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272826910 | 2409.14381 | 2024-09-22 | Investigating Layer Importance in Large Language Models | Large language models (LLMs) have gained increasing attention due to their prominent ability to understand and process texts. Nevertheless, LLMs largely remain opaque. The lack of understanding of LLMs has obstructed the deployment in safety-critical scenarios and hindered the development of better models. In this stud... | [
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272827631 | 2409.14365 | 2024-09-22 | D3RoMa: Disparity Diffusion-based Depth Sensing for Material-Agnostic Robotic Manipulation | Depth sensing is an important problem for 3D vision-based robotics. Yet, a real-world active stereo or ToF depth camera often produces noisy and incomplete depth which bottlenecks robot performances. In this work, we propose D3RoMa, a learning-based depth estimation framework on stereo image pairs that predicts clean a... | [
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272826676 | 2409.14302 | 2024-09-22 | Reliable and diverse evaluation of LLM medical knowledge mastery | Mastering medical knowledge is crucial for medical-specific LLMs. However, despite the existence of medical benchmarks like MedQA, a unified framework that fully leverages existing knowledge bases to evaluate LLMs' mastery of medical knowledge is still lacking. In the study, we propose a novel framework PretexEval that... | [
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271915484 | 2410.02811 | 2024-09-22 | SAC-KG: Exploiting Large Language Models as Skilled Automatic Constructors for Domain Knowledge Graphs | Knowledge graphs (KGs) play a pivotal role in knowledge-intensive tasks across specialized domains, where the acquisition of precise and dependable knowledge is crucial. However, existing KG construction methods heavily rely on human intervention to attain qualified KGs, which severely hinders the practical applicabili... | [
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272827936 | 2409.14679 | 2024-09-22 | Quantifying Context Bias in Domain Adaptation for Object Detection | Domain adaptation for object detection (DAOD) has become essential to counter performance degradation caused by distribution shifts between training and deployment domains. However, a critical factor influencing DAOD - context bias resulting from learned foreground-background (FG-BG) associations - has remained underex... | [
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272880639 | 2409.16322 | 2024-09-22 | On the Within-class Variation Issue in Alzheimer's Disease Detection | Alzheimer's Disease (AD) detection employs machine learning classification models to distinguish between individuals with AD and those without. Different from conventional classification tasks, we identify within-class variation as a critical challenge in AD detection: individuals with AD exhibit a spectrum of cognitiv... | [
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272827079 | 2409.14280 | 2024-09-22 | Accelerated Stochastic ExtraGradient: Mixing Hessian and Gradient Similarity to Reduce Communication in Distributed and Federated Learning | Modern realities and trends in learning require more and more generalization ability of models, which leads to an increase in both models and training sample size. It is already difficult to solve such tasks in a single device mode. This is the reason why distributed and federated learning approaches are becoming more ... | [
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272827593 | 2409.14436 | 2024-09-22 | Automotive innovation landscaping using LLM | The process of landscaping automotive innovation through patent analysis is crucial for Research and Development teams. It aids in comprehending innovation trends, technological advancements, and the latest technologies from competitors. Traditionally, this process required intensive manual efforts. However, with the a... | [
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272827074 | 2409.14393 | 2024-09-22 | MaskedMimic: Unified Physics-Based Character Control Through Masked Motion Inpainting | Crafting a single, versatile physics-based controller that can breathe life into interactive characters across a wide spectrum of scenarios represents an exciting frontier in character animation. An ideal controller should support diverse control modalities, such as sparse target keyframes, text instructions, and scene... | [
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272826964 | 2409.14418 | 2024-09-22 | Delay Minimization for Movable Antennas-Enabled Anti-Jamming Communications With Mobile Edge Computing | In future 6G networks, anti-jamming will become a critical challenge, particularly with the development of intelligent jammers that can initiate malicious interference, posing a significant security threat to communication transmission. Additionally, 6G networks have introduced mobile edge computing (MEC) technology to... | [
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272827734 | 2409.14459 | 2024-09-22 | Exploring Multilingual Probing in Large Language Models: A Cross-Language Analysis | Probing techniques for large language models (LLMs) have primarily focused on English, overlooking the vast majority of the world's languages. In this paper, we extend these probing methods to a multilingual context, investigating the behaviors of LLMs across diverse languages. We conduct experiments on several open-so... | [
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272828167 | 2409.14444 | 2024-09-22 | Fake It till You Make It: Curricular Dynamic Forgery Augmentations towards General Deepfake Detection | Previous studies in deepfake detection have shown promising results when testing face forgeries from the same dataset as the training. However, the problem remains challenging when one tries to generalize the detector to forgeries from unseen datasets and created by unseen methods. In this work, we present a novel gene... | [
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272827080 | 2409.14736 | 2024-09-23 | Safe Navigation of Bipedal Robots via Koopman Operator-Based Model Predictive Control | Nonlinearity in dynamics has long been a major challenge in robotics, often causing significant performance degradation in existing control algorithms. For example, the navigation of bipedal robots can exhibit nonlinear behaviors even under simple velocity commands, as their actual dynamics are governed by complex whol... | [
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272910560 | 2409.17179 | 2024-09-23 | Fully automatic extraction of morphological traits from the Web: utopia or reality? | Plant morphological traits, their observable characteristics, are fundamental to understand the role played by each species within their ecosystem. However, compiling trait information for even a moderate number of species is a demanding task that may take experts years to accomplish. At the same time, massive amounts ... | [
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272827783 | 2409.14781 | 2024-09-23 | Pretraining Data Detection for Large Language Models: A Divergence-based Calibration Method | As the scale of training corpora for large language models (LLMs) grows, model developers become increasingly reluctant to disclose details on their data. This lack of transparency poses challenges to scientific evaluation and ethical deployment. Recently, pretraining data detection approaches, which infer whether a gi... | [
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272832307 | 2409.15518 | 2024-09-23 | Eagle: Efficient Training-Free Router for Multi-LLM Inference | The proliferation of Large Language Models (LLMs) with varying capabilities and costs has created a need for efficient model selection in AI systems. LLM routers address this need by dynamically choosing the most suitable model for a given query based on task requirements and budget constraints. However, existing route... | [
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272880864 | 2409.16327 | 2024-09-23 | GATher: Graph Attention Based Predictions of Gene-Disease Links | Target selection is crucial in pharmaceutical drug discovery, directly influencing clinical trial success. Despite its importance, drug development remains resource-intensive, often taking over a decade with significant financial costs. High failure rates highlight the need for better early-stage target selection. We p... | [
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272826783 | 2409.15035 | 2024-09-23 | Can CLIP Count Stars? An Empirical Study on Quantity Bias in CLIP | CLIP has demonstrated great versatility in adapting to various downstream tasks, such as image editing and generation, visual question answering, and video understanding. However, CLIP-based applications often suffer from misunderstandings regarding user intent, leading to discrepancies between the required number of o... | [
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273227916 | 2410.05278 | 2024-09-23 | Dumpling GNN: Hybrid GNN Enables Better ADC Payload Activity Prediction Based on Chemical Structure | Antibody-drug conjugates (ADCs) have emerged as a promising class of targeted cancer therapeutics, but the design and optimization of their cytotoxic payloads remain challenging. This study introduces DumplingGNN, a novel hybrid Graph Neural Network architecture specifically designed for predicting ADC payload activity... | [
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272827843 | 2409.14940 | 2024-09-23 | Improving Adversarial Robustness for 3D Point Cloud Recognition at Test-Time through Purified Self-Training | Recognizing 3D point cloud plays a pivotal role in many real-world applications. However, deploying 3D point cloud deep learning model is vulnerable to adversarial attacks. Despite many efforts into developing robust model by adversarial training, they may become less effective against emerging attacks. This limitation... | [
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272831760 | 2409.15461 | 2024-09-23 | RAM2C: A Liberal Arts Educational Chatbot based on Retrieval-augmented Multi-role Multi-expert Collaboration | Recently, many studies focus on utilizing large language models (LLMs) into educational dialogues. Especially, within liberal arts dialogues, educators must balance \textbf{H}umanized communication, \textbf{T}eaching expertise, and \textbf{S}afety-ethics (\textbf{HTS}), besides the subject knowledge itself. However, du... | [
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272987386 | 2409.19010 | 2024-09-23 | A comprehensive study of on-device NLP applications -- VQA, automated Form filling, Smart Replies for Linguistic Codeswitching | Recent improvement in large language models, open doors for certain new experiences for on-device applications which were not possible before. In this work, we propose 3 such new experiences in 2 categories. First we discuss experiences which can be powered in screen understanding i.e. understanding whats on user scree... | [
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272832594 | 2409.15503 | 2024-09-23 | From Text to Treatment Effects: A Meta-Learning Approach to Handling Text-Based Confounding | One of the central goals of causal machine learning is the accurate estimation of heterogeneous treatment effects from observational data. In recent years, meta-learning has emerged as a flexible, model-agnostic paradigm for estimating conditional average treatment effects (CATE) using any supervised model. This paper ... | [
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272831808 | 2409.15582 | 2024-09-23 | Generalization vs. Specialization under Concept Shift | Machine learning models are often brittle under distribution shift, i.e., when data distributions at test time differ from those during training. Understanding this failure mode is central to identifying and mitigating safety risks of mass adoption of machine learning. Here we analyze ridge regression under concept shi... | [
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272826760 | 2409.15251 | 2024-09-23 | Machine Learning Toric Duality in Brane Tilings | We apply a variety of machine learning methods to the study of Seiberg duality within 4d $\mathcal{N}=1$ quantum field theories arising on the worldvolumes of D3-branes probing toric Calabi-Yau 3-folds. Such theories admit an elegant description in terms of bipartite tessellations of the torus known as brane tilings or... | [
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272826860 | 2409.14997 | 2024-09-23 | Enhancing Aspect-based Sentiment Analysis in Tourism Using Large Language Models and Positional Information | Aspect-Based Sentiment Analysis (ABSA) in tourism plays a significant role in understanding tourists' evaluations of specific aspects of attractions, which is crucial for driving innovation and development in the tourism industry. However, traditional pipeline models are afflicted by issues such as error propagation an... | [
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272827356 | 2409.14755 | 2024-09-23 | BranchPoseNet: Characterizing tree branching with a deep learning-based pose estimation approach | This paper presents an automated pipeline for detecting tree whorls in proximally laser scanning data using a pose-estimation deep learning model. Accurate whorl detection provides valuable insights into tree growth patterns, wood quality, and offers potential for use as a biometric marker to track trees throughout the... | [
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272826992 | 2409.14879 | 2024-09-23 | Privacy Policy Analysis through Prompt Engineering for LLMs | Privacy policies are often obfuscated by their complexity, which impedes transparency and informed consent. Conventional machine learning approaches for automatically analyzing these policies demand significant resources and substantial domain-specific training, causing adaptability issues. Moreover, they depend on ext... | [
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273233699 | 2410.07148 | 2024-09-23 | Lateral Ventricle Shape Modeling using Peripheral Area Projection for Longitudinal Analysis | The deformation of the lateral ventricle (LV) shape is widely studied to identify specific morphometric changes associated with diseases. Since LV enlargement is considered a relative change due to brain atrophy, local longitudinal LV deformation can indicate deformation in adjacent brain areas. However, conventional m... | [
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272827055 | 2409.15052 | 2024-09-23 | Brotherhood at WMT 2024: Leveraging LLM-Generated Contextual Conversations for Cross-Lingual Image Captioning | In this paper, we describe our system under the team name Brotherhood for the English-to-Lowres Multi-Modal Translation Task. We participate in the multi-modal translation tasks for English-Hindi, English-Hausa, English-Bengali, and English-Malayalam language pairs. We present a method leveraging multi-modal Large Lang... | [
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272826919 | 2409.15256 | 2024-09-23 | Behavioral Bias of Vision-Language Models: A Behavioral Finance View | Large Vision-Language Models (LVLMs) evolve rapidly as Large Language Models (LLMs) was equipped with vision modules to create more human-like models. However, we should carefully evaluate their applications in different domains, as they may possess undesired biases. Our work studies the potential behavioral biases of ... | [
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