Knowledge catalogue
arXiv:2605.15365v1 Announce Type: new Abstract: Communicating using only a limited vocabulary is a common but challenging cognitive phenomenon, requiring an ideal communicator to plan carefully to opt
arXiv:2605.16179v1 Announce Type: new Abstract: Agricultural landscape segmentation in the Global South is challenging as it is characterized by fragmented plots, high intra-class variance, and a scar
arXiv:2605.16165v1 Announce Type: cross Abstract: Autoregressive next-token training offers a unified formulation for image generation and text understanding, but it also creates strong modality compe
arXiv:2605.16087v1 Announce Type: cross Abstract: Deep Neural Networks have become the dominant solution for Autonomous Driving perception, but their opacity conflicts with emerging Trustworthy AI gui
arXiv:2605.14461v1 Announce Type: new Abstract: Existing object removal tools often rely on manual masks or text prompts, making precise removal difficult for non-expert users in complex scenes and of
arXiv:2505.11809v3 Announce Type: replace Abstract: Visibility analysis in urban planning has traditionally relied on line-of-sight (LoS) simulations, which capture geometric occlusion. However, these
arXiv:2505.22394v2 Announce Type: replace Abstract: We present PacTure, a novel framework for generating physically-based rendering (PBR) material textures for an untextured 3D mesh from a text descri
arXiv:2408.12935v4 Announce Type: replace Abstract: AI Safety is an emerging area of critical importance to the safe adoption and deployment of AI systems. With the rapid proliferation of AI and espec
arXiv:2605.13221v1 Announce Type: new Abstract: In cloud manufacturing, unmanned aerial vehicles (UAVs) can support both product collection and mobile edge computing (MEC). This joint operation forms
arXiv:2605.13538v1 Announce Type: cross Abstract: Personally Identifiable Information (PII) redaction usually replaces detected entities with placeholder tokens such as [PERSON], destroying the downst
arXiv:2605.12838v1 Announce Type: new Abstract: Tracking an interpretable emotional arc of a conversation via the sentiment of individual utterances processed as a whole is central to both understandi
arXiv:2411.15913v4 Announce Type: replace-cross Abstract: Music style transfer blends source structure with reference style to enable personalized music creation. However, existing zero-shot methods o
A Chrome extension that communicates directly with local Ollama instances without sending data to external servers , enabling users to submit messages through a popup interface with responses streamin
arXiv:2605.11859v1 Announce Type: new Abstract: Robot navigation is a crucial task with applications to social robots in dynamic human environments. While Reinforcement Learning (RL) has shown great p
arXiv:2605.11959v1 Announce Type: cross Abstract: Multimodal video summarization requires visual features that align semantically with language generation. Traditional approaches rely on CNN features
arXiv:2605.11154v1 Announce Type: cross Abstract: Modern astrophysical studies rely heavily on complex data analysis pipelines; however, published descriptions often lack the detail required for compu
arXiv:2510.05408v2 Announce Type: replace Abstract: Recovering the past from present observations is an intriguing challenge with potential applications in forensics and scene analysis. Thermal imagin
arXiv:2605.11840v1 Announce Type: new Abstract: Radar-camera depth estimation must turn an ultra-sparse, all-weather, metric radar signal into a dense per-pixel depth map. Existing methods -- concaten
arXiv:2602.05352v2 Announce Type: replace Abstract: Modern neural networks have shown promise for solving partial differential equations over surfaces, often by discretizing the surface as a mesh and
arXiv:2605.11435v1 Announce Type: new Abstract: In this paper, we propose a zero-reference diffusion-based framework, named ZeroIDIR, for illumination degradation image restoration, which decouples th
arXiv:2605.10239v1 Announce Type: new Abstract: This work explores a simple yet powerful lightweight adapter design for feed-forward 3D Gaussian Splatting (3DGS). Existing methods typically apply comp
arXiv:2603.10126v2 Announce Type: replace-cross Abstract: We propose a standalone autoregressive (AR) Action Expert that generates actions as a continuous causal sequence while conditioning on refresh
arXiv:2605.08218v1 Announce Type: cross Abstract: This paper proposes latent visualization by optimization (LVO), a mechanistic interpretability technique that extends feature visualization by optimiz
arXiv:2603.08065v2 Announce Type: replace-cross Abstract: Structured pruning reduces LLM inference cost by removing low-importance architectural components. This can be viewed as learning a multiplica
arXiv:2602.05391v2 Announce Type: replace Abstract: Dataset distillation seeks to synthesize a highly compact dataset that achieves performance comparable to the original dataset on downstream tasks.
arXiv:2507.06658v2 Announce Type: replace-cross Abstract: Theories of democratic stability, populism, and party-system crisis often point to a form of polarization that comparative research rarely mea
arXiv:2605.09429v1 Announce Type: cross Abstract: Are low-attention visual tokens truly redundant in vision-language reasoning? Existing pruning methods often assume so, ranking visual tokens by shall
arXiv:2605.09419v1 Announce Type: new Abstract: While experience replay is essential for data efficiency in reinforcement learning (RL), standard methods treat the replay buffer as a passive memory sy
arXiv:2605.10458v1 Announce Type: new Abstract: Atomic properties such as partial charges or multipoles encode chemically meaningful information that can inform downstream molecular property predictio
arXiv:2605.08464v1 Announce Type: new Abstract: The manifold hypothesis (MH) is often used to explain how machine learning can overcome the curse of dimensionality. However, the MH is only applicable
arXiv:2511.09016v2 Announce Type: replace-cross Abstract: The Kalman filter and Rauch-Tung-Striebel (RTS) smoother are optimal for state estimation in linear dynamic systems. With nonlinear systems, t
arXiv:2605.07478v1 Announce Type: new Abstract: Speech-driven facial animation requires accurate correspondence between acoustic signals and facial motion, especially for articulation-related mouth mo
arXiv:2602.16928v3 Announce Type: replace-cross Abstract: Much of the advancement in Multi-Agent Reinforcement Learning (MARL) for imperfect-information games has historically depended on the manual,
arXiv:2605.07244v1 Announce Type: cross Abstract: We introduce Mutual Reinforcement Learning, a framework for concurrent RL post-training in which heterogeneous LLM policies exchange typed experience
arXiv:2605.07649v1 Announce Type: cross Abstract: Over the last few years, research on autonomous systems has matured to such a degree that the field is increasingly well-positioned to translate resea
arXiv:2605.05806v2 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) typically treats retrieval and generation as separate systems. We ask whether an attention-based encoder-decode
arXiv:2605.07100v1 Announce Type: cross Abstract: Constructing valid and informative conformal prediction regions for multi-dimensional outputs remains a fundamental challenge. While conformal predict
arXiv:2605.04062v1 Announce Type: new Abstract: Recent years have witnessed an increasing interest in deploying LLMs on resource-constrained devices, among which quantization has emerged as a promisin
arXiv:2602.02924v2 Announce Type: replace Abstract: Diffusion policy sampling enables reinforcement learning (RL) to represent multimodal action distributions beyond suboptimal unimodal Gaussian polic
arXiv:2605.04744v1 Announce Type: new Abstract: Plant breeding underpins global food security through incremental, accumulating improvements in crop yield, quality and sustainability, achieved via rep
arXiv:2605.03408v1 Announce Type: new Abstract: Reinforcement learning systems rely on environment interfaces that specify observations and reward functions, yet constructing these interfaces for new
arXiv:2605.02912v1 Announce Type: new Abstract: Video Anomaly Detection (VAD) has traditionally been framed as binary classification or outlier detection, providing neither interpretable reasoning nor
Dedicated inference cloud startup Deepinfra Inc. is looking to expand its global capacity after raising 107 million in a Series B round of funding led by 500 Global and Georges Harik, who was one of G
arXiv:2605.00874v1 Announce Type: new Abstract: The rapid proliferation of AI-powered video generation systems has introduced significant challenges in content moderation, particularly with respect to
arXiv:2405.10271v4 Announce Type: replace Abstract: The practical deployment of Federated Learning (FL) on resource-constrained devices is fundamentally limited by the high cost of training large mode
arXiv:2605.00279v1 Announce Type: cross Abstract: AI-powered edge computing security is moving Intelligent Transportation Systems (ITS) from passive, rule-based protections to proactive, smart, zero-t
arXiv:2503.06740v2 Announce Type: replace Abstract: Gaussian Splatting has become a popular technique for various 3D Computer Vision tasks, including novel view synthesis, scene reconstruction, and dy
arXiv:2605.00294v1 Announce Type: new Abstract: This study presents a systematic approach to identifying and characterizing student misconceptions in online learning environments through a novel combi
arXiv:2507.12414v2 Announce Type: replace-cross Abstract: Training of autonomous driving systems requires extensive datasets with precise annotations to attain robust performance. Human annotations su
arXiv:2604.27859v1 Announce Type: new Abstract: Reinforcement Learning (RL) has traditionally focused on training specialized agents to optimize predefined reward functions within narrowly defined env
arXiv:2604.26229v1 Announce Type: new Abstract: This study compares machine learning and deep learning approaches for cyberbullying detection in Indonesian-language Instagram comments. Using a balance
arXiv:2505.22910v2 Announce Type: replace Abstract: When a student fails an exam, do we tend to blame their effort or the test's difficulty? Attribution, defined as how reasons are assigned to event o
arXiv:2412.10441v2 Announce Type: replace-cross Abstract: In the burgeoning field of medical imaging, precise computation of 3D volume holds a significant importance for subsequent qualitative analysi
arXiv:2604.22555v1 Announce Type: new Abstract: Estimating racial disparity requires individual-level race data, which are often unavailable due to the sensitivity of collecting such information. To a
This post discusses the need for built-in speech-to-text (STT) and text-to-speech (TTS) capabilities in a product or platform (likely referring to Hugging Face's platform based on the mention of Clem
arXiv:2604.16809v1 Announce Type: cross Abstract: Delayed loss spikes have been reported in neural-network training, but existing theory mainly explains earlier non-monotone behavior caused by overly
arXiv:2602.03986v2 Announce Type: replace Abstract: Conformal prediction, a post-hoc, distribution-free, finite-sample method of uncertainty quantification that offers formal coverage guarantees under
arXiv:2604.14287v1 Announce Type: new Abstract: Tensor networks were developed in the context of many-body physics as compressed representations of multiparticle quantum states. These representations
arXiv:2604.14163v1 Announce Type: new Abstract: Maritime distress communications transmitted over very high frequency (VHF) radio are safety-critical voice messages used to report emergencies at sea.
arXiv:2510.19268v2 Announce Type: replace-cross Abstract: Long-horizon routing tasks of deformable linear objects (DLOs), such as cables and ropes, are common in industrial assembly lines and everyday