Despite regulations imposed by nations and social media platforms, e.g. (Government of India, 2021; European Parliament and Council of the European Union, 2022), inter alia, hateful content persists as a significant challenge. Existing approaches primarily rely on reactive measures such as blocking or suspending offensive messages, with emerging strategies focusing on proactive measurements like detoxification and counterspeech. In our work, which we call HatePRISM, we conduct a comprehensive examination of hate speech regulations and strategies from three perspectives: country regulations, social platform policies, and NLP research datasets. Our findings reveal significant inconsistencies in hate speech definitions and moderation practices across jurisdictions and platforms, alongside a lack of alignment with research efforts. Based on these insights, we suggest ideas and research direction for further exploration of a unified framework for automated hate speech moderation incorporating diverse strategies.

Piano sustain pedal detection has previously been approached as a binary on/off classification task, limiting its application in real-world piano performance scenarios where pedal depth significantly influences musical expression. This paper presents a novel approach for high-resolution estimation that predicts continuous pedal depth values. We introduce a Transformer-based architecture that not only matches state-of-the-art performance on the traditional binary classification task but also achieves high accuracy in continuous pedal depth estimation. Furthermore, by estimating continuous values, our model provides musically meaningful predictions for sustain pedal usage, whereas baseline models struggle to capture such nuanced expressions with their binary detection approach. Additionally, this paper investigates the influence of room acoustics on sustain pedal estimation using a synthetic dataset that includes varied acoustic conditions. We train our model with different combinations of room settings and test it in an unseen new environment using a "leave-one-out" approach. Our findings show that the two baseline models and ours are not robust to unseen room conditions. Statistical analysis further confirms that reverberation influences model predictions and introduces an overestimation bias.

Automated fact checking with large language models (LLMs) offers a scalable alternative to manual verification. Evaluating fact checking is challenging as existing benchmark datasets often include post claim analysis and annotator cues, which are absent in real world scenarios where claims are fact checked immediately after being made. This limits the realism of current evaluations. We present Politi Fact Only (PFO), a 5 class benchmark dataset of 2,982 political claims from politifact.com, where all post claim analysis and annotator cues have been removed manually. This ensures that models are evaluated using only the information that would have been available prior to the claim's verification. Evaluating LLMs on PFO, we see an average performance drop of 22% in terms of macro f1 compared to PFO's unfiltered version. Based on the identified challenges of the existing LLM based fact checking system, we propose RAV (Recon Answer Verify), an agentic framework with three agents: question generator, answer generator, and label generator. Our pipeline iteratively generates and answers sub questions to verify different aspects of the claim before finally generating the label. RAV generalizes across domains and label granularities, and it outperforms state of the art approaches on well known baselines RAWFC (fact checking, 3 class) by 25.28%, and on HOVER (encyclopedia, 2 class) by 1.54% on 2 hop, 4.94% on 3 hop, and 1.78% on 4 hop, sub categories respectively. RAV shows the least performance drop compared to baselines of 16.3% in macro f1 when we compare PFO with its unfiltered version.

Hyperbolic representations are effective in modeling knowledge graph data which is prevalently used to facilitate multi-hop reasoning. However, a rigorous and detailed comparison of the two spaces for this task is lacking. In this paper, through a simple integration of hyperbolic representations with an encoder-decoder model, we perform a controlled and comprehensive set of experiments to compare the capacity of hyperbolic space versus Euclidean space in multi-hop reasoning. Our results show that the former consistently outperforms the latter across a diverse set of datasets. In addition, through an ablation study, we show that a learnable curvature initialized with the delta hyperbolicity of the utilized data yields superior results to random initializations. Furthermore, our findings suggest that hyperbolic representations can be significantly more advantageous when the datasets exhibit a more hierarchical structure.

Sony's anime-focused streaming service Crunchyroll has come under fire after users pointed out substandard AI-generated subtitles in several of its series. For example, viewers reportedly saw the phrase "ChatGPT said" in the German subtitles for Necronomico and the Cosmic Horror Show. Both the English and German captions have been criticized for being sloppy and difficult to understand. Engadget reports that Crunchyroll confirmed a third-party provider violated its agreement by using AI, and the company is now investigating the incident. The company's CEO, Rahul Purini, previously said in an interview with The Verge that Crunchyroll has been testing AI subtitles to release episodes more quickly.

If only more of these dumb ones come along," boasts a woman in a new video game that has fuelled a debate on sexism in China. The players in the live-action Revenge on Gold Diggers are male protagonists lured into relationships by manipulative women who are after their money - how the man responds shapes the rest of the story. It topped the gaming platform Steam's sales list within hours of its release in June but controversy quickly followed. Some slammed it for reinforcing insulting gender stereotypes, while supporters say the game cautions people about love scams. So heated was the criticism that the game's creators quietly renamed it Emotional Anti-Fraud Simulator the next day. But that wasn't enough to undo the damage. The game's lead director, Hong Kong filmmaker Mark Hu, has now been banned on several Chinese social media platforms. The game's creators insist they never intended to "target women" - rather they wanted to facilitate "open dialogue about emotional boundaries and the grey zones in modern dating". Xu Yikun, an artist who tried the game and found it deeply offensive, rejects that rationale. She accuses them of "a classic business model that thrives on generating content that sparks debate and divisions". Critics like her say the very term "gold digger" reeks of misogyny. "It's a label that's used, all too often, on women," Ms Xu says. "Sexist jokes and derogatory terms like these have found their way into our everyday language." "If you have a rich boyfriend, you are called a gold digger.

Industries can rethink how work gets done, raising the bar for productivity and workplace safety. Across industries, companies are feeling the squeeze from labor shortages, rising costs and nonstop pressure to boost efficiency. Robots are quickly becoming real-life solutions, and their promise has never felt more relevant. With factories and warehouses scrambling to fill essential roles, the search for fresh ideas is heating up. That's where AEON comes in.

A growing number of fire departments across the country are turning to artificial intelligence to help detect and respond to wildfires more quickly. The rise of artificial intelligence in education is forcing schools and universities to rethink everything from homework policies to how final exams are administered. With tools like ChatGPT now widespread, students can generate essays, solve complex math problems or draft lab reports in seconds, raising urgent questions about what authentic learning looks like in 2025. To fight back, some schools are turning to an unlikely solution: pen and paper. The old-school "blue book," a lined booklet used for handwritten test answers, is staging a comeback, according to reporting from The Wall Street Journal.

The traffic receded as Chicago withdrew into the distance behind me on Interstate 90. The speakers in my rental car, playing Spotify from my smartphone, put out the opening riff of a laid-back psychedelic-rock song. When the lyrics came, delivered in a folksy vibrato, they matched my mood: "Smoke in the sky / No peace found," the band's vocalist sang. Except perhaps he didn't really sing, because he doesn't exist. By all appearances, neither does the band, called the Velvet Sundown.

Perhaps unsurprisingly, the combo delivers record-setting performance. The launch of new Nvidia RTX mobile graphics--including the top-tier RTX 5090 with 24GB of VRAM--has the potential for chart-topping performance. Now it's joined by AMD's Ryzen 9 9955HX3D, a 16-core CPU with the company's vaunted 3D V-Cache, an extra stack of L3 cache that can prove useful in games. The MSI Raider A18 HX A9W brings both new chips into one chassis. That's incredible hardware, but the laptop retails for an equally incredible MSRP of 5,099.99. Each is an undisputed heavyweight in its category and should deliver a killer one-two punch of CPU and GPU performance. With that said, however, this MSI Raider A18 HX A9W still must deal with the power and thermal constraints faced by every laptop--and it will be interesting to see the results. The MSI Raider A18 HX A9W delivers additional technical highlights, too, like the PCIe 5.0 solid state drive and the 4K Mini-LED display.