Art Therapy (AT) is an established practice that facilitates emotional processing and recovery through creative expression. Recently, Visual Art Recommender Systems (VA RecSys) have emerged to support AT, demonstrating their potential by personalizing therapeutic artwork recommendations. Nonetheless, current VA RecSys rely on visual stimuli for user modeling, limiting their ability to capture the full spectrum of emotional responses during preference elicitation. Previous studies have shown that music stimuli elicit unique affective reflections, presenting an opportunity for cross-domain recommendation (CDR) to enhance personalization in AT. Since CDR has not yet been explored in this context, we propose a family of CDR methods for AT based on music-driven preference elicitation. A large-scale study with 200 users demonstrates the efficacy of music-driven preference elicitation, outperforming the classic visual-only elicitation approach. Our source code, data, and models are available at https://github.com/ArtAICare/Affect-aware-CDR

We investigate how large language models perform latent multi-hop reasoning in prompts like "Wolfgang Amadeus Mozart's mother's spouse is". To analyze this process, we introduce logit flow, an interpretability method that traces how logits propagate across layers and positions toward the final prediction. Using logit flow, we identify four distinct stages in single-hop knowledge prediction: (A) entity subject enrichment, (B) entity attribute extraction, (C) relation subject enrichment, and (D) relation attribute extraction. Extending this analysis to multi-hop reasoning, we find that failures often stem from the relation attribute extraction stage, where conflicting logits reduce prediction accuracy. To address this, we propose back attention, a novel mechanism that enables lower layers to leverage higher-layer hidden states from different positions during attention computation. With back attention, a 1-layer transformer achieves the performance of a 2-layer transformer. Applied to four LLMs, back attention improves accuracy on five reasoning datasets, demonstrating its effectiveness in enhancing latent multi-hop reasoning ability.

On his videos, Sergey appears fresh-faced and smiling enthusiastically. Speaking in Russian and sometimes in slightly broken English, he goes through coding challenges step-by-step. His YouTube channel has more than 3,500 subscribers, interested in learning programming languages Python and Unity, or who want to hear more about neural networks, which underlie many artificial intelligence tools. Mr Mandik said Sergey showed not only remarkable developer skills but also "equally unique" skills in teaching. "For me, he is kind of a Mozart."

In recent years, AI-Generated Content (AIGC) has witnessed rapid advancements, facilitating the generation of music, images, and other forms of artistic expression across various industries. However, researches on general multi-modal music generation model remain scarce. To fill this gap, we propose a multi-modal music generation framework Mozart's Touch. It could generate aligned music with the cross-modality inputs, such as images, videos and text. Mozart's Touch is composed of three main components: Multi-modal Captioning Module, Large Language Model (LLM) Understanding & Bridging Module, and Music Generation Module. Unlike traditional approaches, Mozart's Touch requires no training or fine-tuning pre-trained models, offering efficiency and transparency through clear, interpretable prompts. We also introduce "LLM-Bridge" method to resolve the heterogeneous representation problems between descriptive texts of different modalities. We conduct a series of objective and subjective evaluations on the proposed model, and results indicate that our model surpasses the performance of current state-of-the-art models. Our codes and examples is availble at: https://github.com/WangTooNaive/MozartsTouch

The research explores the steerability of Large Language Models (LLMs), particularly OpenAI's ChatGPT iterations. By employing a behavioral psychology framework called OCEAN (Openness, Conscientiousness, Extroversion, Agreeableness, Neuroticism), we quantitatively gauged the model's responsiveness to tailored prompts. When asked to generate text mimicking an extroverted personality, OCEAN scored the language alignment to that behavioral trait. In our analysis, while "openness" presented linguistic ambiguity, "conscientiousness" and "neuroticism" were distinctly evoked in the OCEAN framework, with "extroversion" and "agreeableness" showcasing a notable overlap yet distinct separation from other traits. Our findings underscore GPT's versatility and ability to discern and adapt to nuanced instructions. Furthermore, historical figure simulations highlighted the LLM's capacity to internalize and project instructible personas, precisely replicating their philosophies and dialogic styles. However, the rapid advancements in LLM capabilities and the opaque nature of some training techniques make metric proposals degrade rapidly. Our research emphasizes a quantitative role to describe steerability in LLMs, presenting both its promise and areas for further refinement in aligning its progress to human intentions.

Academics from the University of Cambridge have revealed that they are on the hunt for'super memorisers'. These are people with exceptional memories, and are wanted to take part in a study which could uncover why some are much better at remembering than others. But it may not just be down to natural born ability, as there are some things you can do that have been scientifically proven to help improve your memory. As well as doing brain teasers, there are some less conventional ways, including eating chocolate, walking backwards and spending time in the sunshine. MailOnline takes a look at the strangest techniques scientists have discovered that could turn you into a super memoriser.

In the bustling city of Vienna, there lived a young boy named Wolfgang Amadeus Mozart. From a very young age, it was clear that he was a prodigy, gifted in music beyond his years. His father, Leopold, was a musician himself and recognized Wolfgang's talents early on, dedicating himself to nurturing and developing his son's abilities. Leopold took Wolfgang on tours throughout Europe, where they performed for royalty and commoners alike, and the young Mozart wowed audiences with his incredible musicianship. As he grew older, Wolfgang began to compose his own music and soon became one of the most sought-after composers in Europe.

Cracking jokes is not the same as digging them. I've been working around AI for 30 years and haven't yet seen an AI system able to explain what is funny about a given joke. I'm not talking about pre-programmed answers, like the ones you can find in Siri: if you ask "What's the meaning of life," you'll get a funny answer, like "A good life is about wearing clean and dry clothes," as this answer was put there by a human programmer; the system doesn't have a clue about why this could possibly be funny. Notice that the three questions are ordered in increasing difficulty levels, which perhaps is counterintuitive to many of us because creating something is supposedly more difficult than understanding something. But in this case, the opposite holds true, as we'll explain.

The uncanny valley is the abrupt dip in human affinity to a non-human creature when we see it approaching human-like characteristics. For instance, the spooky feeling when one looks at Sofia the robot or Lil Miquela the Instagram influencer. Really though, Lil Miquela gives me the creeps when I go through her timeline. It is the eeriness of a realistic face with personalized captions with her sense of awareness that she is not a real person that is quite unsettling. There is something surreal about it that makes working with it exciting.

Listening to motivational music like'Eye of the Tiger' by Survivor does actually help runners combat mental fatigue, a new study has claimed. University of Edinburgh experts found that a motivational playlist that included the 1982 smash hit improved performance on running tests after a mentally-draining cognitive test. As well as'Eye of the Tiger', the playlists included'No One Knows' by Queens of the Stone Age, as well as'Run This Town' by Jay-Z and'Power' by Kanye West. 'Eye of the Tiger' was famously featured throughout the 1982 film'Rocky III', starring Sylvester Stallone as the titular character. Listening to music while running might be the key to improving people's performance when they feel mentally fatigued, a University of Edinburgh study suggests (stock image) Arguably, the song, which reached number one on the UK singles chart, has become a quintessential motivational tune for sportspeople and gym-goers alike – but researchers were intrigued to find out if it actually helped performance.