This paper explores the modeling method of polyphonic music sequence. Due to the great potential of Transformer models in music generation, controllable music generation is receiving more attention. In the task of polyphonic music, current controllable generation research focuses on controlling the generation of chords, but lacks precise adjustment for the controllable generation of choral music textures. This paper proposed Condition Choir Transformer (CoCoFormer) which controls the output of the model by controlling the chord and rhythm inputs at a fine-grained level. In this paper, the self-supervised method improves the loss function and performs joint training through conditional control input and unconditional input training. In order to alleviate the lack of diversity on generated samples caused by the teacher forcing training, this paper added an adversarial training method. CoCoFormer enhances model performance with explicit and implicit inputs to chords and rhythms. In this paper, the experiments proves that CoCoFormer has reached the current better level than current models. On the premise of specifying the polyphonic music texture, the same melody can also be generated in a variety of ways.

The prevalence of propaganda in our digital society poses a challenge to societal harmony and the dissemination of truth. Detecting propaganda through NLP in text is challenging due to subtle manipulation techniques and contextual dependencies. To address this issue, we investigate the effectiveness of modern Large Language Models (LLMs) such as GPT-3 and GPT-4 for propaganda detection. We conduct experiments using the SemEval-2020 task 11 dataset, which features news articles labeled with 14 propaganda techniques as a multi-label classification problem. Five variations of GPT-3 and GPT-4 are employed, incorporating various prompt engineering and fine-tuning strategies across the different models. We evaluate the models' performance by assessing metrics such as $F1$ score, $Precision$, and $Recall$, comparing the results with the current state-of-the-art approach using RoBERTa. Our findings demonstrate that GPT-4 achieves comparable results to the current state-of-the-art. Further, this study analyzes the potential and challenges of LLMs in complex tasks like propaganda detection.

The study deployed four AI-detection tools to uncover possible evidence of hastily crafted, insincere apologies penned by an AI chatbot: ChatGPTZero, Undetectable.ai, The team collected apologies from posts and videos and transcribed the content, which was scanned through the four systems and then analyzed for the likelihood of AI generation. Overall percentages were then calculated, finding averages of each percentage found on different AI detector tools for that celebrity. Viral TikTok sensation Tiffany Gomas, whose unhinged reaction to another airline passenger spanned the internet, scored a combined 72 percent likelihood that AI-generated her video-taped Instagram apology. The transcribed text of the content was found to be 99 percent likely AI on Sapling and 45 percent likely AI on ChatGPTZero.

Every single year I tell myself that I'm not going to go overboard for the holidays. Then I start shopping for 20 people. If you're in the same boat, you'll be happy to know we've tracked down the Black Friday deals under $50 on reviewer-approved gadgets. WIRED tests products year-round and handpicked these deals based on the actual discounts. Products that are sold out or no longer discounted as of publishing will be crossed out . We'll update this guide through Black Friday. If you buy something using links in our stories, we may earn a commission. This helps support our journalism. If you watch mainly Amazon Prime content, the Fire TV Stick is the streaming device you need, and this one was just released at the end of September. You can stream from any service, of course, but it's heavily geared toward the company's own content. This 4K Max is faster, with 16 gigabytes of storage versus 8, but if you want to spend less and still stay in the Amazon ecosystem, the also-new 4K Stick is on sale for $25 ($25 off). The Echo Show 5 is typically overpriced at $90, but the deal price of $40 matches the best we have tracked. Just keep in mind that it goes on sale quite frequently. We prefer the Echo Show 10 for its larger size, but the smaller footprint of the Echo Show 5 is good for a nightstand or tiny kitchen.

It's Sunday now, but there are lots of Black Friday deals still available--most more appealing than the leftover turkey turning vaguely green in your fridge. Many of these will carry on over through Cyber Monday tomorrow too. WIRED's gear team spends all year combing the internet to bring you the best discounts on smartphones, laptops, iPads, headphones, battery chargers, and plenty more WIRED-approved gear. We have dozens of deals posts broken up by category which you can find linked below but this post is where we put our very favorite deals from across genres. We'll update this post throughout the weekend with more deals as we find them. We last updated it on Sunday, November 26, 2023, at 8 am. We test products year-round and handpicked these deals. The discount amounts we show are based on actual street prices at retailers in the past few months. Products that are sold out or no longer discounted as of publishing will be crossed out. We'll update this guide periodically.

We've already discussed how the Israel-Hamas war is the latest conflict where people are poring over social media and news channels looking for updates on what, exactly, is happening. After all, whether it's news about our neighborhoods or communities on the other side of the world, the web is where we go to find updates. And it's another reminder that misinformation is often big business, and it's everywhere: fake news and fabrications, half-truths and obfuscations, and flat-out lies and propaganda. The rise in AI-powered deep fakes has only made the problem worse and increased the amount of untrustworthy content out there. So is it actually still possible to filter truth from lies online?

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Communication is the bedrock of human interaction, influencing every facet of our lives -- from our personal connections to our professional endeavors. Beyond being a beneficial skill, effective communication stands as a vital asset in shaping the depth of our relationships, steering the course of our careers and serving as an incentive for personal growth and fulfillment. Communication resonates far beyond mere conversation; it's the foundation that underpins our connections, aspirations and journey toward self-improvement.

Fox News Flash top entertainment and celebrity headlines are here. The classic romantic comedy follows nine love stories, including tales about a woman whose husband is cheating on her, a man who's in love with his best friend's wife, and a little boy trying to profess his love to his crush. In its initial run, the movie made nearly $250 million at the global box office, and has since become a must-watch movie during the holiday season. Here is what the film's cast has been up to since its November 2003 release date. "Love Actually" is celebrating its 20th anniversary.

We present a framework SCStory for online story discovery, that helps people digest rapidly published news article streams in real-time without human annotations. To organize news article streams into stories, existing approaches directly encode the articles and cluster them based on representation similarity. However, these methods yield noisy and inaccurate story discovery results because the generic article embeddings do not effectively reflect the story-indicative semantics in an article and cannot adapt to the rapidly evolving news article streams. SCStory employs self-supervised and continual learning with a novel idea of story-indicative adaptive modeling of news article streams. With a lightweight hierarchical embedding module that first learns sentence representations and then article representations, SCStory identifies story-relevant information of news articles and uses them to discover stories. The embedding module is continuously updated to adapt to evolving news streams with a contrastive learning objective, backed up by two unique techniques, confidence-aware memory replay and prioritized-augmentation, employed for label absence and data scarcity problems. Thorough experiments on real and the latest news data sets demonstrate that SCStory outperforms existing state-of-the-art algorithms for unsupervised online story discovery.

Large language models (LLMs) have emerged as pivotal contributors in contemporary natural language processing and are increasingly being applied across a diverse range of industries. However, these large-scale probabilistic statistical models cannot currently ensure the requisite quality in professional content generation. These models often produce hallucinated text, compromising their practical utility in professional contexts. To assess the authentic reliability of LLMs in text generation, numerous initiatives have developed benchmark evaluations for hallucination phenomena. Nevertheless, these benchmarks frequently utilize constrained generation techniques due to cost and temporal constraints. These techniques encompass the use of directed hallucination induction and strategies that deliberately alter authentic text to produce hallucinations. These approaches are not congruent with the unrestricted text generation demanded by real-world applications. Furthermore, a well-established Chinese-language dataset dedicated to the evaluation of hallucinations in text generation is presently lacking. Consequently, we have developed an Unconstrained Hallucination Generation Evaluation (UHGEval) benchmark, designed to compile outputs produced with minimal restrictions by LLMs. Concurrently, we have established a comprehensive benchmark evaluation framework to aid subsequent researchers in undertaking scalable and reproducible experiments. We have also executed extensive experiments, evaluating prominent Chinese language models and the GPT series models to derive professional performance insights regarding hallucination challenges.