Trump turns to Epstein's lawyer to prove he has'nothing to hide' as he orders GOP to vote on releasing ALL documents to avert MAGA mutiny If I had to start over, here's how I'd make millions again! KEVIN O'LEARY reveals best investments, the career with soaring salaries and worst mistake he made My Montecito mole tells me why Me-Me-Meghan'threw a fit' after Kris Jenner's birthday party... this Kardashian drama just won't go away: KENNEDY Jeff Bezos's ex MacKenzie Scott contributes more than $700MILLION to'historically black colleges' Boy, 9, accused of raping and brutally attacking girl, 5, is allowed home with ankle monitor...despite victim's mom pleading with judge Smiling girl, 14, who vanished without a trace is found dead in RV... as cops arrest her family member Marjorie Taylor Greene's lookalike daughter defends mom against'fake MAGA' attacks amid fallout with Trump Trump crashes Mar-a-Lago wedding to talk about getting into heaven... but MAGA Christians are left angry Terrifying rise of'taboo cancer': Doctors reveal subtle signs ALL women must know... the most common cause... and a game-changer shot that could save your life She runs the anonymous real-life Gossip Girl account outing Hollywood scandals now we expose HER identity and the secret life she's desperate to hide Ariana Grande and Cynthia Erivo cause a stir with ANOTHER'ridiculous' red carpet moment Residents of city dubbed the'Birthplace of Silicon Valley' that's home to Mark Zuckerberg are sick of sleepless nights Nigerian gunmen abduct'dozens' of girls from boarding school after killing deputy head teacher in chilling echo of Chibok kidnappings Emily Blunt's asymmetrical frock horror and Kate Hudson's drab dress lead worst dressed stars at 16th Governors Awards Timothee Chalamet reveals his'true feelings' about ex Kylie Jenner after avoiding the'Kardashian curse' that has destroyed the lives and careers of the sisters' famous exes Iconic O.J. Simpson witness looks VERY different 30 years after legendary murder trial... see him now Most parents try to get them over and done with as soon as possible - but woke scientists now claim that nappy changes should be used as an opportunity to teach babies consent. Dr Nicole Downs and Dr Katherine Bussey, lecturers in Early Childhood at Deakin University in Australia, maintain that parents should not wait until their kids are teenagers to talk about appropriate touching. Instead, consent should be a'normal, everyday part of life' that teaches babies what is acceptable when it comes to their bodies. Parents should take their children's views into account, according to the pair - even when it comes to dealing with a dreaded nappy disaster.

The UN Security Council is expected to vote on a draft resolution backing Donald Trump's peace plan for Gaza. The text, submitted by the US, would give a mandate for the deployment of an International Stabilization Force (ISF) and to set up transitional governance there. The US says multiple unnamed countries have offered to contribute to the ISF, though it is unclear whether it would be required to ensure Hamas disarms or function as a peacekeeping force. Its formation is a central plank of Trump's 20-point plan which last month brought a ceasefire between Israel and Hamas in their two-year war. The draft also raises the possibility of a Palestinian state - something Israel strongly opposes.

The Anthropic chief executive, Dario Amodei, has flagged various concerns about its AI models recently. The Anthropic chief executive, Dario Amodei, has flagged various concerns about its AI models recently. AI firms must be clear on risks or repeat tobacco's mistakes, says Anthropic chief Artificial intelligence will become smarter than'most or all humans in most or all ways', says Dario Amodei Mon 17 Nov 2025 06.35 ESTLast modified on Mon 17 Nov 2025 07.25 EST Artificial intelligence companies must be transparent about the risks posed by their products or be in danger of repeating the mistakes of tobacco and opioid companies, according to the chief executive of the AI startup Anthropic. Dario Amodei, who runs the US company behind the Claude chatbot, said he believed AI would become smarter than "most or all humans in most or all ways" and urged his peers to "call it as you see it". Speaking to CBS News, Amodei said a lack of transparency about the impact of powerful AI would replay the errors of cigarette and opioid firms that failed to raise a red flag over the potential health damage of their own products.

What is the chance your plane will be hit by space debris? Explains: Let our writers untangle the complex, messy world of technology to help you understand what's coming next. In mid-October, a mysterious object cracked the windshield of a packed Boeing 737 cruising at 36,000 feet above Utah, forcing the pilots into an emergency landing. The internet was suddenly buzzing with the prospect that the plane had been hit by a piece of space debris. We still don't know exactly what hit the plane--likely a remnant of a weather balloon--but it turns out the speculation online wasn't that far-fetched. That's because while the risk of flights being hit by space junk is still small, it is, in fact, growing.

There are no catchy melodies in McCartney's first release in five years, only quiet hiss and the odd clatter. There are no catchy melodies in McCartney's first release in five years, only quiet hiss and the odd clatter. But Paul McCartney's first new recording in five years lacks the sing-along tune and jaunty guitar chops because there's barely anything there. In place of catchy melodies and evocative lyrics there is only quiet hiss and the odd clatter. It suggests that if AI companies unfairly exploit musicians' intellectual property to train their generative AI models, the creative ecosystem will be wrecked and original music silenced.

This paper explores the automatic classification of exam questions and learning outcomes according to Bloom's Taxonomy. A small dataset of 600 sentences labeled with six cognitive categories - Knowledge, Comprehension, Application, Analysis, Synthesis, and Evaluation - was processed using traditional machine learning (ML) models (Naive Bayes, Logistic Regression, Support Vector Machines), recurrent neural network architectures (LSTM, BiLSTM, GRU, BiGRU), transformer-based models (BERT and RoBERTa), and large language models (OpenAI, Gemini, Ollama, Anthropic). Each model was evaluated under different preprocessing and augmentation strategies (for example, synonym replacement, word embeddings, etc.). Among traditional ML approaches, Support Vector Machines (SVM) with data augmentation achieved the best overall performance, reaching 94 percent accuracy, recall, and F1 scores with minimal overfitting. In contrast, the RNN models and BERT suffered from severe overfitting, while RoBERTa initially overcame it but began to show signs as training progressed. Finally, zero-shot evaluations of large language models (LLMs) indicated that OpenAI and Gemini performed best among the tested LLMs, achieving approximately 0.72-0.73 accuracy and comparable F1 scores. These findings highlight the challenges of training complex deep models on limited data and underscore the value of careful data augmentation and simpler algorithms (such as augmented SVM) for Bloom's Taxonomy classification.

While large language models (LLMs) offer promising capabilities for automating academic workflows, existing systems for academic peer review remain constrained by text-only inputs, limited contextual grounding, and a lack of actionable feedback. In this work, we present an interactive web-based system for multimodal, community-aware peer review simulation to enable effective manuscript revisions before paper submission. Our framework integrates textual and visual information through multimodal LLMs, enhances review quality via retrieval-augmented generation (RAG) grounded in web-scale OpenReview data, and converts generated reviews into actionable to-do lists using the proposed Action:Objective[\#] format, providing structured and traceable guidance. The system integrates seamlessly into existing academic writing platforms, providing interactive interfaces for real-time feedback and revision tracking. Experimental results highlight the effectiveness of the proposed system in generating more comprehensive and useful reviews aligned with expert standards, surpassing ablated baselines and advancing transparent, human-centered scholarly assistance.

A person's gaze offers valuable insights into their focus of attention, level of social engagement, and confidence. In this work, we investigate how contextual cues combined with visual scene and facial information can be effectively utilized to predict and interpret social gaze patterns during conversational interactions. We introduce CSGaze, a context aware multimodal approach that leverages facial, scene information as complementary inputs to enhance social gaze pattern prediction from multi-person images. The model also incorporates a fine-grained attention mechanism centered on the principal speaker, which helps in better modeling social gaze dynamics. Experimental results show that CSGaze performs competitively with state-of-the-art methods on GP-Static, UCO-LAEO and AVA-LAEO. Our findings highlight the role of contextual cues in improving social gaze prediction. Additionally, we provide initial explainability through generated attention scores, offering insights into the model's decision-making process. We also demonstrate our model's generalizability by testing our model on open set datasets that demonstrating its robustness across diverse scenarios.

Vision-based lane keeping is a topic of significant interest in the robotics and autonomous ground vehicles communities in various on-road and off-road applications. The skid-steered vehicle architecture has served as a useful vehicle platform for human controlled operations. However, systematic modeling, especially of the skid-slip wheel terrain interactions (primarily in off-road settings) has created bottlenecks for automation deployment. End-to-end learning based methods such as imitation learning and deep reinforcement learning, have gained prominence as a viable deployment option to counter the lack of accurate analytical models. However, the systematic formulation and subsequent verification/validation in dynamic operation regimes (particularly for skid-steered vehicles) remains a work in progress. To this end, a novel approach for structured formulation for learning visual navigation is proposed and investigated in this work. Extensive software simulations, hardware evaluations and ablation studies now highlight the significantly improved performance of the proposed approach against contemporary literature.

Nature is not a blocker to housing growth and the government risks missing both its housing and nature targets if it views it as one, a cross-party group of MPs has warned in a new report. The Planning and Infrastructure Bill overrides existing habitat protections, which the government has suggested is a barrier to its target to build 1.5 million houses by the end of this parliament. But in a report published on Sunday, the Environmental Audit Committee (EAC) found the measures outlined in the bill are not enough to allow the government to meet its goals. Using nature as a scapegoat means that the government will be less effective at tackling some of the genuine challenges facing the planning system, the report said. A Ministry of Housing spokesperson said it was fixing a failing system with landmark reforms, which would deliver a win-win for the economy and the environment.