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34,378
27
Title: On Onboard LiDAR-based Flying Object Detection Abstract: A new robust and accurate approach for the detection and localization of flying objects with the purpose of highly dynamic aerial interception and agile multi-robot interaction is presented in this paper. The approach is proposed for use onboard an autonom...
[ 33376, 29201, 45306, 27877 ]
Test
34,379
27
Title: RH-Map: Online Map Construction Framework of Dynamic Objects Removal Based on Region-wise Hash Map Structure Abstract: Mobile robots navigating in outdoor environments frequently encounter the issue of undesired traces left by dynamic objects and manifested as obstacles on map, impeding robots from achieving acc...
[]
Train
34,380
16
Title: A Survey of Deep Learning in Sports Applications: Perception, Comprehension, and Decision Abstract: Deep learning has the potential to revolutionize sports performance, with applications ranging from perception and comprehension to decision. This paper presents a comprehensive survey of deep learning in sports p...
[ 16480, 11273, 36811, 38060, 45039, 29239, 8824 ]
Train
34,381
16
Title: InDL: A New Datasets and Benchmark for In-Diagram Logic Interpreting based on Visual Illusion Abstract: This paper introduces a novel approach to evaluating deep learning models' capacity for in-diagram logic interpretation. Leveraging the intriguing realm of visual illusions, we establish a unique dataset, InDL...
[]
Test
34,382
24
Title: Stochastic Gradient Descent outperforms Gradient Descent in recovering a high-dimensional signal in a glassy energy landscape Abstract: Stochastic Gradient Descent (SGD) is an out-of-equilibrium algorithm used extensively to train artificial neural networks. However very little is known on to what extent SGD is ...
[]
Train
34,383
8
Title: SamurAI: A Versatile IoT Node With Event-Driven Wake-Up and Embedded ML Acceleration Abstract: Increased capabilities, such as recognition and self-adaptability, are now required from Internet-of-Things (IoT) applications. While IoT node power consumption is a major concern for these applications, cloud-based pr...
[ 5440 ]
Validation
34,384
16
Title: Video OWL-ViT: Temporally-consistent open-world localization in video Abstract: We present an architecture and a training recipe that adapts pre-trained open-world image models to localization in videos. Understanding the open visual world (without being constrained by fixed label spaces) is crucial for many rea...
[ 9419 ]
Test
34,385
30
Title: Text-Augmented Open Knowledge Graph Completion via Pre-Trained Language Models Abstract: The mission of open knowledge graph (KG) completion is to draw new findings from known facts. Existing works that augment KG completion require either (1) factual triples to enlarge the graph reasoning space or (2) manually ...
[ 19159 ]
Train
34,386
17
Title: Generator Matrices by Solving Integer Linear Programs Abstract: In quasi-Monte Carlo methods, generating high-dimensional low discrepancy sequences by generator matrices is a popular and efficient approach. Historically, constructing or finding such generator matrices has been a hard problem. In particular, it i...
[]
Test
34,387
16
Title: Explicit Visual Prompting for Universal Foreground Segmentations Abstract: Foreground segmentation is a fundamental problem in computer vision, which includes salient object detection, forgery detection, defocus blur detection, shadow detection, and camouflage object detection. Previous works have typically reli...
[ 30825 ]
Train
34,388
31
Title: Naver Labs Europe (SPLADE) @ TREC NeuCLIR 2022 Abstract: This paper describes our participation in the 2022 TREC NeuCLIR challenge. We submitted runs to two out of the three languages (Farsi and Russian), with a focus on first-stage rankers and comparing mono-lingual strategies to Adhoc ones. For monolingual run...
[ 41512, 19486 ]
Train
34,389
24
Title: A Comparative Analysis of Multiple Methods for Predicting a Specific Type of Crime in the City of Chicago Abstract: Researchers regard crime as a social phenomenon that is influenced by several physical, social, and economic factors. Different types of crimes are said to have different motivations. Theft, for in...
[]
Train
34,390
30
Title: On the Computational Power of Decoder-Only Transformer Language Models Abstract: This article presents a theoretical evaluation of the computational universality of decoder-only transformer models. We extend the theoretical literature on transformer models and show that decoder-only transformer architectures (ev...
[ 4027, 33220, 20951 ]
Test
34,391
28
Title: Improved Random-Binning Exponent for Distributed Hypothesis Testing Abstract: Shimokawa, Han, and Amari proposed a"quantization and binning"scheme for distributed binary hypothesis testing. We propose a simple improvement on the receiver's guessing rule in this scheme. This attains a better exponent of the error...
[]
Train
34,392
16
Title: SALAD: Part-Level Latent Diffusion for 3D Shape Generation and Manipulation Abstract: We present a cascaded diffusion model based on a part-level implicit 3D representation. Our model achieves state-of-the-art generation quality and also enables part-level shape editing and manipulation without any additional tr...
[ 40671 ]
Train
34,393
13
Title: Improving Time and Memory Efficiency of Genetic Algorithms by Storing Populations as Minimum Spanning Trees of Patches Abstract: In many applications of evolutionary algorithms the computational cost of applying operators and storing populations is comparable to the cost of fitness evaluation. Furthermore, by kn...
[]
Validation
34,394
24
Title: Temporal Data Meets LLM - Explainable Financial Time Series Forecasting Abstract: This paper presents a novel study on harnessing Large Language Models' (LLMs) outstanding knowledge and reasoning abilities for explainable financial time series forecasting. The application of machine learning models to financial ...
[ 40192, 13345, 13700, 24308, 5078, 15129, 45242 ]
Train
34,395
24
Title: Multi-task Hierarchical Adversarial Inverse Reinforcement Learning Abstract: Multi-task Imitation Learning (MIL) aims to train a policy capable of performing a distribution of tasks based on multi-task expert demonstrations, which is essential for general-purpose robots. Existing MIL algorithms suffer from low d...
[ 30498, 11947 ]
Test
34,396
30
Title: BEVERS: A General, Simple, and Performant Framework for Automatic Fact Verification Abstract: Automatic fact verification has become an increasingly popular topic in recent years and among datasets the Fact Extraction and VERification (FEVER) dataset is one of the most popular. In this work we present BEVERS, a ...
[ 292 ]
Train
34,397
16
Title: Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation Abstract: Whilst the availability of 3D LiDAR point cloud data has significantly grown in recent years, annotation remains expensive and time-consuming, leading to a demand for semi-supervised semantic segmentation methods ...
[ 41730, 4443 ]
Train
34,398
27
Title: CAJun: Continuous Adaptive Jumping using a Learned Centroidal Controller Abstract: We present CAJun, a novel hierarchical learning and control framework that enables legged robots to jump continuously with adaptive jumping distances. CAJun consists of a high-level centroidal policy and a low-level leg controller...
[ 43792, 27812, 43061, 28567 ]
Validation
34,399
16
Title: ShapeClipper: Scalable 3D Shape Learning from Single-View Images via Geometric and CLIP-Based Consistency Abstract: We present ShapeClipper, a novel method that reconstructs 3D object shapes from real-world single-view RGB images. Instead of relying on laborious 3D, multi-view or camera pose annotation, ShapeCli...
[ 19893 ]
Validation
34,400
24
Title: Making Binary Classification from Multiple Unlabeled Datasets Almost Free of Supervision Abstract: Training a classifier exploiting a huge amount of supervised data is expensive or even prohibited in a situation, where the labeling cost is high. The remarkable progress in working with weaker forms of supervision...
[]
Test
34,401
28
Title: A Versatile Low-Complexity Feedback Scheme for FDD Systems via Generative Modeling Abstract: In this work, we propose a versatile feedback scheme which can be deployed for both single- and multi-user multiple-input multiple-output (MIMO) frequency division duplex (FDD) systems. Particularly, we propose to use a ...
[ 3224 ]
Train
34,402
16
Title: Five A+ Network: You Only Need 9K Parameters for Underwater Image Enhancement Abstract: A lightweight underwater image enhancement network is of great significance for resource-constrained platforms, but balancing model size, computational efficiency, and enhancement performance has proven difficult for previous...
[ 11842, 29678, 32967 ]
Test
34,403
24
Title: COVID-19 Detection from Mass Spectra of Exhaled Breath Abstract: According to the World Health Organization, the SARS-CoV-2 virus generated a global emergency between 2020 and 2023 resulting in about 7 million deaths out of more than 750 million individuals diagnosed with COVID-19. During these years, polymerase...
[]
Train
34,404
34
Title: Randomized and Deterministic Attention Sparsification Algorithms for Over-parameterized Feature Dimension Abstract: Large language models (LLMs) have shown their power in different areas. Attention computation, as an important subroutine of LLMs, has also attracted interests in theory. Recently the static comput...
[ 39573, 12825, 32416, 11809, 26657, 29089, 12966, 29739, 13100, 4909, 29867, 20911, 34221, 16949, 24635, 33220, 17354, 7506, 18392, 7643, 24299, 42092, 40301, 8436, 11128 ]
Train
34,405
27
Title: Experimental System Identification and Disturbance Observer-based Control for a Monolithic $Z{\theta}_{x}{\theta}_{y}$ Precision Positioning System Abstract: A compliant parallel micromanipulator is a mechanism in which the moving platform is connected to the base through a number of flexural components. Utilizi...
[]
Test
34,406
16
Title: Rethinking Out-of-distribution (OOD) Detection: Masked Image Modeling is All You Need Abstract: The core of out-of-distribution (OOD) detection is to learn the in-distribution (ID) representation, which is distinguishable from OOD samples. Previous work applied recognition-based methods to learn the ID features,...
[ 4303 ]
Train
34,407
6
Title: The Human-Centric Metaverse: A Survey Abstract: In the era of the Web of Things, the Metaverse is expected to be the landing site for the next generation of the Internet, resulting in the increased popularity of related technologies and applications in recent years and gradually becoming the focus of Internet re...
[ 20031 ]
Test
34,408
30
Title: A Formal Perspective on Byte-Pair Encoding Abstract: Byte-Pair Encoding (BPE) is a popular algorithm used for tokenizing data in NLP, despite being devised initially as a compression method. BPE appears to be a greedy algorithm at face value, but the underlying optimization problem that BPE seeks to solve has no...
[ 8858 ]
Train
34,409
6
Title: AI and Education: An Investigation into the Use of ChatGPT for Systems Thinking Abstract: This exploratory study investigates the potential of the artificial intelligence tool, ChatGPT, to support systems thinking (ST) in various subjects. Using both general and subject specific prompts, the study assesses the a...
[]
Validation
34,410
16
Title: Defense against Adversarial Cloud Attack on Remote Sensing Salient Object Detection Abstract: Detecting the salient objects in a remote sensing image has wide applications for the interdisciplinary research. Many existing deep learning methods have been proposed for Salient Object Detection (SOD) in remote sensi...
[]
Validation
34,411
16
Title: FFT-based Dynamic Token Mixer for Vision Abstract: Multi-head-self-attention (MHSA)-equipped models have achieved notable performance in computer vision. Their computational complexity is proportional to quadratic numbers of pixels in input feature maps, resulting in slow processing, especially when dealing with...
[]
Train
34,412
30
Title: Cross-Lingual Constituency Parsing for Middle High German: A Delexicalized Approach Abstract: Constituency parsing plays a fundamental role in advancing natural language processing (NLP) tasks. However, training an automatic syntactic analysis system for ancient languages solely relying on annotated parse data i...
[]
Train
34,413
24
Title: Representation Learning Dynamics of Self-Supervised Models Abstract: Self-Supervised Learning (SSL) is an important paradigm for learning representations from unlabelled data, and SSL with neural networks has been highly successful in practice. However current theoretical analysis of SSL is mostly restricted to ...
[ 17352, 44266 ]
Train
34,414
6
Title: Screen or No Screen? Lessons Learnt from a Real-World Deployment Study of Using Voice Assistants With and Without Touchscreen for Older Adults Abstract: While voice user interfaces offer increased accessibility due to hands-free and eyes-free interactions, older adults often have challenges such as constructing ...
[]
Train
34,415
16
Title: Lightweight Improved Residual Network for Efficient Inverse Tone Mapping Abstract: The display devices like HDR10 televisions are increasingly prevalent in our daily life for visualizing high dynamic range (HDR) images. But the majority of media images on the internet remain in 8-bit standard dynamic range (SDR)...
[]
Validation
34,416
25
Title: ACE-VC: Adaptive and Controllable Voice Conversion using Explicitly Disentangled Self-supervised Speech Representations Abstract: In this work, we propose a zero-shot voice conversion method using speech representations trained with self-supervised learning. First, we develop a multi-task model to decompose a sp...
[]
Validation
34,417
27
Title: An Avatar Robot Overlaid with the 3D Human Model of a Remote Operator Abstract: Although telepresence assistive robots have made significant progress, they still lack the sense of realism and physical presence of the remote operator. This results in a lack of trust and adoption of such robots. In this paper, we ...
[ 32539 ]
Train
34,418
3
Title: Artificial Intelligence for Real Sustainability? -- What is Artificial Intelligence and Can it Help with the Sustainability Transformation? Abstract: The discussion about the disruptive possibilities of a technology called artificial intelligence (AI) is on everyone's lips. Companies and countries alike are runn...
[ 12804 ]
Train
34,419
6
Title: Supporting Piggybacked Co-Located Leisure Activities via Augmented Reality Abstract: Technology, especially the smartphone, is villainized for taking meaning and time away from in-person interactions and secluding people into “digital bubbles”. We believe this is not an intrinsic property of digital gadgets, but...
[]
Train
34,420
24
Title: Intelligent Energy Management with IoT Framework in Smart Cities Using Intelligent Analysis: An Application of Machine Learning Methods for Complex Networks and Systems Abstract: Smart buildings are increasingly using Internet of Things (IoT)-based wireless sensing systems to reduce their energy consumption and ...
[ 35406 ]
Train
34,421
16
Title: Presentation Attack Detection with Advanced CNN Models for Noncontact-based Fingerprint Systems Abstract: Touch-based fingerprint biometrics is one of the most popular biometric modalities with applications in several fields. Problems associated with touch-based techniques such as the presence of latent fingerpr...
[ 3384, 1549 ]
Train
34,422
24
Title: Unsupervised Embedding Learning for Human Activity Recognition Using Wearable Sensor Data Abstract: The embedded sensors in widely used smartphones and other wearable devices make the data of human activities more accessible. However, recognizing different human activities from the wearable sensor data remains a...
[ 5737 ]
Validation
34,423
30
Title: PIVOINE: Instruction Tuning for Open-world Information Extraction Abstract: We consider the problem of Open-world Information Extraction (Open-world IE), which extracts comprehensive entity profiles from unstructured texts. Different from the conventional closed-world setting of Information Extraction (IE), Open...
[ 40192, 13185, 45018, 13700, 40901, 30221, 9264, 31189, 23898, 44124 ]
Train
34,424
27
Title: DexPBT: Scaling up Dexterous Manipulation for Hand-Arm Systems with Population Based Training Abstract: In this work, we propose algorithms and methods that enable learning dexterous object manipulation using simulated one- or two-armed robots equipped with multi-fingered hand end-effectors. Using a parallel GPU...
[]
Train
34,425
16
Title: Reinforced Disentanglement for Face Swapping without Skip Connection Abstract: The SOTA face swap models still suffer the problem of either target identity (i.e., shape) being leaked or the target non-identity attributes (i.e., background, hair) failing to be fully preserved in the final results. We show that th...
[]
Train
34,426
24
Title: The Quantization Model of Neural Scaling Abstract: We propose the $\textit{Quantization Model}$ of neural scaling laws, explaining both the observed power law dropoff of loss with model and data size, and also the sudden emergence of new capabilities with scale. We derive this model from what we call the $\texti...
[ 38338, 10756, 27880, 38834, 28154 ]
Train
34,427
24
Title: Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning Abstract: In many real-world tasks, the concerned objects can be represented as a multi-instance bag associated with a candidate label set, which consists of one ground-truth label and several false positive labels. Multi-instance partia...
[]
Test
34,428
27
Title: An MPC-based Optimal Motion Control Framework for Pendulum-driven Spherical Robots Abstract: Motion control is essential for all autonomous mobile robots, and even more so for spherical robots. Due to the uniqueness of the spherical robot, its motion control must not only ensure accurate tracking of the target c...
[]
Train
34,429
38
Title: Handwriting Analysis on the Diaries of Rosamond Jacob Abstract: Handwriting is an art form that most people learn at an early age. Each person's writing style is unique with small changes as we grow older and as our mood changes. Here we analyse handwritten text in a culturally significant personal diary. We com...
[]
Test
34,430
28
Title: Reduced-Complexity Cross-Domain Iterative Detection for OTFS Modulation via Delay-Doppler Decoupling Abstract: In this paper, a reduced-complexity cross-domain iterative detection for orthogonal time frequency space (OTFS) modulation is proposed, which exploits channel properties in both time and delay-Doppler d...
[ 17957 ]
Train
34,431
16
Title: Dermoscopic Dark Corner Artifacts Removal: Friend or Foe? Abstract: One of the more significant obstacles in classification of skin cancer is the presence of artifacts. This paper investigates the effect of dark corner artifacts, which result from the use of dermoscopes, on the performance of a deep learning bin...
[]
Test
34,432
27
Title: SLAS: Speed and Lane Advisory System for Highway Navigation Abstract: This paper proposes a hierarchical autonomous vehicle navigation architecture, composed of a high-level speed and lane advisory system (SLAS) coupled with low-level trajectory generation and trajectory following modules. Specifically, we targe...
[]
Train
34,433
16
Title: An Improved Baseline Framework for Pose Estimation Challenge at ECCV 2022 Visual Perception for Navigation in Human Environments Workshop Abstract: This technical report describes our first-place solution to the pose estimation challenge at ECCV 2022 Visual Perception for Navigation in Human Environments Worksho...
[]
Validation
34,434
31
Title: DRGame: Diversified Recommendation for Multi-category Video Games with Balanced Implicit Preferences Abstract: The growing popularity of subscription services in video game consumption has emphasized the importance of offering diversified recommendations. Providing users with a diverse range of games is essentia...
[ 32100 ]
Train
34,435
2
Title: Algebraic, Topological, and Mereological Foundations of Existential Granules Abstract: In this research, new concepts of existential granules that determine themselves are invented, and are characterized from algebraic, topological, and mereological perspectives. Existential granules are those that determine the...
[ 38921 ]
Train
34,436
24
Title: Equal Confusion Fairness: Measuring Group-Based Disparities in Automated Decision Systems Abstract: As artificial intelligence plays an increasingly substantial role in decisions affecting humans and society, the accountability of automated decision systems has been receiving increasing attention from researcher...
[]
Train
34,437
28
Title: Fast Decoding of Lifted Interleaved Linearized Reed-Solomon Codes for Multishot Network Coding Abstract: Mart{\'\i}nez-Pe{\~n}as and Kschischang (IEEE Trans.\ Inf.\ Theory, 2019) proposed lifted linearized Reed--Solomon codes as suitable codes for error control in multishot network coding. We show how to constru...
[ 25508 ]
Train
34,438
30
Title: Detecting LLM-Generated Text in Computing Education: A Comparative Study for ChatGPT Cases Abstract: Due to the recent improvements and wide availability of Large Language Models (LLMs), they have posed a serious threat to academic integrity in education. Modern LLM-generated text detectors attempt to combat the...
[ 497, 7796, 13678, 25367 ]
Train
34,439
27
Title: Language-Conditioned Observation Models for Visual Object Search Abstract: Object search is a challenging task because when given complex language descriptions (e.g.,"find the white cup on the table"), the robot must move its camera through the environment and recognize the described object. Previous works map l...
[]
Test
34,440
24
Title: A Closer Look at In-Context Learning under Distribution Shifts Abstract: In-context learning, a capability that enables a model to learn from input examples on the fly without necessitating weight updates, is a defining characteristic of large language models. In this work, we follow the setting proposed in (Gar...
[ 10945, 3795, 2518 ]
Train
34,441
24
Title: A Game-theoretic Framework for Federated Learning Abstract: In federated learning, benign participants aim to optimize a global model collaboratively. However, the risk of \textit{privacy leakage} cannot be ignored in the presence of \textit{semi-honest} adversaries. Existing research has focused either on desig...
[ 12947 ]
Test
34,442
31
Title: Methods and Tools to Advance the Retrieval of Mathematical Knowledge from Digital Libraries for Search-, Recommendation-, and Assistance-Systems Abstract: This project investigated new approaches and technologies to enhance the accessibility of mathematical content and its semantic information for a broad range ...
[]
Train
34,443
16
Title: Rewarded meta-pruning: Meta Learning with Rewards for Channel Pruning Abstract: Convolutional Neural Networks (CNNs) have a large number of parameters and take significantly large hardware resources to compute, so edge devices struggle to run high-level networks. This paper proposes a novel method to reduce the ...
[]
Train
34,444
24
Title: Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How Abstract: With the ever-increasing number of pretrained models, machine learning practitioners are continuously faced with which pretrained model to use, and how to finetune it for a new dataset. In this paper, we propose a methodology that ...
[ 34849, 694, 42263 ]
Test
34,445
16
Title: Learning Pose Image Manifolds Using Geometry-Preserving GANs and Elasticae Abstract: This paper investigates the challenge of learning image manifolds, specifically pose manifolds, of 3D objects using limited training data. It proposes a DNN approach to manifold learning and for predicting images of objects for ...
[]
Test
34,446
24
Title: Privacy Preserving Federated Learning with Convolutional Variational Bottlenecks Abstract: Gradient inversion attacks are an ubiquitous threat in federated learning as they exploit gradient leakage to reconstruct supposedly private training data. Recent work has proposed to prevent gradient leakage without loss ...
[ 37486, 15495 ]
Train
34,447
24
Title: Improve in-situ life prediction and classification performance by capturing both the present state and evolution rate of battery aging Abstract: This study develops a methodology by capturing both the battery aging state and degradation rate for improved life prediction performance. The aging state is indicated ...
[]
Test
34,448
16
Title: DiffuScene: Scene Graph Denoising Diffusion Probabilistic Model for Generative Indoor Scene Synthesis Abstract: We present DiffuScene for indoor 3D scene synthesis based on a novel scene graph denoising diffusion probabilistic model, which generates 3D instance properties stored in a fully-connected scene graph ...
[ 21997, 34000, 33425, 7231, 29439 ]
Train
34,449
24
Title: Explainable AI for Time Series via Virtual Inspection Layers Abstract: The field of eXplainable Artificial Intelligence (XAI) has greatly advanced in recent years, but progress has mainly been made in computer vision and natural language processing. For time series, where the input is often not interpretable, on...
[ 40913, 164 ]
Train
34,450
24
Title: Re-embedding data to strengthen recovery guarantees of clustering Abstract: We propose a clustering method that involves chaining four known techniques into a pipeline yielding an algorithm with stronger recovery guarantees than any of the four components separately. Given $n$ points in $\mathbb R^d$, the first ...
[]
Train
34,451
10
Title: MinT: Boosting Generalization in Mathematical Reasoning via Multi-View Fine-Tuning Abstract: Reasoning in mathematical domains remains a significant challenge for relatively small language models (LMs). Many current methods focus on specializing LMs in mathematical reasoning and rely heavily on knowledge distill...
[ 6353, 13700, 12741, 33207 ]
Validation
34,452
24
Title: HOPE: Human-Centric Off-Policy Evaluation for E-Learning and Healthcare Abstract: Reinforcement learning (RL) has been extensively researched for enhancing human-environment interactions in various human-centric tasks, including e-learning and healthcare. Since deploying and evaluating policies online are high-s...
[ 38919, 28811, 27244, 7543 ]
Validation
34,453
3
Title: Human Culture: A History Irrelevant and Predictable Experience Abstract: Human culture research has witnessed an opportunity of revolution thanks to the big data and social network revolution. Websites such as Douban.com, Goodreads.com, Pandora and IMDB become the new gold mine for cultural researchers. In 2021 ...
[ 14763 ]
Train
34,454
34
Title: Tight algorithms for connectivity problems parameterized by clique-width Abstract: The complexity of problems involving global constraints is usually much more difficult to understand than the complexity of problems only involving local constraints. A natural form of global constraints are connectivity constrain...
[ 10153, 44242, 9230, 34601 ]
Validation
34,455
27
Title: Robust human position estimation in cooperative robotic cells Abstract: nan
[ 46107, 12635 ]
Train
34,456
37
Title: Towards Multifaceted Human-Centered AI Abstract: Human-centered AI workflows involve stakeholders with multiple roles interacting with each other and automated agents to accomplish diverse tasks. In this paper, we call for a holistic view when designing support mechanisms, such as interaction paradigms, interfac...
[ 25375 ]
Validation
34,457
30
Title: LARG, Language-based Automatic Reward and Goal Generation Abstract: Goal-conditioned and Multi-Task Reinforcement Learning (GCRL and MTRL) address numerous problems related to robot learning, including locomotion, navigation, and manipulation scenarios. Recent works focusing on language-defined robotic manipulat...
[ 17153 ]
Validation
34,458
31
Title: Task2KB: A Public Task-Oriented Knowledge Base Abstract: Search engines and conversational assistants are commonly used to help users complete their every day tasks such as booking travel, cooking, etc. While there are some existing datasets that can be used for this purpose, their coverage is limited to very fe...
[]
Train
34,459
36
Title: Block-Coordinate Methods and Restarting for Solving Extensive-Form Games Abstract: Coordinate descent methods are popular in machine learning and optimization for their simple sparse updates and excellent practical performance. In the context of large-scale sequential game solving, these same properties would be...
[]
Validation
34,460
24
Title: Recurrent Memory Decision Transformer Abstract: Originally developed for natural language problems, transformer models have recently been widely used in offline reinforcement learning tasks. This is because the agent's history can be represented as a sequence, and the whole task can be reduced to the sequence mo...
[ 13564 ]
Train
34,461
16
Title: Semi-Structured Object Sequence Encoders Abstract: In this paper we explore the task of modeling semi-structured object sequences; in particular, we focus our attention on the problem of developing a structure-aware input representation for such sequences. Examples of such data include user activity on websites,...
[ 12478 ]
Train
34,462
24
Title: GibbsDDRM: A Partially Collapsed Gibbs Sampler for Solving Blind Inverse Problems with Denoising Diffusion Restoration Abstract: Pre-trained diffusion models have been successfully used as priors in a variety of linear inverse problems, where the goal is to reconstruct a signal from noisy linear measurements. Ho...
[ 30151, 31943, 15663, 500, 13336 ]
Validation
34,463
28
Title: Adaptive Greedy Rejection Sampling Abstract: We consider channel simulation protocols between two communicating parties, Alice and Bob. First, Alice receives a target distribution Q, unknown to Bob. Then, she employs a shared coding distribution P to send the minimum amount of information to Bob so that he can s...
[ 24064 ]
Train
34,464
16
Title: Multimodal Video Adapter for Parameter Efficient Video Text Retrieval Abstract: State-of-the-art video-text retrieval (VTR) methods usually fully fine-tune the pre-trained model (e.g. CLIP) on specific datasets, which may suffer from substantial storage costs in practical applications since a separate model per ...
[ 3520, 43179, 13805, 40528 ]
Validation
34,465
24
Title: Graph-level representations using ensemble-based readout functions Abstract: Graph machine learning models have been successfully deployed in a variety of application areas. One of the most prominent types of models - Graph Neural Networks (GNNs) - provides an elegant way of extracting expressive node-level repr...
[]
Test
34,466
31
Title: TBIN: Modeling Long Textual Behavior Data for CTR Prediction Abstract: Click-through rate (CTR) prediction plays a pivotal role in the success of recommendations. Inspired by the recent thriving of language models (LMs), a surge of works improve prediction by organizing user behavior data in a \textbf{textual} f...
[ 33697, 13700, 4297, 9783, 43641 ]
Test
34,467
26
Title: SynGraphy: Succinct Summarisation of Large Networks via Small Synthetic Representative Graphs Abstract: We describe SynGraphy, a method for visually summarising the structure of large network datasets that works by drawing smaller graphs generated to have similar structural properties to the input graphs. Visual...
[]
Train
34,468
10
Title: Gender mobility in the labor market with skills-based matching models Abstract: Skills-based matching promises mobility of workers between different sectors and occupations in the labor market. In this case, job seekers can look for jobs they do not yet have experience in, but for which they do have relevant ski...
[]
Train
34,469
6
Title: Conversation Regression Testing: A Design Technique for Prototyping Generalizable Prompt Strategies for Pre-trained Language Models Abstract: Pre-trained language models (LLMs) such as GPT-3 can carry fluent, multi-turn conversations out-of-the-box, making them attractive materials for chatbot design. Further, d...
[]
Train
34,470
30
Title: Improving Grammar-based Sequence-to-Sequence Modeling with Decomposition and Constraints Abstract: Neural QCFG is a grammar-based sequence-to-sequence model with strong inductive biases on hierarchical structures. It excels in interpretability and generalization but suffers from expensive inference. In this pape...
[]
Train
34,471
13
Title: Invariants for neural automata Abstract: Computational modeling of neurodynamical systems often deploys neural networks and symbolic dynamics. One particular way for combining these approaches within a framework called vector symbolic architectures leads to neural automata. Specifically, neural automata result f...
[]
Train
34,472
24
Title: Neural Network Pruning as Spectrum Preserving Process Abstract: Neural networks have achieved remarkable performance in various application domains. Nevertheless, a large number of weights in pre-trained deep neural networks prohibit them from being deployed on smartphones and embedded systems. It is highly desi...
[ 23588 ]
Train
34,473
24
Title: Exploring the Carbon Footprint of Hugging Face's ML Models: A Repository Mining Study Abstract: The rise of machine learning (ML) systems has exacerbated their carbon footprint due to increased capabilities and model sizes. However, there is scarce knowledge on how the carbon footprint of ML models is actually m...
[ 43424, 22158, 7984, 28274, 14488 ]
Validation
34,474
37
Title: Change Propagation Without Joins Abstract: We revisit the classical change propagation framework for query evaluation under updates. The standard framework takes a query plan and materializes the intermediate views, which incurs high polynomial costs in both space and time, with the join operator being the culpr...
[]
Train
34,475
30
Title: LinkTransformer: A Unified Package for Record Linkage with Transformer Language Models Abstract: Linking information across sources is fundamental to a variety of analyses in social science, business, and government. While large language models (LLMs) offer enormous promise for improving record linkage in noisy ...
[ 34236, 3084, 1469 ]
Train
34,476
30
Title: Learning to Generate Equitable Text in Dialogue from Biased Training Data Abstract: The ingrained principles of fairness in a dialogue system’s decision-making process and generated responses are crucial for user engagement, satisfaction, and task achievement. Absence of equitable and inclusive principles can hi...
[]
Train
34,477
30
Title: Dynosaur: A Dynamic Growth Paradigm for Instruction-Tuning Data Curation Abstract: Instruction tuning has emerged to enhance the capabilities of large language models (LLMs) in providing appropriate outputs based on input instructions. However, existing methods for collecting instruction-tuning data suffer from ...
[ 13345, 13700, 25892, 10598, 13257, 25226, 10163, 40341, 16698 ]
Validation