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272911435 | 2409.17991 | 2024-09-26 | Dimension-independent learning rates for high-dimensional classification problems | We study the problem of approximating and estimating classification functions that have their decision boundary in the $RBV^2$ space. Functions of $RBV^2$ type arise naturally as solutions of regularized neural network learning problems and neural networks can approximate these functions without the curse of dimensiona... | [
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272910976 | 2409.17481 | 2024-09-26 | MaskLLM: Learnable Semi-Structured Sparsity for Large Language Models | Large Language Models (LLMs) are distinguished by their massive parameter counts, which typically result in significant redundancy. This work introduces MaskLLM, a learnable pruning method that establishes Semi-structured (or ``N:M'') Sparsity in LLMs, aimed at reducing computational overhead during inference. Instead ... | [
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272911309 | 2409.17840 | 2024-09-26 | Detecting and Measuring Confounding Using Causal Mechanism Shifts | Detecting and measuring confounding effects from data is a key challenge in causal inference. Existing methods frequently assume causal sufficiency, disregarding the presence of unobserved confounding variables. Causal sufficiency is both unrealistic and empirically untestable. Additionally, existing methods make stron... | [
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277564430 | 2409.17546 | 2024-09-26 | MASSFormer: Mobility-Aware Spectrum Sensing using Transformer-Driven Tiered Structure | In this paper, we develop a novel mobility-aware transformer-driven tiered structure (MASSFormer) based cooperative spectrum sensing method that effectively models the spatio-temporal dynamics of user movements. Unlike existing methods, our method considers a dynamic scenario involving mobile primary users (PUs) and se... | [
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272910601 | 2409.17656 | 2024-09-26 | Prototype based Masked Audio Model for Self-Supervised Learning of Sound Event Detection | A significant challenge in sound event detection (SED) is the effective utilization of unlabeled data, given the limited availability of labeled data due to high annotation costs. Semi-supervised algorithms rely on labeled data to learn from unlabeled data, and the performance is constrained by the quality and size of ... | [
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272969418 | 2409.18170 | 2024-09-26 | Evaluation of Large Language Models for Summarization Tasks in the Medical Domain: A Narrative Review | Large Language Models have advanced clinical Natural Language Generation, creating opportunities to manage the volume of medical text. However, the high-stakes nature of medicine requires reliable evaluation, which remains a challenge. In this narrative review, we assess the current evaluation state for clinical summar... | [
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272987628 | 2409.19024 | 2024-09-26 | Elephant in the Room: Unveiling the Impact of Reward Model Quality in Alignment | The demand for regulating potentially risky behaviors of large language models (LLMs) has ignited research on alignment methods. Since LLM alignment heavily relies on reward models for optimization or evaluation, neglecting the quality of reward models may cause unreliable results or even misalignment. Despite the vita... | [
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272911362 | 2409.17601 | 2024-09-26 | CleanerCLIP: Fine-grained Counterfactual Semantic Augmentation for Backdoor Defense in Contrastive Learning | Pre-trained large models for multimodal contrastive learning, such as CLIP, have been widely recognized in the industry as highly susceptible to data-poisoned backdoor attacks. This poses significant risks to downstream model training. In response to such potential threats, finetuning offers a simpler and more efficien... | [
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272911329 | 2409.18042 | 2024-09-26 | EMOVA: Empowering Language Models to See, Hear and Speak with Vivid Emotions | GPT-4o, an omni-modal model that enables vocal conversations with diverse emotions and tones, marks a milestone for omni-modal foundation models. However, empowering Large Language Models to perceive and generate images, texts, and speeches end-to-end with publicly available data remains challenging for the open-source... | [
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272911117 | 2409.17791 | 2024-09-26 | Self-supervised Preference Optimization: Enhance Your Language Model with Preference Degree Awareness | Recently, there has been significant interest in replacing the reward model in Reinforcement Learning with Human Feedback (RLHF) methods for Large Language Models (LLMs), such as Direct Preference Optimization (DPO) and its variants. These approaches commonly use a binary cross-entropy mechanism on pairwise samples, i.... | [
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272910967 | 2409.17702 | 2024-09-26 | Episodic Memory Verbalization using Hierarchical Representations of Life-Long Robot Experience | Verbalization of robot experience, i.e., summarization of and question answering about a robot's past, is a crucial ability for improving human-robot interaction. Previous works applied rule-based systems or fine-tuned deep models to verbalize short (several-minute-long) streams of episodic data, limiting generalizatio... | [
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272910876 | 2409.17858 | 2024-09-26 | How Feature Learning Can Improve Neural Scaling Laws | We develop a solvable model of neural scaling laws beyond the kernel limit. Theoretical analysis of this model shows how performance scales with model size, training time, and the total amount of available data. We identify three scaling regimes corresponding to varying task difficulties: hard, easy, and super easy tas... | [
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272910805 | 2409.17588 | 2024-09-26 | DualCoTs: Dual Chain-of-Thoughts Prompting for Sentiment Lexicon Expansion of Idioms | Idioms represent a ubiquitous vehicle for conveying sentiments in the realm of everyday discourse, rendering the nuanced analysis of idiom sentiment crucial for a comprehensive understanding of emotional expression within real-world texts. Nevertheless, the existing corpora dedicated to idiom sentiment analysis conside... | [
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272910762 | 2409.17565 | 2024-09-26 | Pixel-Space Post-Training of Latent Diffusion Models | Latent diffusion models (LDMs) have made significant advancements in the field of image generation in recent years. One major advantage of LDMs is their ability to operate in a compressed latent space, allowing for more efficient training and deployment. However, despite these advantages, challenges with LDMs still rem... | [
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272910824 | 2409.17917 | 2024-09-26 | WaSt-3D: Wasserstein-2 Distance for Scene-to-Scene Stylization on 3D Gaussians | While style transfer techniques have been well-developed for 2D image stylization, the extension of these methods to 3D scenes remains relatively unexplored. Existing approaches demonstrate proficiency in transferring colors and textures but often struggle with replicating the geometry of the scenes. In our work, we le... | [
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272969458 | 2409.18222 | 2024-09-26 | Trustworthy AI: Securing Sensitive Data in Large Language Models | Large Language Models (LLMs) have transformed natural language processing (NLP) by enabling robust text generation and understanding. However, their deployment in sensitive domains like healthcare, finance, and legal services raises critical concerns about privacy and data security. This paper proposes a comprehensive ... | [
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272911283 | 2409.17550 | 2024-09-26 | A Simple but Strong Baseline for Sounding Video Generation: Effective Adaptation of Audio and Video Diffusion Models for Joint Generation | In this work, we build a simple but strong baseline for sounding video generation. Given base diffusion models for audio and video, we integrate them with additional modules into a single model and train it to make the model jointly generate audio and video. To enhance alignment between audio-video pairs, we introduce ... | [
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272911469 | 2409.18071 | 2024-09-26 | FreeEdit: Mask-free Reference-based Image Editing with Multi-modal Instruction | Introducing user-specified visual concepts in image editing is highly practical as these concepts convey the user's intent more precisely than text-based descriptions. We propose FreeEdit, a novel approach for achieving such reference-based image editing, which can accurately reproduce the visual concept from the refer... | [
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272911111 | 2409.18111 | 2024-09-26 | E.T. Bench: Towards Open-Ended Event-Level Video-Language Understanding | Recent advances in Video Large Language Models (Video-LLMs) have demonstrated their great potential in general-purpose video understanding. To verify the significance of these models, a number of benchmarks have been proposed to diagnose their capabilities in different scenarios. However, existing benchmarks merely eva... | [
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272910854 | 2409.17472 | 2024-09-26 | Autoregressive Multi-trait Essay Scoring via Reinforcement Learning with Scoring-aware Multiple Rewards | Recent advances in automated essay scoring (AES) have shifted towards evaluating multiple traits to provide enriched feedback. Like typical AES systems, multi-trait AES employs the quadratic weighted kappa (QWK) to measure agreement with human raters, aligning closely with the rating schema; however, its non-differenti... | [
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272911308 | 2409.17972 | 2024-09-26 | BEATS: Optimizing LLM Mathematical Capabilities with BackVerify and Adaptive Disambiguate based Efficient Tree Search | Large Language Models (LLMs) have exhibited exceptional performance across a broad range of tasks and domains. However, they still encounter difficulties in solving mathematical problems due to the rigorous and logical nature of mathematics. Previous studies have employed techniques such as supervised fine-tuning (SFT)... | [
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272910647 | 2409.17864 | 2024-09-26 | A Multimodal Single-Branch Embedding Network for Recommendation in Cold-Start and Missing Modality Scenarios | Most recommender systems adopt collaborative filtering (CF) and provide recommendations based on past collective interactions. Therefore, the performance of CF algorithms degrades when few or no interactions are available, a scenario referred to as cold-start. To address this issue, previous work relies on models lever... | [
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272969110 | 2409.18219 | 2024-09-26 | Packet Inspection Transformer: A Self-Supervised Journey to Unseen Malware Detection with Few Samples | As networks continue to expand and become more interconnected, the need for novel malware detection methods becomes more pronounced. Traditional security measures are increasingly inadequate against the sophistication of modern cyber attacks. Deep Packet Inspection (DPI) has been pivotal in enhancing network security, ... | [
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273350723 | 2410.10826 | 2024-09-26 | High-Fidelity 3D Lung CT Synthesis in ARDS Swine Models Using Score-Based 3D Residual Diffusion Models | Acute respiratory distress syndrome (ARDS) is a severe condition characterized by lung inflammation and respiratory failure, with a high mortality rate of approximately 40%. Traditional imaging methods, such as chest X-rays, provide only two-dimensional views, limiting their effectiveness in fully assessing lung pathol... | [
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272910776 | 2409.17487 | 2024-09-26 | Learning Quantized Adaptive Conditions for Diffusion Models | The curvature of ODE trajectories in diffusion models hinders their ability to generate high-quality images in a few number of function evaluations (NFE). In this paper, we propose a novel and effective approach to reduce trajectory curvature by utilizing adaptive conditions. By employing a extremely light-weight quant... | [
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272911358 | 2409.17589 | 2024-09-26 | Improving Fast Adversarial Training via Self-Knowledge Guidance | Adversarial training has achieved remarkable advancements in defending against adversarial attacks. Among them, fast adversarial training (FAT) is gaining attention for its ability to achieve competitive robustness with fewer computing resources. Existing FAT methods typically employ a uniform strategy that optimizes a... | [
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272968812 | 2409.18168 | 2024-09-26 | Jump Diffusion-Informed Neural Networks with Transfer Learning for Accurate American Option Pricing under Data Scarcity | Option pricing models, essential in financial mathematics and risk management, have been extensively studied and recently advanced by AI methodologies. However, American option pricing remains challenging due to the complexity of determining optimal exercise times and modeling non-linear payoffs resulting from stochast... | [
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280692237 | 2409.17682 | 2024-09-26 | Dark Miner: Defend against undesirable generation for text-to-image diffusion models | Text-to-image diffusion models have been demonstrated with undesired generation due to unfiltered large-scale training data, such as sexual images and copyrights, necessitating the erasure of undesired concepts. Most existing methods focus on modifying the generation probabilities conditioned on the texts containing ta... | [
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272910595 | 2409.18044 | 2024-09-26 | Unveiling the Role of Pretraining in Direct Speech Translation | Direct speech-to-text translation systems encounter an important drawback in data scarcity. A common solution consists on pretraining the encoder on automatic speech recognition, hence losing efficiency in the training process. In this study, we compare the training dynamics of a system using a pretrained encoder, the ... | [
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272910819 | 2409.17808 | 2024-09-26 | Generative Modeling of Molecular Dynamics Trajectories | Molecular dynamics (MD) is a powerful technique for studying microscopic phenomena, but its computational cost has driven significant interest in the development of deep learning-based surrogate models. We introduce generative modeling of molecular trajectories as a paradigm for learning flexible multi-task surrogate m... | [
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272911103 | 2409.17907 | 2024-09-26 | PhantomLiDAR: Cross-modality Signal Injection Attacks against LiDAR | LiDAR (Light Detection and Ranging) is a pivotal sensor for autonomous driving, offering precise 3D spatial information. Previous signal attacks against LiDAR systems mainly exploit laser signals. In this paper, we investigate the possibility of cross-modality signal injection attacks, i.e., injecting intentional elect... | [
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272911094 | 2409.17674 | 2024-09-26 | Self-Supervised Learning of Deviation in Latent Representation for Co-speech Gesture Video Generation | Gestures are pivotal in enhancing co-speech communication. While recent works have mostly focused on point-level motion transformation or fully supervised motion representations through data-driven approaches, we explore the representation of gestures in co-speech, with a focus on self-supervised representation and pix... | [
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272910829 | 2409.17649 | 2024-09-26 | Provable Performance Guarantees of Copy Detection Patterns | Copy Detection Patterns (CDPs) are crucial elements in modern security applications, playing a vital role in safeguarding industries such as food, pharmaceuticals, and cosmetics. Current performance evaluations of CDPs predominantly rely on empirical setups using simplistic metrics like Hamming distances or Pearson cor... | [
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272968774 | 2409.18333 | 2024-09-26 | A Framework for Standardizing Similarity Measures in a Rapidly Evolving Field | Similarity measures are fundamental tools for quantifying the alignment between artificial and biological systems. However, the diversity of similarity measures and their varied naming and implementation conventions makes it challenging to compare across studies. To facilitate comparisons and make explicit the implemen... | [
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272911257 | 2409.17889 | 2024-09-26 | A multi-source data power load forecasting method using attention mechanism-based parallel cnn-gru | Accurate power load forecasting is crucial for improving energy efficiency and ensuring power supply quality. Considering the power load forecasting problem involves not only dynamic factors like historical load variations but also static factors such as climate conditions that remain constant over specific periods. Fr... | [
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272910764 | 2409.17711 | 2024-09-26 | Efficient Pointwise-Pairwise Learning-to-Rank for News Recommendation | News recommendation is a challenging task that involves personalization based on the interaction history and preferences of each user. Recent works have leveraged the power of pretrained language models (PLMs) to directly rank news items by using inference approaches that predominately fall into three categories: point... | [
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272911049 | 2409.17526 | 2024-09-26 | Drone Stereo Vision for Radiata Pine Branch Detection and Distance Measurement: Integrating SGBM and Segmentation Models | Manual pruning of radiata pine trees presents significant safety risks due to their substantial height and the challenging terrains in which they thrive. To address these risks, this research proposes the development of a drone-based pruning system equipped with specialized pruning tools and a stereo vision camera, ena... | [
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