Knowledge catalogue
arXiv:2604.23547v1 Announce Type: cross Abstract: Efficient hardware implementation of nonlinear activation functions is a crucial task in deploying artificial neural networks on resource-constrained
arXiv:2603.17573v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) Models have become the mainstream solution for robot control, but suffer from slow inference speeds. Speculative
arXiv:2604.23375v1 Announce Type: new Abstract: Convolutional neural networks (CNNs) have become increasingly difficult to deploy in resource-constrained environments due to their large memory and com
arXiv:2604.24606v1 Announce Type: new Abstract: Reverse parking maneuvering of a vehicle with trailer system is a difficult task to complete for human drivers due to the multi-body nature of the syste
arXiv:2604.23467v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved strong performance across natural language and multimodal tasks, yet their practical deployment remains con
I'm so confused… We're excited to partner with Google to offer Grounding With Exa inside of Gemini models! Using Exa's agent-first search, Gemini models can now access billions of websites, technical
arXiv:2503.04338v2 Announce Type: replace-cross Abstract: Graph-based Retrieval-Augmented Generation (RAG) has proven effective in integrating external knowledge into large language models (LLMs), imp
arXiv:2603.15130v2 Announce Type: replace Abstract: Indirectness is a common feature of daily communication, yet is underexplored in NLP research for both low-resource as well as high-resource languag
arXiv:2604.23436v1 Announce Type: cross Abstract: Reliable decision-making with streaming data requires principled uncertainty quantification of online methods. While first-order methods enable effici
arXiv:2604.23716v1 Announce Type: new Abstract: Information-theoretic (IT) measures are ubiquitous in artificial intelligence: entropy drives decision-tree splits and uncertainty quantification, cross
arXiv:2508.19679v2 Announce Type: replace Abstract: Recent advances in Vision-Language Models (VLMs) have enabled mobile agents to perceive and interact with real-world mobile environments based on hu
arXiv:2604.23095v1 Announce Type: new Abstract: Indoor environments lack the spatial intelligence infrastructure that GPS provides outdoors; first responders arriving at unfamiliar buildings typically
arXiv:2604.24002v1 Announce Type: cross Abstract: Improving the effectiveness of human-robot interaction requires social robots to accurately infer human goals through robust intention understanding.
arXiv:2604.22832v1 Announce Type: cross Abstract: Microscopy-based phenotypic profiling is scalable for drug discovery but lacks the mechanistic depth of transcriptomics, which remains costly and scar
arXiv:2511.07940v2 Announce Type: replace Abstract: Talking Face Generation (TFG) methods based on Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have recently achieved impressive prog
arXiv:2603.06589v2 Announce Type: replace-cross Abstract: Model calibration and debiasing are fundamental yet operationally expensive challenges in large-scale recommendation systems. Existing approac
arXiv:2508.10945v2 Announce Type: replace Abstract: Potholes on the roads are a serious hazard and maintenance burden. This poses a significant threat to road safety and vehicle longevity, especially
arXiv:2604.23320v1 Announce Type: new Abstract: The Convolutional Neural Networks (CNNs) have been the dominant and effective approach for general computer vision tasks. Recently, Kolmogorov-Arnold ne
arXiv:2604.23948v1 Announce Type: cross Abstract: The Korean writing system, extit{Hangeul}, has a unique character representation rigidly following the invention principles recorded in extit{Hunminje
Large Language Models (LLMs) demonstrate their reasoning ability through chain-of-thought (CoT) generation. However, LLM’s autoregressive decoding may limit the ability to revisit and refine earlier t
arXiv:2604.24608v1 Announce Type: cross Abstract: Large Language Models (LLMs) have recently been explored as fine-grained zero-shot re-rankers by leveraging attention signals to estimate document rel
arXiv:2604.23950v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have recently demonstrated remarkable capabilities in visual understanding and reasoning, but they also impose significant
arXiv:2604.23355v1 Announce Type: new Abstract: Existing LLM-based EDA agents are often isolated task-specific systems. This leads to repeated engineering effort and limited reuse of successful design
arXiv:2604.24636v1 Announce Type: cross Abstract: On-device Small Language Models (SLMs) promise fully offline, private AI experiences for mobile users (no cloud dependency, no data leaving the device
arXiv:2602.06542v3 Announce Type: replace Abstract: Deep knowledge tracing models have achieved significant breakthroughs in modeling student learning trajectories. However, these architectures requir
arXiv:2604.22829v1 Announce Type: new Abstract: The digital transformation of industrial manufacturing increasingly relies on the ability of autonomous robots to interact with legacy infrastructure, p
arXiv:2603.17717v3 Announce Type: replace-cross Abstract: Supervised detection of network attacks has always been a critical part of network intrusion detection systems (NIDS). Nowadays, in a pivotal
arXiv:2604.23814v1 Announce Type: cross Abstract: Urban environments contain many imaging sensors built for specific purposes, including ATM, body-worn, CCTV, and dashboard cameras. Under the opportun
arXiv:2510.10486v2 Announce Type: replace-cross Abstract: Open-source large language models (LLMs) have demonstrated considerable dominance over proprietary LLMs in resolving neural processing tasks,
arXiv:2604.23289v1 Announce Type: cross Abstract: Due to the unprecedented success of deep learning, it has become an integral component in several multimedia computing applications in todays world. U
arXiv:2604.23539v1 Announce Type: new Abstract: The rapid proliferation of Generative AI necessitates rigorous documentation standards for transparency and governance. However, manual creation of Mode
arXiv:2504.20018v2 Announce Type: replace-cross Abstract: Vector search plays a crucial role in many real-world applications. In addition to single-vector search, multi-vector search becomes important
arXiv:2508.05318v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has emerged as an effective paradigm for expanding the knowledge capacity of Multimodal Large Language Mo
arXiv:2604.23272v1 Announce Type: new Abstract: Humans understand and interact with the real world by relying on diverse physical feedback beyond visual perception. Motivated by this, recent approache
arXiv:2604.23519v1 Announce Type: cross Abstract: Multi-plane architectures have become increasingly prevalent in the Fat-Tree networks of AI data centers. By leveraging multiple ports on a single net
arXiv:2603.26729v2 Announce Type: replace-cross Abstract: The effective utilization of consistency is crucial for multi-view learning. GCNs leverage node connections to propagate information across th
arXiv:2604.24370v1 Announce Type: new Abstract: The shift from stand-level to individual-tree-level forest assessments supports improved biodiversity mapping, particularly in boreal ecosystems where t
arXiv:2511.10047v2 Announce Type: replace Abstract: Zero-shot anomaly classification (AC) and segmentation (AS) methods aim to identify and outline defects without using any labeled samples. In this p
arXiv:2408.08686v4 Announce Type: replace-cross Abstract: Language Models (LMs) have been widely used in recommender systems to incorporate textual information of items into item IDs, leveraging their
arXiv:2601.03790v3 Announce Type: replace-cross Abstract: Neologism-aware machine translation aims to translate source sentences containing neologisms into target languages. This field remains underex
arXiv:2604.23627v1 Announce Type: new Abstract: Resources for Grammatical Error Correction (GEC) in non-English languages are scarce, while available spellcheckers in these languages are mostly limite
arXiv:2604.22838v1 Announce Type: cross Abstract: With the accumulation of resources in the era of big data and the rise of pre-trained models in deep learning, optimizing neural networks for various
new in ml-intern: you can now actually see what's going on inside added native metric logging + trackio integration. every training run the agent kicks off now has live curves you can watch in real ti
arXiv:2412.04468v3 Announce Type: replace Abstract: Visual language models (VLMs) have made significant advances in accuracy in recent years. However, their efficiency has received much less attention
arXiv:2604.22815v1 Announce Type: cross Abstract: Classical vehicle dynamics contains several widely adopted misconceptions that, while intuitively appealing, may lead to inconsistencies when examined
arXiv:2604.22903v1 Announce Type: cross Abstract: The integration of quantum machine learning with classical deep learning offers promising avenues for medical image analysis by mapping data into high
arXiv:2602.00921v2 Announce Type: replace-cross Abstract: Optimal feedback control with implicit Hamiltonians poses a fundamental challenge for learning-based value function methods due to the absence
arXiv:2604.22958v1 Announce Type: new Abstract: Preference-based argumentation frameworks (PAFs) extend Dung's approach to abstract argumentation (AAFs) by encoding preferences over arguments. Such pr
arXiv:2507.06542v4 Announce Type: replace Abstract: Decentralized learning provides a scalable alternative to parameter-server-based training, yet its performance is often hindered by limited peer-to-
arXiv:2604.23402v1 Announce Type: cross Abstract: Haptic technologies have advanced rapidly, yet exploration of robotic touch remains dominated by replicating realistic environmental cues or hand gest
arXiv:2505.16888v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed via third-party system prompts downloaded from public marketplaces. We identify a criti
arXiv:2604.24707v1 Announce Type: new Abstract: Doorways and passages are critical structural elements for indoor robot navigation, yet they remain underexplored in modern Visual SLAM (VSLAM) framewor
arXiv:2604.24384v1 Announce Type: new Abstract: Automated vehicles (AVs) are commonly programmed to yield unconditionally to pedestrians in the interest of safety. However, this design choice can give
arXiv:2604.23543v1 Announce Type: cross Abstract: Test-time alignment methods offer a promising alternative to fine-tuning by steering the outputs of large language models (LLMs) at inference time wit
arXiv:2604.24642v1 Announce Type: new Abstract: The dream of instantly creating rich 360-degree panoramic worlds from text is rapidly becoming a reality, yet a crucial gap exists in our ability to rel
arXiv:2604.23974v1 Announce Type: new Abstract: Fake news generally refers to false information that is spread deliberately to deceive people, which has detrimental social effects. Existing fake news
arXiv:2604.24674v1 Announce Type: new Abstract: Radar offers unique advantages for localization in unstructured environments, including robustness to weather, lighting, and airborne particulates. Whil
arXiv:2604.24052v1 Announce Type: cross Abstract: Video-to-text summarization remains underexplored in terms of comprehensive evaluation methods. Traditional n-gram overlap-based metrics and recent la
arXiv:2604.24543v1 Announce Type: new Abstract: RGB-Thermal (T) crowd counting aims to integrate visible-spectrum and thermal infrared information to improve the robustness of crowd density estimation
arXiv:2604.22755v1 Announce Type: cross Abstract: Reliable decision support in nuclear engineering requires traceable, domain-grounded knowledge retrieval, yet safety and risk analysis workflows remai