We present LEAF ("Lightweight Embedding Alignment Framework"), a knowledge distillation framework for text embedding models. A key distinguishing feature is that our distilled leaf models are aligned to their teacher. In the context of information retrieval, this allows for flexible asymmetric architectures where documents are encoded with the larger teacher model, while queries can be served with the smaller leaf models. We also show that leaf models automatically inherit MRL and robustness to output quantization whenever these properties are present in the teacher model, without explicitly training for them. To demonstrate the capability of our framework we publish leaf-ir, a 23M parameters information retrieval oriented text embedding model trained using LEAF, which sets a new state-of-the-art (SOTA) on BEIR, ranking #1 on the public leaderboard for this benchmark and for models of its size. When run in asymmetric mode, its retrieval performance is further increased. Our scheme is however not restricted to the information retrieval setting, and we demonstrate its wider applicability by synthesizing the multi-task leaf-mt model. This also sets a new SOTA, ranking #1 on the public MTEB v2 (English) leaderboard for its size. LEAF is applicable to black-box models and in contrast to other embedding model training frameworks, it does not require judgments nor hard negatives, and training can be conducted using small batch sizes. Thus, dataset and training infrastructure requirements for our framework are modest. We make our models publicly available under a permissive Apache 2.0 license.

Recent developments in sequence modeling have allowed continuation to be viewed as an autore-gressive task, to be modeled with a suitable tokenization scheme and a powerful sequence model like the ubiquitous Transformer [1]. A nonexhaustive list of prior work in this vein includes the Music Transformer [2], Museformer [3], FIGARO [4], and MuseCoco [5]. Most research in symbolic music modeling has so far focused on generalizing these techniques to--and improving performance on--long-sequence, multitrack, multi-instrument, and/or text-or attribute-controllable generative tasks. Typically, specialized techniques must be developed for these foundation models to handle these harder tasks, such as fine-and coarse-grained attention for long sequences [3], and text feature extraction techniques [4] and attribute augmentation [5] for controllability.

The arrival of AI coding assistants in educational settings presents a paradigm shift, introducing a "new kid in the classroom" for both students and instructors. Thus, understanding the perceptions of these key actors about this new dynamic is critical. This exploratory study contributes to this area by investigating how these tools are shaping the experiences of novice programmers in an introductory programming course. Through a two-part exam, we investigated student perceptions by first providing access to AI support for a programming task and then requiring an extension of the solution without it. We collected Likert-scale and open-ended responses from 20 students to understand their perceptions on the challenges they faced. Our findings reveal that students perceived AI tools as helpful for grasping code concepts and boosting their confidence during the initial development phase. However, a noticeable difficulty emerged when students were asked to work unaided, pointing to potential overreliance and gaps in foundational knowledge transfer. These insights highlight a critical need for new pedagogical approaches that integrate AI effectively while effectively enhancing core programming skills, rather than impersonating them.

Recent advancements in tool-augmented large language models have enabled them to interact with external tools, enhancing their ability to perform complex user tasks. However, existing approaches overlook the role of personalisation in guiding tool use. This work investigates how user preferences can be effectively integrated into goal-oriented dialogue agents. Through extensive analysis, we identify key weaknesses in the ability of LLMs to personalise tool use. To this end, we introduce TAPS, a novel solution that enhances personalised tool use by leveraging a structured tagging tool and an uncertainty-based tool detector. TAPS significantly improves the ability of LLMs to incorporate user preferences, achieving the new state-of-the-art for open source models on the NLSI task.

Terror charges against Luigi Mangione were dismissed in Manhattan court while supporters gathered outside, including one claiming marriage to his AI.

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AI agents thrive when trust is designed in from the start, says vice president of product management at NICE, Neeraj Verma. Automation has become a defining force in the customer experience. Between the chatbots that answer our questions and the recommendation systems that shape our choices, AI-driven tools are now embedded in nearly every interaction. But the latest wave of so-called "agentic AI"--systems that can plan, act, and adapt toward a defined goal--promises to push automation even further. Every single person that I've spoken to has at least spoken to some sort of GenAI bot on their phones. They expect experiences to be not scripted.

The Cloudflare CEO joined to talk about standing up to content scraping, the internet's potential futures, and his company's relationship to Trump. Matthew Prince may not be a household name, but the world most certainly knows his work. Prince is the cofounder and CEO of Cloudflare . Launched in 2010, the internet infrastructure company has found itself increasingly in the position of serving as the web's bodyguard. It filters out bad traffic, keeps sites safe, and stops them from crashing when too many people visit. Its tools defend against DDoS attacks. In 2017, Cloudflare made headlines when it dropped white supremacist site The Daily Stormer . Cloudflare's severing of ties with The Daily Stormer marked a momentous shift, one that came after years of claiming a neutral stance. Prince continues to evolve the way Cloudflare works. In July, the company rolled out a new tool tasked with blocking unauthorized AI scraping. It effectively creates a pay-per-crawl model requiring AI platforms to shell out money if they want access to a site's content. On this episode of, I talked to Prince about publishing, the old internet, and how his ideal version of the future web means that OpenAI just might become the Netflix of content. KATIE DRUMMOND: Good to have you here, Matthew. You should have been warned ahead of time, but you probably weren't.

Five members of the Japan Foundation's Nihongo Partners program (front) gather at the Japanese Embassy in New Delhi on Monday. NEW DELHI - Five people dispatched from Japan to assist in Japanese language education in India gathered in New Delhi on Monday for a six-month program aimed at enhancing cultural exchanges between the two countries. Under the Nihongo Partners program run by the Japan Foundation, the five will assist Japanese language teachers and introduce Japanese culture at secondary schools in the Delhi area over six months. It is the first time that Nihongo Partners are dispatched to a South Asian country, as the program has previously focused on Southeast Asia. The Japan Foundation plans to carry out a similar dispatch to India continuously over a decade starting this year, as part of an agreement reached at a summit of Japanese and Indian leaders last month to increase personnel exchanges between the two countries.

Artificial intelligence avatar Una will appear at the U.N. pavilion at Osaka Expo later this month as part of initiatives to combat climate change. An artificial intelligence avatar will appear at the U.N. Pavilion of the 2025 World Expo in Osaka in late September, sharing stories from Pacific island nations under threat from rising sea levels caused by climate change. The anime-inspired female character, Una, developed as part of climate initiatives supported by the Japanese government, will be showcased with the use of 3D hologram technology from Sept. 29 to Oct. 4. Launched online in May, Una can automatically respond to questions in English, Japanese and other languages. She will be like a strong voice to raise awareness on environment and climate, what is happening in the Pacific, Kanni Wignaraja, U.N. assistant secretary-general and regional director for Asia and the Pacific at the U.N. Development Programme (UNDP), said in an interview in Tokyo. In a time of both misinformation and too much information, quality journalism is more crucial than ever.