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272705894 | 2409.12172 | 2024-09-18 | You Only Read Once (YORO): Learning to Internalize Database Knowledge for Text-to-SQL | While significant progress has been made on the text-to-SQL task, recent solutions repeatedly encode the same database schema for every question, resulting in unnecessary high inference cost and often overlooking crucial database knowledge. To address these issues, we propose You Only Read Once (YORO), a novel paradigm... | [
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272706545 | 2409.11836 | 2024-09-18 | NT-ViT: Neural Transcoding Vision Transformers for EEG-to-fMRI Synthesis | This paper introduces the Neural Transcoding Vision Transformer (\modelname), a generative model designed to estimate high-resolution functional Magnetic Resonance Imaging (fMRI) samples from simultaneous Electroencephalography (EEG) data. A key feature of \modelname is its Domain Matching (DM) sub-module which effecti... | [
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272705834 | 2409.11702 | 2024-09-18 | Discovering Conceptual Knowledge with Analytic Ontology Templates for Articulated Objects | Human cognition can leverage fundamental conceptual knowledge, like geometric and kinematic ones, to appropriately perceive, comprehend and interact with novel objects. Motivated by this finding, we aim to endow machine intelligence with an analogous capability through performing at the conceptual level, in order to un... | [
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272704222 | 2409.12053 | 2024-09-18 | Extended Deep Submodular Functions | We introduce a novel category of set functions called Extended Deep Submodular functions (EDSFs), which are neural network-representable. EDSFs serve as an extension of Deep Submodular Functions (DSFs), inheriting crucial properties from DSFs while addressing innate limitations. It is known that DSFs can represent a li... | [
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272708823 | 2409.12061 | 2024-09-18 | Generalized Robot Learning Framework | Imitation based robot learning has recently gained significant attention in the robotics field due to its theoretical potential for transferability and generalizability. However, it remains notoriously costly, both in terms of hardware and data collection, and deploying it in real-world environments demands meticulous ... | [
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272707986 | 2409.11869 | 2024-09-18 | SpheriGait: Enriching Spatial Representation via Spherical Projection for LiDAR-based Gait Recognition | Gait recognition is a rapidly progressing technique for the remote identification of individuals. Prior research predominantly employing 2D sensors to gather gait data has achieved notable advancements; nonetheless, they have unavoidably neglected the influence of 3D dynamic characteristics on recognition. Gait recogni... | [
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272703912 | 2409.12059 | 2024-09-18 | MeTHanol: Modularized Thinking Language Models with Intermediate Layer Thinking, Decoding and Bootstrapping Reasoning | Current research efforts are focused on enhancing the thinking and reasoning capability of large language model (LLM) by prompting, data-driven emergence and inference-time computation. In this study, we consider stimulating language model's thinking and cognitive abilities from a modular perspective, which mimics the ... | [
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272708564 | 2409.11925 | 2024-09-18 | Haptic-ACT: Bridging Human Intuition with Compliant Robotic Manipulation via Immersive VR | Robotic manipulation is essential for the widespread adoption of robots in industrial and home settings and has long been a focus within the robotics community. Advances in artificial intelligence have introduced promising learning-based methods to address this challenge, with imitation learning emerging as particularl... | [
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219442497 | 2409.11786 | 2024-09-18 | Efficient Low-Resolution Face Recognition via Bridge Distillation | Face recognition in the wild is now advancing towards light-weight models, fast inference speed and resolution-adapted capability. In this paper, we propose a bridge distillation approach to turn a complex face model pretrained on private high-resolution faces into a light-weight one for low-resolution face recognition... | [
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272707579 | 2409.11951 | 2024-09-18 | GaussianHeads: End-to-End Learning of Drivable Gaussian Head Avatars from Coarse-to-fine Representations | Real-time rendering of human head avatars is a cornerstone of many computer graphics applications, such as augmented reality, video games, and films, to name a few. Recent approaches address this challenge with computationally efficient geometry primitives in a carefully calibrated multi-view setup. Albeit producing ph... | [
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272704110 | 2409.11754 | 2024-09-18 | NPAT Null-Space Projected Adversarial Training Towards Zero Deterioration | To mitigate the susceptibility of neural networks to adversarial attacks, adversarial training has emerged as a prevalent and effective defense strategy. Intrinsically, this countermeasure incurs a trade-off, as it sacrifices the model's accuracy in processing normal samples. To reconcile the trade-off, we pioneer the ... | [
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272708618 | 2409.12190 | 2024-09-18 | Bundle Adjustment in the Eager Mode | Bundle adjustment (BA) is a critical technique in various robotic applications such as simultaneous localization and mapping (SLAM), augmented reality (AR), and photogrammetry. BA optimizes parameters such as camera poses and 3D landmarks to align them with observations. With the growing importance of deep learning in ... | [
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272753086 | 2409.12338 | 2024-09-18 | Can I Pet Your Robot? Incorporating Capacitive Touch Sensing into a Soft Socially Assistive Robot Platform | This work presents a method of incorporating low-cost capacitive tactile sensors on a soft socially assistive robot platform. By embedding conductive thread into the robot's crocheted exterior, we formed a set of low-cost, flexible capacitive tactile sensors that do not disrupt the robot's soft, zoomorphic embodiment. ... | [
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272708877 | 2409.12147 | 2024-09-18 | MAgICoRe: Multi-Agent, Iterative, Coarse-to-Fine Refinement for Reasoning | Large Language Models' (LLM) reasoning can be improved using test-time aggregation strategies, i.e., generating multiple samples and voting among generated samples. While these improve performance, they often reach a saturation point. Refinement offers an alternative by using LLM-generated feedback to improve solution ... | [
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272703854 | 2409.12016 | 2024-09-18 | Computational Imaging for Long-Term Prediction of Solar Irradiance | The occlusion of the sun by clouds is one of the primary sources of uncertainties in solar power generation, and is a factor that affects the wide-spread use of solar power as a primary energy source. Real-time forecasting of cloud movement and, as a result, solar irradiance is necessary to schedule and allocate energy... | [
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276318068 | 2409.12000 | 2024-09-18 | "It Might be Technically Impressive, But It's Practically Useless to us": Motivations, Practices, Challenges, and Opportunities for Cross-Functional Collaboration around AI within the News Industry | Recently, an increasing number of news organizations have integrated artificial intelligence (AI) into their workflows, leading to a further influx of AI technologists and data workers into the news industry. This has initiated cross-functional collaborations between these professionals and journalists. Although prior ... | [
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272707597 | 2409.11820 | 2024-09-18 | Optimizing Job Shop Scheduling in the Furniture Industry: A Reinforcement Learning Approach Considering Machine Setup, Batch Variability, and Intralogistics | This paper explores the potential application of Deep Reinforcement Learning in the furniture industry. To offer a broad product portfolio, most furniture manufacturers are organized as a job shop, which ultimately results in the Job Shop Scheduling Problem (JSSP). The JSSP is addressed with a focus on extending tradit... | [
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272707076 | 2409.11780 | 2024-09-18 | Explaining Non-monotonic Normative Reasoning using Argumentation Theory with Deontic Logic | In our previous research, we provided a reasoning system (called LeSAC) based on argumentation theory to provide legal support to designers during the design process. Building on this, this paper explores how to provide designers with effective explanations for their legally relevant design decisions. We extend the pre... | [
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272707883 | 2409.12156 | 2024-09-18 | JEAN: Joint Expression and Audio-guided NeRF-based Talking Face Generation | We introduce a novel method for joint expression and audio-guided talking face generation. Recent approaches either struggle to preserve the speaker identity or fail to produce faithful facial expressions. To address these challenges, we propose a NeRF-based network. Since we train our network on monocular videos witho... | [
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267071086 | 2409.12255 | 2024-09-18 | Efficient Data Subset Selection to Generalize Training Across Models: Transductive and Inductive Networks | Existing subset selection methods for efficient learning predominantly employ discrete combinatorial and model-specific approaches which lack generalizability. For an unseen architecture, one cannot use the subset chosen for a different model. To tackle this problem, we propose $\texttt{SubSelNet}$, a trainable subset ... | [
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272704887 | 2409.12034 | 2024-09-18 | Multi-Sensor Deep Learning for Glacier Mapping | The more than 200,000 glaciers outside the ice sheets play a crucial role in our society by influencing sea-level rise, water resource management, natural hazards, biodiversity, and tourism. However, only a fraction of these glaciers benefit from consistent and detailed in-situ observations that allow for assessing the... | [
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272709440 | 2409.11983 | 2024-09-18 | Intraoperative Registration by Cross-Modal Inverse Neural Rendering | We present in this paper a novel approach for 3D/2D intraoperative registration during neurosurgery via cross-modal inverse neural rendering. Our approach separates implicit neural representation into two components, handling anatomical structure preoperatively and appearance intraoperatively. This disentanglement is a... | [
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272708619 | 2409.11770 | 2024-09-18 | Knowledge Adaptation Network for Few-Shot Class-Incremental Learning | Few-shot class-incremental learning (FSCIL) aims to incrementally recognize new classes using a few samples while maintaining the performance on previously learned classes. One of the effective methods to solve this challenge is to construct prototypical evolution classifiers. Despite the advancement achieved by most e... | [
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273163256 | 2410.02795 | 2024-09-18 | TaCIE: Enhancing Instruction Comprehension in Large Language Models through Task-Centred Instruction Evolution | Large Language Models (LLMs) require precise alignment with complex instructions to optimize their performance in real-world applications. As the demand for refined instruction tuning data increases, traditional methods that evolve simple seed instructions often struggle to effectively enhance complexity or manage diff... | [
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272703908 | 2409.12011 | 2024-09-18 | Mixture of Prompt Learning for Vision Language Models | As powerful pre-trained vision-language models (VLMs) like CLIP gain prominence, numerous studies have attempted to combine VLMs for downstream tasks. Among these, prompt learning has been validated as an effective method for adapting to new tasks, which only requiring a small number of parameters. However, current pro... | [
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272706693 | 2409.12161 | 2024-09-18 | Generalized compression and compressive search of large datasets | The Big Data explosion has necessitated the development of search algorithms that scale sub-linearly in time and memory. While compression algorithms and search algorithms do exist independently, few algorithms offer both, and those which do are domain-specific. We present panCAKES, a novel approach to compressive sear... | [
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272753518 | 2409.12314 | 2024-09-18 | Understanding Implosion in Text-to-Image Generative Models | Recent works show that text-to-image generative models are surprisingly vulnerable to a variety of poisoning attacks. Empirical results find that these models can be corrupted by altering associations between individual text prompts and associated visual features. Furthermore, a number of concurrent poisoning attacks c... | [
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272910724 | 2409.17285 | 2024-09-18 | SpoofCeleb: Speech Deepfake Detection and SASV In The Wild | This paper introduces SpoofCeleb, a dataset designed for Speech Deepfake Detection (SDD) and Spoofing-robust Automatic Speaker Verification (SASV), utilizing source data from real-world conditions and spoofing attacks generated by Text-To-Speech (TTS) systems also trained on the same real-world data. Robust recognition... | [
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272753722 | 2409.12296 | 2024-09-18 | JKO for Landau: a variational particle method for homogeneous Landau equation | Inspired by the gradient flow viewpoint of the Landau equation and corresponding dynamic formulation of the Landau metric in [arXiv:2007.08591], we develop a novel implicit particle method for the Landau equation in the framework of the JKO scheme. We first reformulate the Landau metric in a computationally friendly fo... | [
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272707224 | 2409.11678 | 2024-09-18 | EnhancedRL: An Enhanced-State Reinforcement Learning Algorithm for Multi-Task Fusion in Recommender Systems | As a key stage of Recommender Systems (RSs), Multi-Task Fusion (MTF) is responsible for merging multiple scores output by Multi-Task Learning (MTL) into a single score, finally determining the recommendation results. Recently, Reinforcement Learning (RL) has been applied to MTF to maximize long-term user satisfaction w... | [
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272705854 | 2409.11718 | 2024-09-18 | Free-VSC: Free Semantics from Visual Foundation Models for Unsupervised Video Semantic Compression | Unsupervised video semantic compression (UVSC), i.e., compressing videos to better support various analysis tasks, has recently garnered attention. However, the semantic richness of previous methods remains limited, due to the single semantic learning objective, limited training data, etc. To address this, we propose t... | [
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272709150 | 2409.11889 | 2024-09-18 | M2R-Whisper: Multi-stage and Multi-scale Retrieval Augmentation for Enhancing Whisper | State-of-the-art models like OpenAI's Whisper exhibit strong performance in multilingual automatic speech recognition (ASR), but they still face challenges in accurately recognizing diverse subdialects. In this paper, we propose M2R-whisper, a novel multi-stage and multi-scale retrieval augmentation approach designed t... | [
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