id stringlengths 9 16 | title stringlengths 4 278 | categories listlengths 1 13 | abstract stringlengths 3 4.08k | filtered_category_membership dict |
|---|---|---|---|---|
2411.18015 | AEGIS: An Agent-based Framework for General Bug Reproduction from Issue
Descriptions | [
"cs.SE",
"cs.AI"
] | In software maintenance, bug reproduction is essential for effective fault localization and repair. Manually writing reproduction scripts is a time-consuming task with high requirements for developers. Hence, automation of bug reproduction has increasingly attracted attention from researchers and practitioners. However... | {
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2411.18018 | Neural Finite-State Machines for Surgical Phase Recognition | [
"eess.IV",
"cs.CV"
] | Surgical phase recognition is essential for analyzing procedure-specific surgical videos. While recent transformer-based architectures have advanced sequence processing capabilities, they struggle with maintaining consistency across lengthy surgical procedures. Drawing inspiration from classical hidden Markov models' f... | {
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2411.18021 | Can bidirectional encoder become the ultimate winner for downstream
applications of foundation models? | [
"cs.CL"
] | Over the past few decades, Artificial Intelligence(AI) has progressed from the initial machine learning stage to the deep learning stage, and now to the stage of foundational models. Foundational models have the characteristics of pre-training, transfer learning, and self-supervised learning, and pre-trained models can... | {
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2411.18025 | Pixel-aligned RGB-NIR Stereo Imaging and Dataset for Robot Vision | [
"cs.CV"
] | Integrating RGB and NIR stereo imaging provides complementary spectral information, potentially enhancing robotic 3D vision in challenging lighting conditions. However, existing datasets and imaging systems lack pixel-level alignment between RGB and NIR images, posing challenges for downstream vision tasks. In this pap... | {
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2411.18037 | Normative Feeling: Socially Patterned Affective Mechanisms | [
"cs.MA"
] | Norms and the normative processes that enforce them such as social maintenance are considered fundamental building blocks of human societies, shaping many aspects of our cognition. However, emerging work argues that the building blocks of normativity emerged much earlier in evolution than previously considered. In ligh... | {
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2411.18038 | VLM-HOI: Vision Language Models for Interpretable Human-Object
Interaction Analysis | [
"cs.CV",
"cs.AI"
] | The Large Vision Language Model (VLM) has recently addressed remarkable progress in bridging two fundamental modalities. VLM, trained by a sufficiently large dataset, exhibits a comprehensive understanding of both visual and linguistic to perform diverse tasks. To distill this knowledge accurately, in this paper, we in... | {
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2411.18042 | HyperGLM: HyperGraph for Video Scene Graph Generation and Anticipation | [
"cs.CV"
] | Multimodal LLMs have advanced vision-language tasks but still struggle with understanding video scenes. To bridge this gap, Video Scene Graph Generation (VidSGG) has emerged to capture multi-object relationships across video frames. However, prior methods rely on pairwise connections, limiting their ability to handle c... | {
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2411.18043 | Heterogeneous Relationships of Subjects and Shapelets for
Semi-supervised Multivariate Series Classification | [
"cs.LG",
"cs.AI"
] | Multivariate time series (MTS) classification is widely applied in fields such as industry, healthcare, and finance, aiming to extract key features from complex time series data for accurate decision-making and prediction. However, existing methods for MTS often struggle due to the challenges of effectively modeling hi... | {
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2411.18050 | RL for Mitigating Cascading Failures: Targeted Exploration via
Sensitivity Factors | [
"cs.LG",
"cs.AI",
"cs.SY",
"eess.SY"
] | Electricity grid's resiliency and climate change strongly impact one another due to an array of technical and policy-related decisions that impact both. This paper introduces a physics-informed machine learning-based framework to enhance grid's resiliency. Specifically, when encountering disruptive events, this paper d... | {
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2411.18054 | Using different sources of ground truths and transfer learning to
improve the generalization of photometric redshift estimation | [
"astro-ph.IM",
"astro-ph.GA",
"cs.LG"
] | In this work, we explore methods to improve galaxy redshift predictions by combining different ground truths. Traditional machine learning models rely on training sets with known spectroscopic redshifts, which are precise but only represent a limited sample of galaxies. To make redshift models more generalizable to the... | {
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2411.18055 | FAMES: Fast Approximate Multiplier Substitution for Mixed-Precision
Quantized DNNs--Down to 2 Bits! | [
"cs.LG",
"cs.ET"
] | A widely-used technique in designing energy-efficient deep neural network (DNN) accelerators is quantization. Recent progress in this direction has reduced the bitwidths used in DNN down to 2. Meanwhile, many prior works apply approximate multipliers (AppMuls) in designing DNN accelerators to lower their energy consump... | {
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2411.18060 | ORIS: Online Active Learning Using Reinforcement Learning-based
Inclusive Sampling for Robust Streaming Analytics System | [
"cs.LG"
] | Effective labeled data collection plays a critical role in developing and fine-tuning robust streaming analytics systems. However, continuously labeling documents to filter relevant information poses significant challenges like limited labeling budget or lack of high-quality labels. There is a need for efficient human-... | {
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2411.18061 | Multi-task Gaze Estimation Via Unidirectional Convolution | [
"cs.CV"
] | Using lightweight models as backbone networks in gaze estimation tasks often results in significant performance degradation. The main reason is that the number of feature channels in lightweight networks is usually small, which makes the model expression ability limited. In order to improve the performance of lightweig... | {
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2411.18063 | Mortality Prediction of Pulmonary Embolism Patients with Deep Learning
and XGBoost | [
"eess.IV",
"cs.CV",
"cs.LG"
] | Pulmonary Embolism (PE) is a serious cardiovascular condition that remains a leading cause of mortality and critical illness, underscoring the need for enhanced diagnostic strategies. Conventional clinical methods have limited success in predicting 30-day in-hospital mortality of PE patients. In this study, we present ... | {
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2411.18064 | Lightweight Gaze Estimation Model Via Fusion Global Information | [
"cs.CV"
] | Deep learning-based appearance gaze estimation methods are gaining popularity due to their high accuracy and fewer constraints from the environment. However, existing high-precision models often rely on deeper networks, leading to problems such as large parameters, long training time, and slow convergence. In terms of ... | {
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2411.18066 | GLS: Geometry-aware 3D Language Gaussian Splatting | [
"cs.CV"
] | Recently, 3D Gaussian Splatting (3DGS) has achieved significant performance on indoor surface reconstruction and open-vocabulary segmentation. This paper presents GLS, a unified framework of surface reconstruction and open-vocabulary segmentation based on 3DGS. GLS extends two fields by exploring the correlation betwee... | {
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2411.18068 | PersonaCraft: Personalized Full-Body Image Synthesis for Multiple
Identities from Single References Using 3D-Model-Conditioned Diffusion | [
"cs.CV",
"cs.AI"
] | Personalized image generation has been significantly advanced, enabling the creation of highly realistic and customized images. However, existing methods often struggle with generating images of multiple people due to occlusions and fail to accurately personalize full-body shapes. In this paper, we propose PersonaCraft... | {
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2411.18069 | Overview of TREC 2024 Biomedical Generative Retrieval (BioGen) Track | [
"cs.IR"
] | With the advancement of large language models (LLMs), the biomedical domain has seen significant progress and improvement in multiple tasks such as biomedical question answering, lay language summarization of the biomedical literature, clinical note summarization, etc. However, hallucinations or confabulations remain o... | {
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2411.18070 | Large Scale Evaluation of Deep Learning-based Explainable Solar Flare
Forecasting Models with Attribution-based Proximity Analysis | [
"cs.LG",
"astro-ph.SR",
"cs.CV",
"stat.ML"
] | Accurate and reliable predictions of solar flares are essential due to their potentially significant impact on Earth and space-based infrastructure. Although deep learning models have shown notable predictive capabilities in this domain, current evaluations often focus on accuracy while neglecting interpretability and ... | {
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2411.18071 | Simulating Tabular Datasets through LLMs to Rapidly Explore Hypotheses
about Real-World Entities | [
"cs.AI"
] | Do horror writers have worse childhoods than other writers? Though biographical details are known about many writers, quantitatively exploring such a qualitative hypothesis requires significant human effort, e.g. to sift through many biographies and interviews of writers and to iteratively search for quantitative featu... | {
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2411.18072 | SmileSplat: Generalizable Gaussian Splats for Unconstrained Sparse
Images | [
"cs.CV"
] | Sparse Multi-view Images can be Learned to predict explicit radiance fields via Generalizable Gaussian Splatting approaches, which can achieve wider application prospects in real-life when ground-truth camera parameters are not required as inputs. In this paper, a novel generalizable Gaussian Splatting method, SmileSpl... | {
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2411.18073 | DuMapper: Towards Automatic Verification of Large-Scale POIs with Street
Views at Baidu Maps | [
"cs.AI",
"cs.IR"
] | With the increased popularity of mobile devices, Web mapping services have become an indispensable tool in our daily lives. To provide user-satisfied services, such as location searches, the point of interest (POI) database is the fundamental infrastructure, as it archives multimodal information on billions of geograph... | {
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2411.18077 | MiniKV: Pushing the Limits of LLM Inference via 2-Bit
Layer-Discriminative KV Cache | [
"cs.CL",
"cs.LG"
] | How to efficiently serve LLMs in practice has become exceptionally challenging due to their prohibitive memory and computation requirements. In this study, we investigate optimizing the KV cache, whose memory footprint poses a critical bottleneck in LLM inference, especially when dealing with long context tasks. To tac... | {
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2411.18078 | Dual-Level Boost Network for Long-Tail Prohibited Items Detection in
X-ray Security Inspection | [
"cs.CV"
] | The detection of prohibited items in X-ray security inspections is vital for ensuring public safety. However, the long-tail distribution of item categories, where certain prohibited items are far less common, poses a big challenge for detection models, as rare categories often lack sufficient training data. Existing me... | {
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2411.18082 | Dual-view X-ray Detection: Can AI Detect Prohibited Items from Dual-view
X-ray Images like Humans? | [
"cs.CV"
] | To detect prohibited items in challenging categories, human inspectors typically rely on images from two distinct views (vertical and side). Can AI detect prohibited items from dual-view X-ray images in the same way humans do? Existing X-ray datasets often suffer from limitations, such as single-view imaging or insuffi... | {
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2411.18084 | From Exploration to Revelation: Detecting Dark Patterns in Mobile Apps | [
"cs.SE",
"cs.AI",
"cs.HC"
] | Mobile apps are essential in daily life, yet they often employ dark patterns, such as visual tricks to highlight certain options or linguistic tactics to nag users into making purchases, to manipulate user behavior. Current research mainly uses manual methods to detect dark patterns, a process that is time-consuming an... | {
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2411.18085 | MONOPOLY: Learning to Price Public Facilities for Revaluing Private
Properties with Large-Scale Urban Data | [
"cs.AI",
"cs.SI"
] | The value assessment of private properties is an attractive but challenging task which is widely concerned by a majority of people around the world. A prolonged topic among us is ``\textit{how much is my house worth?}''. To answer this question, most experienced agencies would like to price a property given the factors... | {
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2411.18086 | DMVC-Tracker: Distributed Multi-Agent Trajectory Planning for Target
Tracking Using Dynamic Buffered Voronoi and Inter-Visibility Cells | [
"cs.RO",
"cs.SY",
"eess.SY"
] | This letter presents a distributed trajectory planning method for multi-agent aerial tracking. The proposed method uses a Dynamic Buffered Voronoi Cell (DBVC) and a Dynamic Inter-Visibility Cell (DIVC) to formulate the distributed trajectory generation. Specifically, the DBVC and the DIVC are time-variant spaces that p... | {
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2411.18092 | Training Noise Token Pruning | [
"cs.CV"
] | In the present work we present Training Noise Token (TNT) Pruning for vision transformers. Our method relaxes the discrete token dropping condition to continuous additive noise, providing smooth optimization in training, while retaining discrete dropping computational gains in deployment settings. We provide theoretica... | {
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2411.18095 | Derivation of Closed Form of Expected Improvement for Gaussian Process
Trained on Log-Transformed Objective | [
"cs.LG",
"cs.AI",
"stat.ML"
] | Expected Improvement (EI) is arguably the most widely used acquisition function in Bayesian optimization. However, it is often challenging to enhance the performance with EI due to its sensitivity to numerical precision. Previously, Hutter et al. (2009) tackled this problem by using Gaussian process trained on the log-... | {
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2411.18099 | Fine-Tuning Small Embeddings for Elevated Performance | [
"cs.CL"
] | Contextual Embeddings have yielded state-of-the-art results in various natural language processing tasks. However, these embeddings are constrained by models requiring large amounts of data and huge computing power. This is an issue for low-resource languages like Nepali as the amount of data available over the interne... | {
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2411.18101 | Aligning Knowledge Concepts to Whole Slide Images for Precise
Histopathology Image Analysis | [
"cs.CV",
"cs.LG"
] | Due to the large size and lack of fine-grained annotation, Whole Slide Images (WSIs) analysis is commonly approached as a Multiple Instance Learning (MIL) problem. However, previous studies only learn from training data, posing a stark contrast to how human clinicians teach each other and reason about histopathologic e... | {
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2411.18104 | Training and Evaluating Language Models with Template-based Data
Generation | [
"cs.CL",
"cs.AI",
"cs.LG"
] | The rapid advancement of large language models (LLMs) such as GPT-3, PaLM, and Llama has significantly transformed natural language processing, showcasing remarkable capabilities in understanding and generating language. However, these models often struggle with tasks requiring complex reasoning, particularly in mathem... | {
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2411.18109 | Training Data Synthesis with Difficulty Controlled Diffusion Model | [
"cs.CV"
] | Semi-supervised learning (SSL) can improve model performance by leveraging unlabeled images, which can be collected from public image sources with low costs. In recent years, synthetic images have become increasingly common in public image sources due to rapid advances in generative models. Therefore, it is becoming in... | {
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2411.18111 | When Large Vision-Language Models Meet Person Re-Identification | [
"cs.CV"
] | Large Vision-Language Models (LVLMs) that incorporate visual models and Large Language Models (LLMs) have achieved impressive results across various cross-modal understanding and reasoning tasks. In recent years, person re-identification (ReID) has also started to explore cross-modal semantics to improve the accuracy o... | {
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2411.18115 | Spectral-Spatial Transformer with Active Transfer Learning for
Hyperspectral Image Classification | [
"cs.CV"
] | The classification of hyperspectral images (HSI) is a challenging task due to the high spectral dimensionality and limited labeled data typically available for training. In this study, we propose a novel multi-stage active transfer learning (ATL) framework that integrates a Spatial-Spectral Transformer (SST) with an ac... | {
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2411.18121 | The Bigger the Better? Accurate Molecular Potential Energy Surfaces from
Minimalist Neural Networks | [
"physics.chem-ph",
"cs.LG"
] | Atomistic simulations are a powerful tool for studying the dynamics of molecules, proteins, and materials on wide time and length scales. Their reliability and predictiveness, however, depend directly on the accuracy of the underlying potential energy surface (PES). Guided by the principle of parsimony this work introd... | {
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2411.18122 | Using Machine Bias To Measure Human Bias | [
"cs.LG"
] | Biased human decisions have consequential impacts across various domains, yielding unfair treatment of individuals and resulting in suboptimal outcomes for organizations and society. In recognition of this fact, organizations regularly design and deploy interventions aimed at mitigating these biases. However, measuring... | {
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2411.18123 | Adaptive Cell Range Expansion in Multi-Band UAV Communication Networks | [
"cs.IT",
"eess.SP",
"math.IT"
] | This paper leverages stochastic geometry to model, analyze, and optimize multi-band unmanned aerial vehicle (UAV) communication networks operating across low-frequency and millimeter-wave (mmWave) bands. We introduce a novel approach to modeling mmWave antenna gain in such networks, which allows us to better capture an... | {
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2411.18124 | Influence of Critical Current Distribution on Operation, Quench
Detection and Protection of HTS Pancake Coils | [
"physics.acc-ph",
"cs.CE"
] | High-temperature superconductor (HTS) coated conductors (CC) are often wound into pancake coils with electrical insulation in-between the turns. The copper terminals are used for current injection and conduction cooling. An inherent variation of the critical current along the CC length results from its manufacturing pr... | {
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2411.18126 | Curriculum Demonstration Selection for In-Context Learning | [
"cs.CL"
] | Large Language Models (LLMs) have shown strong in-context learning (ICL) abilities with a few demonstrations. However, one critical challenge is how to select demonstrations to elicit the full potential of LLMs. In this paper, we propose Curriculum Demonstration Selection (CDS), a novel demonstration selection method f... | {
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2411.18133 | Towards Cross-device and Training-free Robotic Grasping in 3D Open World | [
"cs.RO",
"cs.CV"
] | Robotic grasping in the open world is a critical component of manufacturing and automation processes. While numerous existing approaches depend on 2D segmentation output to facilitate the grasping procedure, accurately determining depth from 2D imagery remains a challenge, often leading to limited performance in comple... | {
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2411.18135 | ModeDreamer: Mode Guiding Score Distillation for Text-to-3D Generation
using Reference Image Prompts | [
"cs.CV"
] | Existing Score Distillation Sampling (SDS)-based methods have driven significant progress in text-to-3D generation. However, 3D models produced by SDS-based methods tend to exhibit over-smoothing and low-quality outputs. These issues arise from the mode-seeking behavior of current methods, where the scores used to upda... | {
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2411.18138 | SALMONN-omni: A Codec-free LLM for Full-duplex Speech Understanding and
Generation | [
"eess.AS",
"cs.AI",
"cs.CL",
"cs.SD"
] | Full-duplex multimodal large language models (LLMs) provide a unified framework for addressing diverse speech understanding and generation tasks, enabling more natural and seamless human-machine conversations. Unlike traditional modularised conversational AI systems, which separate speech recognition, understanding, an... | {
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2411.18141 | Predicting Water Quality using Quantum Machine Learning: The Case of the
Umgeni Catchment (U20A) Study Region | [
"quant-ph",
"cs.AI",
"cs.LG"
] | In this study, we consider a real-world application of QML techniques to study water quality in the U20A region in Durban, South Africa. Specifically, we applied the quantum support vector classifier (QSVC) and quantum neural network (QNN), and we showed that the QSVC is easier to implement and yields a higher accuracy... | {
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2411.18142 | Enhancing Visual Reasoning with Autonomous Imagination in Multimodal
Large Language Models | [
"cs.CV"
] | There have been recent efforts to extend the Chain-of-Thought (CoT) paradigm to Multimodal Large Language Models (MLLMs) by finding visual clues in the input scene, advancing the visual reasoning ability of MLLMs. However, current approaches are specially designed for the tasks where clue finding plays a major role in ... | {
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2411.18145 | COREval: A Comprehensive and Objective Benchmark for Evaluating the
Remote Sensing Capabilities of Large Vision-Language Models | [
"cs.CV"
] | With the rapid development of Large Vision-Language Models (VLMs), both general-domain models and those specifically tailored for remote sensing Earth observation, have demonstrated exceptional perception and reasoning abilities within this specific field. However, the current absence of a comprehensive benchmark for h... | {
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2411.18147 | Online Knowledge Integration for 3D Semantic Mapping: A Survey | [
"cs.RO",
"cs.CV",
"cs.LG"
] | Semantic mapping is a key component of robots operating in and interacting with objects in structured environments. Traditionally, geometric and knowledge representations within a semantic map have only been loosely integrated. However, recent advances in deep learning now allow full integration of prior knowledge, rep... | {
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2411.18148 | A Runtime-Adaptive Transformer Neural Network Accelerator on FPGAs | [
"cs.AR",
"cs.LG",
"cs.SY",
"eess.SY"
] | Transformer neural networks (TNN) excel in natural language processing (NLP), machine translation, and computer vision (CV) without relying on recurrent or convolutional layers. However, they have high computational and memory demands, particularly on resource-constrained devices like FPGAs. Moreover, transformer model... | {
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2411.18150 | A Cost-Effective Approach to Smooth A* Path Planning for Autonomous
Vehicles | [
"cs.RO",
"cs.SY",
"eess.SY"
] | Path planning for wheeled mobile robots is a critical component in the field of automation and intelligent transportation systems. Car-like vehicles, which have non-holonomic constraints on their movement capability impose additional requirements on the planned paths. Traditional path planning algorithms, such as A* , ... | {
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2411.18152 | MSA-ASR: Efficient Multilingual Speaker Attribution with frozen ASR
Models | [
"cs.CL",
"cs.SD",
"eess.AS"
] | Speaker-attributed automatic speech recognition (SA-ASR) aims to transcribe speech while assigning transcripts to the corresponding speakers accurately. Existing methods often rely on complex modular systems or require extensive fine-tuning of joint modules, limiting their adaptability and general efficiency. This pape... | {
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2411.18157 | A survey on cutting-edge relation extraction techniques based on
language models | [
"cs.CL",
"cs.AI"
] | This comprehensive survey delves into the latest advancements in Relation Extraction (RE), a pivotal task in natural language processing essential for applications across biomedical, financial, and legal sectors. This study highlights the evolution and current state of RE techniques by analyzing 137 papers presented at... | {
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2411.18158 | Abductive Symbolic Solver on Abstraction and Reasoning Corpus | [
"cs.AI"
] | This paper addresses the challenge of enhancing artificial intelligence reasoning capabilities, focusing on logicality within the Abstraction and Reasoning Corpus (ARC). Humans solve such visual reasoning tasks based on their observations and hypotheses, and they can explain their solutions with a proper reason. Howeve... | {
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2411.18159 | Type-R: Automatically Retouching Typos for Text-to-Image Generation | [
"cs.CV"
] | While recent text-to-image models can generate photorealistic images from text prompts that reflect detailed instructions, they still face significant challenges in accurately rendering words in the image. In this paper, we propose to retouch erroneous text renderings in the post-processing pipeline. Our approach, call... | {
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2411.18161 | The Rn-index: a more accurate variant of the Rk-index | [
"cs.DL",
"cs.IR"
] | The contribution to pushing the boundaries of knowledge is a critical metric for evaluating the research performance of countries and institutions, which in many cases is not revealed by common bibliometric indicators. The Rk-index was specifically designed to assess such contributions, and the Rn-index is a variant th... | {
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2411.18162 | SentiXRL: An advanced large language Model Framework for Multilingual
Fine-Grained Emotion Classification in Complex Text Environment | [
"cs.CL"
] | With strong expressive capabilities in Large Language Models(LLMs), generative models effectively capture sentiment structures and deep semantics, however, challenges remain in fine-grained sentiment classification across multi-lingual and complex contexts. To address this, we propose the Sentiment Cross-Lingual Recogn... | {
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2411.18164 | RPEE-HEADS: A Novel Benchmark for Pedestrian Head Detection in Crowd
Videos | [
"cs.CV",
"cs.LG"
] | The automatic detection of pedestrian heads in crowded environments is essential for crowd analysis and management tasks, particularly in high-risk settings such as railway platforms and event entrances. These environments, characterized by dense crowds and dynamic movements, are underrepresented in public datasets, po... | {
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2411.18165 | KAN See Your Face | [
"cs.CV"
] | With the advancement of face reconstruction (FR) systems, privacy-preserving face recognition (PPFR) has gained popularity for its secure face recognition, enhanced facial privacy protection, and robustness to various attacks. Besides, specific models and algorithms are proposed for face embedding protection by mapping... | {
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2411.18166 | Combined Learning of Linear Parameter-Varying Models and Robust Control
Invariant Sets | [
"eess.SY",
"cs.SY"
] | Dynamical models identified from data are frequently employed in control system design. However, decoupling system identification from controller synthesis can result in situations where no suitable controller exists after a model has been identified. In this work, we introduce a novel control-oriented regularization i... | {
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2411.18169 | PDZSeg: Adapting the Foundation Model for Dissection Zone Segmentation
with Visual Prompts in Robot-assisted Endoscopic Submucosal Dissection | [
"cs.CV",
"cs.AI"
] | Purpose: Endoscopic surgical environments present challenges for dissection zone segmentation due to unclear boundaries between tissue types, leading to segmentation errors where models misidentify or overlook edges. This study aims to provide precise dissection zone suggestions during endoscopic submucosal dissection ... | {
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2411.18172 | Enhancing Computer Vision with Knowledge: a Rummikub Case Study | [
"cs.CV",
"cs.LO"
] | Artificial Neural Networks excel at identifying individual components in an image. However, out-of-the-box, they do not manage to correctly integrate and interpret these components as a whole. One way to alleviate this weakness is to expand the network with explicit knowledge and a separate reasoning component. In this... | {
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2411.18174 | ORB-SLAM3AB: Augmenting ORB-SLAM3 to Counteract Bumps with Optical Flow
Inter-frame Matching | [
"cs.RO"
] | This paper proposes an enhancement to the ORB-SLAM3 algorithm, tailored for applications on rugged road surfaces. Our improved algorithm adeptly combines feature point matching with optical flow methods, capitalizing on the high robustness of optical flow in complex terrains and the high precision of feature points on ... | {
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2411.18177 | Machine Unlearning reveals that the Gender-based Violence Victim
Condition can be detected from Speech in a Speaker-Agnostic Setting | [
"cs.LG"
] | This study addresses the critical issue of gender-based violence's (GBV) impact on women's mental health. GBV, encompassing physical and sexual aggression, often results in long-lasting adverse effects for the victims, including anxiety, depression, post-traumatic stress disorder (PTSD), and substance abuse. Artificial... | {
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2411.18179 | Prediction with Action: Visual Policy Learning via Joint Denoising
Process | [
"cs.RO",
"cs.AI"
] | Diffusion models have demonstrated remarkable capabilities in image generation tasks, including image editing and video creation, representing a good understanding of the physical world. On the other line, diffusion models have also shown promise in robotic control tasks by denoising actions, known as diffusion policy.... | {
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2411.18180 | DistinctAD: Distinctive Audio Description Generation in Contexts | [
"cs.CV"
] | Audio Descriptions (ADs) aim to provide a narration of a movie in text form, describing non-dialogue-related narratives, such as characters, actions, or scene establishment. Automatic generation of ADs remains challenging due to: i) the domain gap between movie-AD data and existing data used to train vision-language mo... | {
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2411.18183 | Equi join query acceleration using algebraic signatures (Published at
IADIS'2008 Applied Computing conf.) | [
"cs.DB"
] | Evaluation of join queries is very challenging since they have to deal with an increasing data size. We study the relational join query processing realized by hash tables and we focus on the case of equi join queries. We propose to use a new form of signatures, the algebraic signatures, for fast comparison between valu... | {
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2411.18189 | Towards Lensless Image Deblurring with Prior-Embedded Implicit Neural
Representations in the Low-Data Regime | [
"eess.IV",
"cs.CV"
] | The field of computational imaging has witnessed a promising paradigm shift with the emergence of untrained neural networks, offering novel solutions to inverse computational imaging problems. While existing techniques have demonstrated impressive results, they often operate either in the high-data regime, leveraging G... | {
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2411.18195 | Scalable Multi-Objective Reinforcement Learning with Fairness Guarantees
using Lorenz Dominance | [
"cs.LG"
] | Multi-Objective Reinforcement Learning (MORL) aims to learn a set of policies that optimize trade-offs between multiple, often conflicting objectives. MORL is computationally more complex than single-objective RL, particularly as the number of objectives increases. Additionally, when objectives involve the preferences ... | {
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2411.18197 | Make-It-Animatable: An Efficient Framework for Authoring Animation-Ready
3D Characters | [
"cs.GR",
"cs.CV"
] | 3D characters are essential to modern creative industries, but making them animatable often demands extensive manual work in tasks like rigging and skinning. Existing automatic rigging tools face several limitations, including the necessity for manual annotations, rigid skeleton topologies, and limited generalization a... | {
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2411.18199 | Semantic Edge Computing and Semantic Communications in 6G Networks: A
Unifying Survey and Research Challenges | [
"cs.LG",
"cs.NI",
"eess.SP"
] | Semantic Edge Computing (SEC) and Semantic Communications (SemComs) have been proposed as viable approaches to achieve real-time edge-enabled intelligence in sixth-generation (6G) wireless networks. On one hand, SemCom leverages the strength of Deep Neural Networks (DNNs) to encode and communicate the semantic informat... | {
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2411.18201 | Learning for Long-Horizon Planning via Neuro-Symbolic Abductive
Imitation | [
"cs.LG",
"cs.AI"
] | Recent learning-to-imitation methods have shown promising results in planning via imitating within the observation-action space. However, their ability in open environments remains constrained, particularly in long-horizon tasks. In contrast, traditional symbolic planning excels in long-horizon tasks through logical re... | {
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2411.18203 | Critic-V: VLM Critics Help Catch VLM Errors in Multimodal Reasoning | [
"cs.CV",
"cs.CL"
] | Vision-language models (VLMs) have shown remarkable advancements in multimodal reasoning tasks. However, they still often generate inaccurate or irrelevant responses due to issues like hallucinated image understandings or unrefined reasoning paths. To address these challenges, we introduce Critic-V, a novel framework i... | {
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2411.18207 | From Open Vocabulary to Open World: Teaching Vision Language Models to
Detect Novel Objects | [
"cs.CV",
"cs.AI"
] | Traditional object detection methods operate under the closed-set assumption, where models can only detect a fixed number of objects predefined in the training set. Recent works on open vocabulary object detection (OVD) enable the detection of objects defined by an unbounded vocabulary, which reduces the cost of traini... | {
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2411.18211 | TimeMarker: A Versatile Video-LLM for Long and Short Video Understanding
with Superior Temporal Localization Ability | [
"cs.CV",
"cs.AI"
] | Rapid development of large language models (LLMs) has significantly advanced multimodal large language models (LMMs), particularly in vision-language tasks. However, existing video-language models often overlook precise temporal localization and struggle with videos of varying lengths. We introduce TimeMarker, a versat... | {
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2411.18212 | SCoTT: Wireless-Aware Path Planning with Vision Language Models and
Strategic Chains-of-Thought | [
"cs.LG",
"cs.AI",
"cs.RO",
"cs.SY",
"eess.SY"
] | Path planning is a complex problem for many practical applications, particularly in robotics. Existing algorithms, however, are exhaustive in nature and become increasingly complex when additional side constraints are incorporated alongside distance minimization. In this paper, a novel approach using vision language mo... | {
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2411.18216 | Evaluating and Improving the Robustness of Security Attack Detectors
Generated by LLMs | [
"cs.SE",
"cs.CR",
"cs.LG"
] | Large Language Models (LLMs) are increasingly used in software development to generate functions, such as attack detectors, that implement security requirements. However, LLMs struggle to generate accurate code, resulting, e.g., in attack detectors that miss well-known attacks when used in practice. This is most likely... | {
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2411.18217 | How to Learn a New Language? An Efficient Solution for Self-Supervised
Learning Models Unseen Languages Adaption in Low-Resource Scenario | [
"cs.SD",
"cs.CL",
"eess.AS"
] | The utilization of speech Self-Supervised Learning (SSL) models achieves impressive performance on Automatic Speech Recognition (ASR). However, in low-resource language ASR, they encounter the domain mismatch problem between pre-trained and low-resource languages. Typical solutions like fine-tuning the SSL model suffer... | {
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2411.18220 | R-MTLLMF: Resilient Multi-Task Large Language Model Fusion at the
Wireless Edge | [
"eess.SP",
"cs.AI",
"cs.LG"
] | Multi-task large language models (MTLLMs) are important for many applications at the wireless edge, where users demand specialized models to handle multiple tasks efficiently. However, training MTLLMs is complex and exhaustive, particularly when tasks are subject to change. Recently, the concept of model fusion via tas... | {
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2411.18224 | KANs for Computer Vision: An Experimental Study | [
"cs.CV"
] | This paper presents an experimental study of Kolmogorov-Arnold Networks (KANs) applied to computer vision tasks, particularly image classification. KANs introduce learnable activation functions on edges, offering flexible non-linear transformations compared to traditional pre-fixed activation functions with specific ne... | {
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2411.18225 | PATHS: A Hierarchical Transformer for Efficient Whole Slide Image
Analysis | [
"cs.CV",
"cs.AI"
] | Computational analysis of whole slide images (WSIs) has seen significant research progress in recent years, with applications ranging across important diagnostic and prognostic tasks such as survival or cancer subtype prediction. Many state-of-the-art models process the entire slide - which may be as large as $150,000 ... | {
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2411.18226 | Feature-Factory: Automating Software Feature Integration Using
Generative AI | [
"cs.SE",
"cs.AI",
"cs.LG",
"cs.MA"
] | Integrating new features into existing software projects can be a complex and time-consuming process. Feature-Factory leverages Generative AI with WatsonX.ai to automate the analysis, planning, and implementation of feature requests. By combining advanced project parsing, dependency resolution, and AI-generated code, t... | {
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2411.18229 | SharpDepth: Sharpening Metric Depth Predictions Using Diffusion
Distillation | [
"cs.CV"
] | We propose SharpDepth, a novel approach to monocular metric depth estimation that combines the metric accuracy of discriminative depth estimation methods (e.g., Metric3D, UniDepth) with the fine-grained boundary sharpness typically achieved by generative methods (e.g., Marigold, Lotus). Traditional discriminative model... | {
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2411.18230 | Dependency-Aware CAV Task Scheduling via Diffusion-Based Reinforcement
Learning | [
"cs.AI",
"cs.RO"
] | In this paper, we propose a novel dependency-aware task scheduling strategy for dynamic unmanned aerial vehicle-assisted connected autonomous vehicles (CAVs). Specifically, different computation tasks of CAVs consisting of multiple dependency subtasks are judiciously assigned to nearby CAVs or the base station for prom... | {
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2411.18231 | Machine learning-based classification for Single Photon Space Debris
Light Curves | [
"astro-ph.IM",
"cs.LG"
] | The growing number of man-made debris in Earth's orbit poses a threat to active satellite missions due to the risk of collision. Characterizing unknown debris is, therefore, of high interest. Light Curves (LCs) are temporal variations of object brightness and have been shown to contain information such as shape, attitu... | {
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2411.18234 | Randomized-Grid Search for Hyperparameter Tuning in Decision Tree Model
to Improve Performance of Cardiovascular Disease Classification | [
"cs.LG",
"cs.AI",
"cs.PF",
"stat.CO"
] | Cardiovascular disease refers to any critical condition that impacts the heart. Because heart diseases can be life-threatening. Researchers are focusing on designing smart systems to accurately diagnose them based on electronic health data, with the aid of machine learning algorithms. Heart disease classification using... | {
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2411.18235 | Certified Training with Branch-and-Bound: A Case Study on
Lyapunov-stable Neural Control | [
"cs.LG",
"cs.AI",
"cs.RO",
"cs.SY",
"eess.SY"
] | We study the problem of learning Lyapunov-stable neural controllers which provably satisfy the Lyapunov asymptotic stability condition within a region-of-attraction. Compared to previous works which commonly used counterexample guided training on this task, we develop a new and generally formulated certified training f... | {
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2411.18241 | Exploration of LLM Multi-Agent Application Implementation Based on
LangGraph+CrewAI | [
"cs.MA",
"cs.AI"
] | With the rapid development of large model technology, the application of agent technology in various fields is becoming increasingly widespread, profoundly changing people's work and lifestyles. In complex and dynamic systems, multi-agents achieve complex tasks that are difficult for a single agent to complete through ... | {
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2411.18242 | Thai Financial Domain Adaptation of THaLLE -- Technical Report | [
"cs.CL",
"cs.AI"
] | Large Language Models (LLMs) excel in general tasks but struggle with domain-specific challenges, such as specialized terminology and localized regulations. Existing financial LLMs, like FinGPT and BloombergGPT, lack support for the Thai financial domain. We developed a Thai Financial LLM using the Investment Consultan... | {
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2411.18247 | A gentle push funziona benissimo: making instructed models in Italian
via contrastive activation steering | [
"cs.CL",
"cs.LG"
] | Adapting models to a language that was only partially present in the pre-training data requires fine-tuning, which is expensive in terms of both data and computational resources. As an alternative to fine-tuning, we explore the potential of activation steering-based techniques to enhance model performance on Italian ta... | {
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2411.18249 | Deep End-to-end Adaptive k-Space Sampling, Reconstruction, and
Registration for Dynamic MRI | [
"eess.IV",
"cs.CV",
"physics.med-ph"
] | Dynamic MRI enables a range of clinical applications, including cardiac function assessment, organ motion tracking, and radiotherapy guidance. However, fully sampling the dynamic k-space data is often infeasible due to time constraints and physiological motion such as respiratory and cardiac motion. This necessitates u... | {
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} |
2411.18250 | IKUN: Initialization to Keep snn training and generalization great with
sUrrogate-stable variaNce | [
"cs.LG",
"cs.AI"
] | Weight initialization significantly impacts the convergence and performance of neural networks. While traditional methods like Xavier and Kaiming initialization are widely used, they often fall short for spiking neural networks (SNNs), which have distinct requirements compared to artificial neural networks (ANNs). To... | {
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} |
2411.18252 | Target Tracking: Statistics of Successive Successful Target Detection in
Automotive Radar Networks | [
"cs.IT",
"math.IT"
] | We introduce a novel metric for stochastic geometry based analysis of automotive radar networks called target {\it tracking probability}. Unlike the well-investigated detection probability (often termed as the success or coverage probability in stochastic geometry), the tracking probability characterizes the event of s... | {
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} |
2411.18253 | Multimodal Integration of Longitudinal Noninvasive Diagnostics for
Survival Prediction in Immunotherapy Using Deep Learning | [
"cs.LG",
"cs.AI",
"q-bio.QM"
] | Purpose: Analyzing noninvasive longitudinal and multimodal data using artificial intelligence could potentially transform immunotherapy for cancer patients, paving the way towards precision medicine. Methods: In this study, we integrated pre- and on-treatment blood measurements, prescribed medications and CT-based volu... | {
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} |
2411.18254 | Active partitioning: inverting the paradigm of active learning | [
"cs.LG"
] | Datasets often incorporate various functional patterns related to different aspects or regimes, which are typically not equally present throughout the dataset. We propose a novel, general-purpose partitioning algorithm that utilizes competition between models to detect and separate these functional patterns. This compe... | {
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} |
2411.18259 | Transfer Learning for Deep Learning-based Prediction of Lattice Thermal
Conductivity | [
"cs.LG",
"physics.comp-ph"
] | Machine learning promises to accelerate the material discovery by enabling high-throughput prediction of desirable macro-properties from atomic-level descriptors or structures. However, the limited data available about precise values of these properties have been a barrier, leading to predictive models with limited pre... | {
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} |
2411.18260 | MetaphorShare: A Dynamic Collaborative Repository of Open Metaphor
Datasets | [
"cs.CL"
] | The metaphor studies community has developed numerous valuable labelled corpora in various languages over the years. Many of these resources are not only unknown to the NLP community, but are also often not easily shared among the researchers. Both in human sciences and in NLP, researchers could benefit from a centrali... | {
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} |
2411.18261 | Dynamic Retail Pricing via Q-Learning -- A Reinforcement Learning
Framework for Enhanced Revenue Management | [
"cs.LG"
] | This paper explores the application of a reinforcement learning (RL) framework using the Q-Learning algorithm to enhance dynamic pricing strategies in the retail sector. Unlike traditional pricing methods, which often rely on static demand models, our RL approach continuously adapts to evolving market dynamics, offerin... | {
"Other": 0,
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} |
2411.18262 | Break the ID-Language Barrier: An Adaption Framework for Sequential
Recommendation | [
"cs.IR",
"cs.LG"
] | The recent breakthrough of large language models (LLMs) in natural language processing has sparked exploration in recommendation systems, however, their limited domain-specific knowledge remains a critical bottleneck. Specifically, LLMs lack key pieces of information crucial for sequential recommendations, such as user... | {
"Other": 0,
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} |
2411.18263 | TSD-SR: One-Step Diffusion with Target Score Distillation for Real-World
Image Super-Resolution | [
"cs.CV"
] | Pre-trained text-to-image diffusion models are increasingly applied to real-world image super-resolution (Real-ISR) task. Given the iterative refinement nature of diffusion models, most existing approaches are computationally expensive. While methods such as SinSR and OSEDiff have emerged to condense inference steps vi... | {
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} |
2411.18266 | Wearable intelligent throat enables natural speech in stroke patients
with dysarthria | [
"eess.AS",
"cs.AI",
"cs.SD",
"cs.SY",
"eess.SY"
] | Wearable silent speech systems hold significant potential for restoring communication in patients with speech impairments. However, seamless, coherent speech remains elusive, and clinical efficacy is still unproven. Here, we present an AI-driven intelligent throat (IT) system that integrates throat muscle vibrations an... | {
"Other": 0,
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"cs.SY": 1
} |
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