
1905.13540	Gaining Extra Supervision via Multi-task learning for Multi-Modal Video Question Answering	This paper proposes a method to gain extra supervision via multi-task learning for multi-modal video question answering. Multi-modal video question answering is an important task that aims at the joint understanding of vision and language. However, establishing large scale dataset for multi-modal video question answeri...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	133,160
2410.08646	Fully Unsupervised Dynamic MRI Reconstruction via Diffeo-Temporal Equivariance	Reconstructing dynamic MRI image sequences from undersampled accelerated measurements is crucial for faster and higher spatiotemporal resolution real-time imaging of cardiac motion, free breathing motion and many other applications. Classical paradigms, such as gated cine MRI, assume periodicity, disallowing imaging of...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	497,213
2407.12061	Situated Instruction Following	Language is never spoken in a vacuum. It is expressed, comprehended, and contextualized within the holistic backdrop of the speaker's history, actions, and environment. Since humans are used to communicating efficiently with situated language, the practicality of robotic assistants hinge on their ability to understand ...	true	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	473,749
1511.02254	Active Perceptual Similarity Modeling with Auxiliary Information	Learning a model of perceptual similarity from a collection of objects is a fundamental task in machine learning underlying numerous applications. A common way to learn such a model is from relative comparisons in the form of triplets: responses to queries of the form "Is object a more similar to b than it is to c?". I...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	48,600
2106.00104	Text Summarization with Latent Queries	The availability of large-scale datasets has driven the development of neural models that create summaries from single documents, for generic purposes. When using a summarization system, users often have specific intents with various language realizations, which, depending on the information need, can range from a sing...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	237,982
2212.11409	DExT: Detector Explanation Toolkit	State-of-the-art object detectors are treated as black boxes due to their highly non-linear internal computations. Even with unprecedented advancements in detector performance, the inability to explain how their outputs are generated limits their use in safety-critical applications. Previous work fails to produce expla...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	337,782
2409.16202	CJEval: A Benchmark for Assessing Large Language Models Using Chinese Junior High School Exam Data	Online education platforms have significantly transformed the dissemination of educational resources by providing a dynamic and digital infrastructure. With the further enhancement of this transformation, the advent of Large Language Models (LLMs) has elevated the intelligence levels of these platforms. However, curren...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	491,244
2407.11984	Mimetic Poet	This paper presents the design and initial assessment of a novel device that uses generative AI to facilitate creative ideation, inspiration, and reflective thought. Inspired by magnetic poetry, which was originally designed to help overcome writer's block, the device allows participants to compose short poetic texts f...	true	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	473,703
2311.11567	InfiMM-Eval: Complex Open-Ended Reasoning Evaluation For Multi-Modal Large Language Models	Multi-modal Large Language Models (MLLMs) are increasingly prominent in the field of artificial intelligence. These models not only excel in traditional vision-language tasks but also demonstrate impressive performance in contemporary multi-modal benchmarks. Although many of these benchmarks attempt to holistically eva...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	408,996
2306.05772	A Boosted Model Ensembling Approach to Ball Action Spotting in Videos: The Runner-Up Solution to CVPR'23 SoccerNet Challenge	This technical report presents our solution to Ball Action Spotting in videos. Our method reached second place in the CVPR'23 SoccerNet Challenge. Details of this challenge can be found at https://www.soccer-net.org/tasks/ball-action-spotting. Our approach is developed based on a baseline model termed E2E-Spot, which w...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	372,329
2305.17349	Condition-Invariant Semantic Segmentation	Adaptation of semantic segmentation networks to different visual conditions is vital for robust perception in autonomous cars and robots. However, previous work has shown that most feature-level adaptation methods, which employ adversarial training and are validated on synthetic-to-real adaptation, provide marginal gai...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	368,540
2407.16697	AbdomenAtlas: A Large-Scale, Detailed-Annotated, & Multi-Center Dataset for Efficient Transfer Learning and Open Algorithmic Benchmarking	We introduce the largest abdominal CT dataset (termed AbdomenAtlas) of 20,460 three-dimensional CT volumes sourced from 112 hospitals across diverse populations, geographies, and facilities. AbdomenAtlas provides 673K high-quality masks of anatomical structures in the abdominal region annotated by a team of 10 radiolog...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	475,693
2312.02798	Weakly Supervised Detection of Hallucinations in LLM Activations	We propose an auditing method to identify whether a large language model (LLM) encodes patterns such as hallucinations in its internal states, which may propagate to downstream tasks. We introduce a weakly supervised auditing technique using a subset scanning approach to detect anomalous patterns in LLM activations fro...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	413,009
1712.02985	A Classification of Functions in Multiterminal Distributed Computing	In the distributed function computation problem, dichotomy theorems, initiated by Han-Kobayashi, seek to classify functions by whether the rate regions for function computation improve on the Slepian-Wolf regions or not. In this paper, we develop a general approach to derive converse bounds on the distributed function ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	86,381
1910.01888	Measuring Arithmetic Extrapolation Performance	The Neural Arithmetic Logic Unit (NALU) is a neural network layer that can learn exact arithmetic operations between the elements of a hidden state. The goal of NALU is to learn perfect extrapolation, which requires learning the exact underlying logic of an unknown arithmetic problem. Evaluating the performance of the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	148,069
2403.12407	Cross-Lingual Transfer for Natural Language Inference via Multilingual Prompt Translator	Based on multilingual pre-trained models, cross-lingual transfer with prompt learning has shown promising effectiveness, where soft prompt learned in a source language is transferred to target languages for downstream tasks, particularly in the low-resource scenario. To efficiently transfer soft prompt, we propose a no...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	439,162
2311.14276	Racing With ROS 2 A Navigation System for an Autonomous Formula Student Race Car	The advent of autonomous vehicle technologies has significantly impacted various sectors, including motorsport, where Formula Student and Formula: Society of Automotive Engineers introduced autonomous racing classes. These offer new challenges to aspiring engineers, including the team at QUT Motorsport, but also raise ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	410,051
2003.09119	CentripetalNet: Pursuing High-quality Keypoint Pairs for Object Detection	Keypoint-based detectors have achieved pretty-well performance. However, incorrect keypoint matching is still widespread and greatly affects the performance of the detector. In this paper, we propose CentripetalNet which uses centripetal shift to pair corner keypoints from the same instance. CentripetalNet predicts the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	168,963
2011.12722	Attention Aware Cost Volume Pyramid Based Multi-view Stereo Network for 3D Reconstruction	We present an efficient multi-view stereo (MVS) network for 3D reconstruction from multiview images. While previous learning based reconstruction approaches performed quite well, most of them estimate depth maps at a fixed resolution using plane sweep volumes with a fixed depth hypothesis at each plane, which requires ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	208,254
1511.00776	Coherent Detection of Turbo-Coded OFDM Signals Transmitted through Frequency Selective Rayleigh Fading Channels with Receiver Diversity and Increased Throughput	In this work, we discuss techniques for coherently detecting turbo coded orthogonal frequency division multiplexed (OFDM) signals, transmitted through frequency selective Rayleigh (the magnitude of each channel tap is Rayleigh distributed) fading channels having a uniform power delay profile. The channel output is furt...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	48,439
1704.00758	Unsupervised Action Proposal Ranking through Proposal Recombination	Recently, action proposal methods have played an important role in action recognition tasks, as they reduce the search space dramatically. Most unsupervised action proposal methods tend to generate hundreds of action proposals which include many noisy, inconsistent, and unranked action proposals, while supervised actio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	71,136
1512.09327	Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server	This paper makes two contributions to Bayesian machine learning algorithms. Firstly, we propose stochastic natural gradient expectation propagation (SNEP), a novel alternative to expectation propagation (EP), a popular variational inference algorithm. SNEP is a black box variational algorithm, in that it does not requi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	50,586
2312.03979	Node-aware Bi-smoothing: Certified Robustness against Graph Injection Attacks	Deep Graph Learning (DGL) has emerged as a crucial technique across various domains. However, recent studies have exposed vulnerabilities in DGL models, such as susceptibility to evasion and poisoning attacks. While empirical and provable robustness techniques have been developed to defend against graph modification at...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	413,496
2411.10023	Model Inversion Attacks: A Survey of Approaches and Countermeasures	The success of deep neural networks has driven numerous research studies and applications from Euclidean to non-Euclidean data. However, there are increasing concerns about privacy leakage, as these networks rely on processing private data. Recently, a new type of privacy attack, the model inversion attacks (MIAs), aim...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	508,465
2101.07481	Density-Ratio Based Personalised Ranking from Implicit Feedback	Learning from implicit user feedback is challenging as we can only observe positive samples but never access negative ones. Most conventional methods cope with this issue by adopting a pairwise ranking approach with negative sampling. However, the pairwise ranking approach has a severe disadvantage in the convergence t...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	216,043
1811.02373	Sets of autoencoders with shared latent spaces	Autoencoders receive latent models of input data. It was shown in recent works that they also estimate probability density functions of the input. This fact makes using the Bayesian decision theory possible. If we obtain latent models of input data for each class or for some points in the space of parameters in a param...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	112,577
2109.07494	Making Heads and Tails of Models with Marginal Calibration for Sparse Tagsets	For interpreting the behavior of a probabilistic model, it is useful to measure a model's calibration--the extent to which it produces reliable confidence scores. We address the open problem of calibration for tagging models with sparse tagsets, and recommend strategies to measure and reduce calibration error (CE) in s...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	255,544
1711.09081	Deep Extreme Cut: From Extreme Points to Object Segmentation	This paper explores the use of extreme points in an object (left-most, right-most, top, bottom pixels) as input to obtain precise object segmentation for images and videos. We do so by adding an extra channel to the image in the input of a convolutional neural network (CNN), which contains a Gaussian centered in each o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	85,324
2404.08791	Expectation Alignment: Handling Reward Misspecification in the Presence of Expectation Mismatch	Detecting and handling misspecified objectives, such as reward functions, has been widely recognized as one of the central challenges within the domain of Artificial Intelligence (AI) safety research. However, even with the recognition of the importance of this problem, we are unaware of any works that attempt to provi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	446,400
2106.06987	Learning the Imaging Landmarks: Unsupervised Key point Detection in Lung Ultrasound Videos	Lung ultrasound (LUS) is an increasingly popular diagnostic imaging modality for continuous and periodic monitoring of lung infection, given its advantages of non-invasiveness, non-ionizing nature, portability and easy disinfection. The major landmarks assessed by clinicians for triaging using LUS are pleura, A and B l...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	240,719
1811.00761	ChemBoost: A chemical language based approach for protein-ligand binding affinity prediction	Identification of high affinity drug-target interactions is a major research question in drug discovery. Proteins are generally represented by their structures or sequences. However, structures are available only for a small subset of biomolecules and sequence similarity is not always correlated with functional similar...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	112,190
2501.10362	Reviewing Uses of Regulatory Compliance Monitoring	In order to deliver their services and products to customers, organizations need to manage numerous business processes. One important consideration thereby lies in the adherence to regulations such as laws, guidelines, or industry standards. In order to monitor adherence of their business processes to regulations - in ...	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	false	525,485
1805.08324	Measurement-wise Occlusion in Multi-object Tracking	Handling object interaction is a fundamental challenge in practical multi-object tracking, even for simple interactive effects such as one object temporarily occluding another. We formalize the problem of occlusion in tracking with two different abstractions. In object-wise occlusion, objects that are occluded by other...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	98,105
2111.03950	Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curves	We propose simple nonparametric estimators for mediated and time-varying dose response curves based on kernel ridge regression. By embedding Pearl's mediation formula and Robins' g-formula with kernels, we allow treatments, mediators, and covariates to be continuous in general spaces, and also allow for nonlinear treat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	265,329
2203.12593	Semantic Similarity Computing for Scientific Academic Conferences fused with domain features	Aiming at the problem that the current general-purpose semantic text similarity calculation methods are difficult to use the semantic information of scientific academic conference data, a semantic similarity calculation algorithm for scientific academic conferences by fusion with domain features is proposed. First, the...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	287,320
2109.11797	CPT: Colorful Prompt Tuning for Pre-trained Vision-Language Models	Pre-Trained Vision-Language Models (VL-PTMs) have shown promising capabilities in grounding natural language in image data, facilitating a broad variety of cross-modal tasks. However, we note that there exists a significant gap between the objective forms of model pre-training and fine-tuning, resulting in a need for l...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	257,062
1804.00376	End-to-End Detection and Re-identification Integrated Net for Person Search	This paper proposes a pedestrian detection and re-identification (re-id) integration net (I-Net) in an end-to-end learning framework. The I-Net is used in real-world video surveillance scenarios, where the target person needs to be searched in the whole scene videos, while the annotations of pedestrian bounding boxes a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	94,009
2302.00102	Towards Detecting Harmful Agendas in News Articles	Manipulated news online is a growing problem which necessitates the use of automated systems to curtail its spread. We argue that while misinformation and disinformation detection have been studied, there has been a lack of investment in the important open challenge of detecting harmful agendas in news articles; identi...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	343,095
2303.08877	ROSE: A Neurocomputational Architecture for Syntax	A comprehensive model of natural language processing in the brain must accommodate four components: representations, operations, structures and encoding. It further requires a principled account of how these components mechanistically, and causally, relate to each another. While previous models have isolated regions of...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	351,804
2401.08920	Idempotence and Perceptual Image Compression	Idempotence is the stability of image codec to re-compression. At the first glance, it is unrelated to perceptual image compression. However, we find that theoretically: 1) Conditional generative model-based perceptual codec satisfies idempotence; 2) Unconditional generative model with idempotence constraint is equival...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	422,075
2203.10350	CLRNet: Cross Layer Refinement Network for Lane Detection	Lane is critical in the vision navigation system of the intelligent vehicle. Naturally, lane is a traffic sign with high-level semantics, whereas it owns the specific local pattern which needs detailed low-level features to localize accurately. Using different feature levels is of great importance for accurate lane det...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	286,503
2502.00151	A Comprehensive Review: Applicability of Deep Neural Networks in Business Decision Making and Market Prediction Investment	Big data, both in its structured and unstructured formats, have brought in unforeseen challenges in economics and business. How to organize, classify, and then analyze such data to obtain meaningful insights are the ever-going research topics for business leaders and academic researchers. This paper studies recent appl...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	529,231
2409.03765	AI and Entrepreneurship: Facial Recognition Technology Detects Entrepreneurs, Outperforming Human Experts	Occupational outcomes like entrepreneurship are generally considered personal information that individuals should have the autonomy to disclose. With the advancing capability of artificial intelligence (AI) to infer private details from widely available human-centric data, such as social media, it is crucial to investi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	486,165
2207.07149	Bug Fix Time Optimization Using Matrix Factorization and Iterative Gale-Shaply Algorithms	Bug triage is an essential task in software maintenance phase. It assigns developers (fixers) to bug reports to fix them. This process is performed manually by a triager, who analyzes developers profiles and submitted bug reports to make suitable assignments. Bug triaging process is time consuming thus automating this ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	308,117
2204.12024	Reprint: a randomized extrapolation based on principal components for data augmentation	Data scarcity and data imbalance have attracted a lot of attention in many fields. Data augmentation, explored as an effective approach to tackle them, can improve the robustness and efficiency of classification models by generating new samples. This paper presents REPRINT, a simple and effective hidden-space data augm...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	293,340
2002.08740	Towards Certifiable Adversarial Sample Detection	Convolutional Neural Networks (CNNs) are deployed in more and more classification systems, but adversarial samples can be maliciously crafted to trick them, and are becoming a real threat. There have been various proposals to improve CNNs' adversarial robustness but these all suffer performance penalties or other limit...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	164,851
2501.08418	CVaR-Based Variational Quantum Optimization for User Association in Handoff-Aware Vehicular Networks	Efficient resource allocation is essential for optimizing various tasks in wireless networks, which are usually formulated as generalized assignment problems (GAP). GAP, as a generalized version of the linear sum assignment problem, involves both equality and inequality constraints that add computational challenges. In...	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	true	524,748
2305.10396	Cultural Differences in Signed Ego Networks on Twitter: An Investigatory Analysis	Human social behaviour has been observed to adhere to certain structures. One such structure, the Ego Network Model (ENM), has been found almost ubiquitously in human society. Recently, this model has been extended to include signed connections. While the unsigned ENM has been rigorously observed for decades, the signe...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	365,034
2306.02964	Beyond Harm: an Ethical Framework to Tackle Misinformation on Social Media	This paper aims to build an actionable framework for permissible online content moderation to combat misinformation. Often strong content moderation policies are invoked when misinformation causes harm. By adopting Mill's ethical framework, I show the complexities involved in permissible content moderation. The conclus...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	371,133
2211.04673	Syntax-Aware On-the-Fly Code Completion	Code completion aims to help improve developers' productivity by suggesting the next code tokens from a given context. Various approaches have been proposed to incorporate abstract syntax tree (AST) information for model training, ensuring that code completion is aware of the syntax of the programming languages. Howeve...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	329,318
1210.5167	Influence of the Dynamic Social Network Timeframe Type and Size on the Group Evolution Discovery	New technologies allow to store vast amount of data about users interaction. From those data the social network can be created. Additionally, because usually also time and dates of this activities are stored, the dynamic of such network can be analysed by splitting it into many timeframes representing the state of the ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	19,254
1011.0490	Computational Modeling for the Activation Cycle of G-proteins by G-protein-coupled Receptors	In this paper, we survey five different computational modeling methods. For comparison, we use the activation cycle of G-proteins that regulate cellular signaling events downstream of G-protein-coupled receptors (GPCRs) as a driving example. Starting from an existing Ordinary Differential Equations (ODEs) model, we imp...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	8,107
2210.01267	Learning from Viral Content	We study learning on social media with an equilibrium model of users interacting with shared news stories. Rational users arrive sequentially, observe an original story (i.e., a private signal) and a sample of predecessors' stories in a news feed, and then decide which stories to share. The observed sample of stories d...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	321,189
2010.11272	Predicting Chemical Properties using Self-Attention Multi-task Learning based on SMILES Representation	In the computational prediction of chemical compound properties, molecular descriptors and fingerprints encoded to low dimensional vectors are used. The selection of proper molecular descriptors and fingerprints is both important and challenging as the performance of such models is highly dependent on descriptors. To o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	202,179
2305.01618	ContactArt: Learning 3D Interaction Priors for Category-level Articulated Object and Hand Poses Estimation	We propose a new dataset and a novel approach to learning hand-object interaction priors for hand and articulated object pose estimation. We first collect a dataset using visual teleoperation, where the human operator can directly play within a physical simulator to manipulate the articulated objects. We record the dat...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	361,737

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