Ward: Newsss

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NSW premier announces new laws banning hate speech and symbols in wake of Bondi beach terror attack

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 …

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Boosting t-SNE Efficiency for Sequencing Data: Insights from Kernel Selection

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

Can Transformers overcome the lack of data in the simulation of history-dependent flows?

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…

320

The Emergence of Chunking Structures with Hierarchical RNN

arXiv:2309.04919v2 Announce Type: replace
Abstract: In Natural Language Processing (NLP), predicting linguistic structures, such as parsing and chunking, has mostly relied on manual annotations of syntactic structures. This paper introduces an unsupervised approach to chunking, a syntactic task tha…

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Two-Step Data Augmentation for Masked Face Detection and Recognition: Turning Fake Masks to Real

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…

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Online Bandits with (Biased) Offline Data: Adaptive Learning under Distribution Mismatch

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…

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Information theory and discriminative sampling for model discovery

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

Gated KalmaNet: A Fading Memory Layer Through Test-Time Ridge Regression

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 …

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From Frames to Clips: Training-free Adaptive Key Clip Selection for Long-Form Video Understanding

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…

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Justice Department releases trove of Epstein files hours before deadline

The Justice Department has unveiled four groups of records from the Jeffrey Epstein files, the first documents to come to light under a new law signed by President Trump compelling their release. Scott MacFarlane reports.

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Inside enterprise AI’s turning point: 31 interviews on theCUBE that defined 2025

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.…

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Alchemist: Unlocking Efficiency in Text-to-Image Model Training via Meta-Gradient Data Selection

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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Detailed balance in large language model-driven agents

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MoHoBench: Assessing Honesty of Multimodal Large Language Models via Unanswerable Visual Questions

arXiv:2507.21503v3 Announce Type: replace
Abstract: Recently Multimodal Large Language Models (MLLMs) have achieved considerable advancements in vision-language tasks, yet produce potentially harmful or untrustworthy content. Despite substantial work investigating the trustworthiness of language mo…

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Roomba rival bets on AI to clean up market for robot vacuum cleaners

Roborock chief says innovations such as robotic arms and dog excrement recognition are key to survival

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AdaGradSelect: An adaptive gradient-guided layer selection method for efficient fine-tuning of SLMs

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…

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Provable optimal transport with transformers: The essence of depth and prompt engineering

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…

219

Generation is Required for Data-Efficient Perception

arXiv:2512.08854v2 Announce Type: replace
Abstract: It has been hypothesized that human-level visual perception requires a generative approach in which internal representations result from inverting a decoder. Yet today's most successful vision models are non-generative, relying on an encoder that …

210

Preparing Future-Ready Learners: K12 Skills Shift and GenAI EdTech Innovation Direction

arXiv:2512.16428v1 Announce Type: new
Abstract: Since Generative AI came out it has quickly embedded itself in our social fabric, triggering lots of discussions, predictions, and efforts from research, industry, government and capital market to experiment and embrace the technology. The question fo…

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A Network Arena for Benchmarking AI Agents on Network Troubleshooting

arXiv:2512.16381v1 Announce Type: new
Abstract: Agentic systems, powered by Large Language Models (LLMs), assist network engineers with network configuration synthesis and network troubleshooting tasks. For network troubleshooting, progress is hindered by the absence of standardized and accessible …