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arXiv:2512.16873v1 Announce Type: new
Abstract: Artificial intelligence systems are increasingly deployed in domains that shape human behaviour, institutional decision-making, and societal outcomes. Existing responsible AI and governance efforts provide important normative principles but often lack…
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NSW parliament will be recalled on Monday and Tuesday to consider legislation responding to the Bondi terrorist attackGet our breaking news email, free app or daily news podcastNSW will outlaw the display of terrorist symbols, such as those of Islamic State and Hamas, and ban hate speech, including …
350

arXiv:2512.15900v1 Announce Type: new
Abstract: Dimensionality reduction techniques are essential for visualizing and analyzing high-dimensional biological sequencing data. t-distributed Stochastic Neighbor Embedding (t-SNE) is widely used for this purpose, traditionally employing the Gaussian kern…
320

arXiv:2512.16305v1 Announce Type: cross
Abstract: It is well known that the lack of information about certain variables necessary for the description of a dynamical system leads to the introduction of historical dependence (lack of Markovian character of the model) and noise. Traditionally, scienti…
223

arXiv:2512.16919v1 Announce Type: new
Abstract: Perceiving and reconstructing 3D scene geometry from visual inputs is crucial for autonomous driving. However, there still lacks a driving-targeted dense geometry perception model that can adapt to different scenarios and camera configurations. To bri…
220

arXiv:2405.02594v2 Announce Type: replace
Abstract: Traditional online learning models are typically initialized from scratch. By contrast, contemporary real-world applications often have access to historical datasets that can potentially enhanced the online learning processes. We study how offline…
229

arXiv:2512.15774v1 Announce Type: new
Abstract: Data scarcity and distribution shift pose major challenges for masked face detection and recognition. We propose a two-step generative data augmentation framework that combines rule-based mask warping with unpaired image-to-image translation using GAN…
210

arXiv:2512.16000v1 Announce Type: new
Abstract: Fisher information and Shannon entropy are fundamental tools for understanding and analyzing dynamical systems from complementary perspectives. They can characterize unknown parameters by quantifying the information contained in variables, or measure …
229

arXiv:2511.21016v2 Announce Type: replace
Abstract: As efficient alternatives to softmax Attention, linear State-Space Models (SSMs) achieve constant memory and linear compute, but maintain only a lossy, fading summary of the past, often leading to inferior performance in recall-oriented tasks. We …
218

arXiv:2510.02262v2 Announce Type: replace
Abstract: Video Large Language Models (VLMs) have achieved strong performance on various vision-language tasks, yet their practical use is limited by the massive number of visual tokens produced from raw video frames, which quickly exhausts the model's cont…
213

arXiv:2512.16905v1 Announce Type: new
Abstract: Recent advances in Text-to-Image (T2I) generative models, such as Imagen, Stable Diffusion, and FLUX, have led to remarkable improvements in visual quality. However, their performance is fundamentally limited by the quality of training data. Web-crawl…
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TheCUBE spent 2025 talking directly with top tech executives as they worked through how computing is being rebuilt inside their organizations, driven by real-world constraints rather than abstract roadmaps. Across those conversations, a consistent shift emerged away from theory and toward execution.…
209

arXiv:2512.15764v1 Announce Type: new
Abstract: Large Language Models (LLMs) can perform many NLP tasks well, but fully fine-tuning them is expensive and requires a lot of memory. Parameter-Efficient Fine-Tuning (PEFT) methods such as LoRA reduce this cost by adding small low-rank updates to frozen…
211

arXiv:2410.19931v3 Announce Type: replace
Abstract: Despite their empirical success, the internal mechanism by which transformer models align tokens during language processing remains poorly understood. This paper provides a mechanistic and theoretical explanation of token alignment in LLMs. We fir…
120

arXiv:2512.16270v1 Announce Type: new
Abstract: Text rendering has recently emerged as one of the most challenging frontiers in visual generation, drawing significant attention from large-scale diffusion and multimodal models. However, text editing within images remains largely unexplored, as it re…