{"date":"2025-11-11","schema_version":1,"captured_at":"2026-08-25T22:55:49.311Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":15},"attention":[{"title":"Google Chrome","views":341734,"rank":4,"extract":"Google Chrome is a cross-platform web browser developed by Google. It was launched in September 2008 for Microsoft Windows and was built with free software components from Apple WebKit and Mozilla Firefox. Versions for Linux, macOS, iOS, iPadOS, and Android we","url":"https://en.wikipedia.org/wiki/Google_Chrome","thumb":"https://upload.wikimedia.org/wikipedia/commons/thumb/e/e1/Google_Chrome_icon_%28February_2022%29.svg/330px-Google_Chrome_icon_%28February_2022%29.svg.png?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail"},{"title":"James A. 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squares","points":184,"comments":56,"url":"https://unflipgame.com/","discussion":"https://news.ycombinator.com/item?id=45891066"}],"research":[{"title":"3D Guard-Layer: An Integrated Agentic AI Safety System for Edge Artificial Intelligence","abstract":"AI systems have found a wide range of real-world applications in recent years. The adoption of edge artificial intelligence, embedding AI directly into edge devices, is rapidly growing. Despite the implementation of guardrails and safety mechanisms, security vulnerabilities and challenges have become increasingly prevalent in this domain, posing a significant barrier to the practical deployment and safety of AI syste","authors":["Eren Kurshan","Yuan Xie","Paul Franzon"],"url":"http://arxiv.org/abs/2511.08842v1","arxiv_id":"2511.08842v1","published":"2025-11-11T23:55:09Z"},{"title":"Enhancing DPSGD via Per-Sample Momentum and Low-Pass Filtering","abstract":"Differentially Private Stochastic Gradient Descent (DPSGD) is widely used to train deep neural networks with formal privacy guarantees. However, the addition of differential privacy (DP) often degrades model accuracy by introducing both noise and bias. Existing techniques typically address only one of these issues, as reducing DP noise can exacerbate clipping bias and vice-versa. In this paper, we propose a novel met","authors":["Xincheng Xu","Thilina Ranbaduge","Qing Wang","Thierry Rakotoarivelo","David Smith"],"url":"http://arxiv.org/abs/2511.08841v1","arxiv_id":"2511.08841v1","published":"2025-11-11T23:40:02Z"},{"title":"Beyond Task-Oriented and Chitchat Dialogues: Proactive and Transition-Aware Conversational Agents","abstract":"Conversational agents have traditionally been developed for either task-oriented dialogue (TOD) or open-ended chitchat, with limited progress in unifying the two. Yet, real-world conversations naturally involve fluid transitions between these modes. To address this gap, we introduce TACT (TOD-And-Chitchat Transition), a dataset designed for transition-aware dialogue modeling that incorporates structurally diverse and","authors":["Yejin Yoon","Yuri Son","Namyoung So","Minseo Kim","Minsoo Cho","Chanhee Park"],"url":"http://arxiv.org/abs/2511.08835v1","arxiv_id":"2511.08835v1","published":"2025-11-11T23:03:44Z"},{"title":"TIGER-MARL: Enhancing Multi-Agent Reinforcement Learning with Temporal Information through Graph-based Embeddings and Representations","abstract":"In this paper, we propose capturing and utilizing \\textit{Temporal Information through Graph-based Embeddings and Representations} or \\textbf{TIGER} to enhance multi-agent reinforcement learning (MARL). We explicitly model how inter-agent coordination structures evolve over time. While most MARL approaches rely on static or per-step relational graphs, they overlook the temporal evolution of interactions that naturall","authors":["Nikunj Gupta","Ludwika Twardecka","James Zachary Hare","Jesse Milzman","Rajgopal Kannan","Viktor Prasanna"],"url":"http://arxiv.org/abs/2511.08832v1","arxiv_id":"2511.08832v1","published":"2025-11-11T23:00:23Z"},{"title":"Neural Value Iteration","abstract":"The value function of a POMDP exhibits the piecewise-linear-convex (PWLC) property and can be represented as a finite set of hyperplanes, known as $α$-vectors. Most state-of-the-art POMDP solvers (offline planners) follow the point-based value iteration scheme, which performs Bellman backups on $α$-vectors at reachable belief points until convergence. However, since each $α$-vector is $|S|$-dimensional, these methods","authors":["Yang You","Ufuk Çakır","Alex Schutz","Nick Hawes"],"url":"http://arxiv.org/abs/2511.08825v3","arxiv_id":"2511.08825v3","published":"2025-11-11T22:46:31Z"},{"title":"DT-NVS: Diffusion Transformers for Novel View Synthesis","abstract":"Generating novel views of a natural scene, e.g., every-day scenes both indoors and outdoors, from a single view is an under-explored problem, even though it is an organic extension to the object-centric novel view synthesis. Existing diffusion-based approaches focus rather on small camera movements in real scenes or only consider unnatural object-centric scenes, limiting their potential applications in real-world set","authors":["Wonbong Jang","Jonathan Tremblay","Lourdes Agapito"],"url":"http://arxiv.org/abs/2511.08823v1","arxiv_id":"2511.08823v1","published":"2025-11-11T22:40:00Z"},{"title":"Learning with Preserving for Continual Multitask Learning","abstract":"Artificial intelligence systems in critical fields like autonomous driving and medical imaging analysis often continually learn new tasks using a shared stream of input data. For instance, after learning to detect traffic signs, a model may later need to learn to classify traffic lights or different types of vehicles using the same camera feed. This scenario introduces a challenging setting we term Continual Multitas","authors":["Hanchen David Wang","Siwoo Bae","Zirong Chen","Meiyi Ma"],"url":"http://arxiv.org/abs/2511.11676v1","arxiv_id":"2511.11676v1","published":"2025-11-11T22:23:20Z"},{"title":"Who Gets the Reward &amp; Who Gets the Blame? Evaluation-Aligned Training Signals for Multi-LLM Agents","abstract":"Large Language Models (LLMs) in multi-agent systems (MAS) have shown promise for complex tasks, yet current training methods lack principled ways to connect system-level evaluation with agent- and message-level learning. We propose a theoretical framework that unifies cooperative game-theoretic attribution with process reward modeling to transform system evaluation to agent credit to response-level signals. Unlike pr","authors":["Chih-Hsuan","Yang","Tanwi Mallick","Le Chen","Krishnan Raghavan","Amal Gueroudji"],"url":"http://arxiv.org/abs/2511.10687v3","arxiv_id":"2511.10687v3","published":"2025-11-11T22:21:08Z"},{"title":"Structured Uncertainty guided Clarification for LLM Agents","abstract":"LLM agents with tool-calling capabilities often fail when user instructions are ambiguous or incomplete, leading to incorrect invocations and task failures. Existing approaches operate in unstructured language spaces, generating clarifying questions through prompting strategies that lack principled criteria for determining which questions to ask and when to stop. We introduce a principled formulation of structured un","authors":["Manan Suri","Puneet Mathur","Nedim Lipka","Franck Dernoncourt","Ryan A. Rossi","Dinesh Manocha"],"url":"http://arxiv.org/abs/2511.08798v2","arxiv_id":"2511.08798v2","published":"2025-11-11T21:50:44Z"},{"title":"Beyond One-Way Pruning: Bidirectional Pruning-Regrowth for Extreme Accuracy-Sparsity Tradeoff","abstract":"As a widely adopted model compression technique, model pruning has demonstrated strong effectiveness across various architectures. However, we observe that when sparsity exceeds a certain threshold, both iterative and one-shot pruning methods lead to a steep decline in model performance. This rapid degradation limits the achievable compression ratio and prevents models from meeting the stringent size constraints requ","authors":["Junchen Liu","Yi Sheng"],"url":"http://arxiv.org/abs/2511.11675v1","arxiv_id":"2511.11675v1","published":"2025-11-11T21:22:29Z"},{"title":"The Singularity Warfare: The metatheoretical Framework","abstract":"This paper introduces the \"Singularity Warfare\" concept, arguing that the accelerating pace of technological revolution, driven by artificial intelligence and quantum mechanics, is fundamentally reshaping the nature of conflict. Moving beyond traditional \"Newtonian\" warfare and current military doctrines, this framework posits that future battlefields will be defined by a merger of physical and abstract domains, wher","authors":["Ridvan Bari Urcosta"],"url":"http://arxiv.org/abs/2511.11674v1","arxiv_id":"2511.11674v1","published":"2025-11-11T21:20:02Z"},{"title":"Hey Pentti, We Did (More of) It!: A Vector-Symbolic Lisp With Residue Arithmetic","abstract":"Using Frequency-domain Holographic Reduced Representations (FHRRs), we extend a Vector-Symbolic Architecture (VSA) encoding of Lisp 1.5 with primitives for arithmetic operations using Residue Hyperdimensional Computing (RHC). Encoding a Turing-complete syntax over a high-dimensional vector space increases the expressivity of neural network states, enabling network states to contain arbitrarily structured representati","authors":["Connor Hanley","Eilene Tomkins-Flanaganm","Mary Alexandria Kelly"],"url":"http://arxiv.org/abs/2511.08767v1","arxiv_id":"2511.08767v1","published":"2025-11-11T20:42:56Z"},{"title":"Information-Driven Fault Detection and Identification for Multi-Agent Spacecraft Systems: Collaborative On-Orbit Inspection Mission","abstract":"This work presents a global-to-local, task-aware fault detection and identification (FDI) framework for multi-spacecraft systems conducting collaborative inspection missions in low Earth orbit. The inspection task is represented by a global information-driven cost functional that integrates the sensor model, spacecraft poses, and mission-level information-gain objectives. This formulation links guidance, control, and","authors":["Akshita Gupta","Arna Bhardwaj","Yashwanth Kumar Nakka","Changrak Choi","Amir Rahmani"],"url":"http://arxiv.org/abs/2511.08752v1","arxiv_id":"2511.08752v1","published":"2025-11-11T20:10:39Z"},{"title":"Interpretable by Design: Query-Specific Neural Modules for Explainable Reinforcement Learning","abstract":"Reinforcement learning has traditionally focused on a singular objective: learning policies that select actions to maximize reward. We challenge this paradigm by asking: what if we explicitly architected RL systems as inference engines that can answer diverse queries about their environment? In deterministic settings, trained agents implicitly encode rich knowledge about reachability, distances, values, and dynamics ","authors":["Mehrdad Zakershahrak"],"url":"http://arxiv.org/abs/2511.08749v1","arxiv_id":"2511.08749v1","published":"2025-11-11T20:08:32Z"},{"title":"Vector Symbolic Algebras for the Abstraction and Reasoning Corpus","abstract":"The Abstraction and Reasoning Corpus for Artificial General Intelligence (ARC-AGI) is a generative, few-shot fluid intelligence benchmark. Although humans effortlessly solve ARC-AGI, it remains extremely difficult for even the most advanced artificial intelligence systems. Inspired by methods for modelling human intelligence spanning neuroscience to psychology, we propose a cognitively plausible ARC-AGI solver. Our s","authors":["Isaac Joffe","Chris Eliasmith"],"url":"http://arxiv.org/abs/2511.08747v1","arxiv_id":"2511.08747v1","published":"2025-11-11T20:07:50Z"},{"title":"Intuitive Programming, Adaptive Task Planning, and Dynamic Role Allocation in Human-Robot Collaboration","abstract":"Remarkable capabilities have been achieved by robotics and AI, mastering complex tasks and environments. Yet, humans often remain passive observers, fascinated but uncertain how to engage. Robots, in turn, cannot reach their full potential in human-populated environments without effectively modeling human states and intentions and adapting their behavior. To achieve a synergistic human-robot collaboration (HRC), a co","authors":["Marta Lagomarsino","Elena Merlo","Andrea Pupa","Timo Birr","Franziska Krebs","Cristian Secchi"],"url":"http://arxiv.org/abs/2511.08732v1","arxiv_id":"2511.08732v1","published":"2025-11-11T19:49:30Z"},{"title":"Benevolent Dictators? On LLM Agent Behavior in Dictator Games","abstract":"In behavioral sciences, experiments such as the ultimatum game are conducted to assess preferences for fairness or self-interest of study participants. In the dictator game, a simplified version of the ultimatum game where only one of two players makes a single decision, the dictator unilaterally decides how to split a fixed sum of money between themselves and the other player. Although recent studies have explored b","authors":["Andreas Einwiller","Kanishka Ghosh Dastidar","Artur Romazanov","Annette Hautli-Janisz","Michael Granitzer","Florian Lemmerich"],"url":"http://arxiv.org/abs/2511.08721v1","arxiv_id":"2511.08721v1","published":"2025-11-11T19:29:12Z"},{"title":"SynthTools: A Framework for Scaling Synthetic Tools for Agent Development","abstract":"For agentic systems to use external tools to solve complex, long-horizon tasks, we need a large set of diverse and controllable tool-use environments. We introduce SynthTools, a fully LLM-based pipeline spanning the entire lifecycle: environment generation, simulation, validation and task construction. By operating end-to-end through LLMs, our framework complements other tool-use environments bottlenecked by the comp","authors":["Tommaso Castellani","Naimeng Ye","Daksh Mittal","Thomson Yen","Emmanouil Koukoumidis","William Zeng"],"url":"http://arxiv.org/abs/2511.09572v2","arxiv_id":"2511.09572v2","published":"2025-11-11T19:26:40Z"},{"title":"Bridging Natural Language and ASP: A Hybrid Approach Using LLMs and AMR Parsing","abstract":"Answer Set Programming (ASP) is a declarative programming paradigm based on logic programming and non-monotonic reasoning. It is a tremendously powerful tool for describing and solving combinatorial problems. Like any other language, ASP requires users to learn how it works and the syntax involved. It is becoming increasingly required for those unfamiliar with programming languages to interact with code. This paper p","authors":["Connar Hite","Sean Saud","Raef Taha","Nayim Rahman","Tanvir Atahary","Scott Douglass"],"url":"http://arxiv.org/abs/2511.08715v1","arxiv_id":"2511.08715v1","published":"2025-11-11T19:25:44Z"},{"title":"Convergence dynamics of Agent-to-Agent Interactions with Misaligned objectives","abstract":"We develop and analyze a theoretical framework for agent-to-agent interactions in a simplified in-context linear regression setting. In our model, each agent is instantiated as a single-layer transformer with linear self-attention (LSA) trained to implement gradient-descent-like updates on a quadratic regression objective from in-context examples. We then study the coupled dynamics when two such LSA agents alternatel","authors":["Romain Cosentino","Sarath Shekkizhar","Adam Earle"],"url":"http://arxiv.org/abs/2511.08710v3","arxiv_id":"2511.08710v3","published":"2025-11-11T19:18:55Z"},{"title":"FAIRPLAI: A Human-in-the-Loop Approach to Fair and Private Machine Learning","abstract":"As machine learning systems move from theory to practice, they are increasingly tasked with decisions that affect healthcare access, financial opportunities, hiring, and public services. In these contexts, accuracy is only one piece of the puzzle - models must also be fair to different groups, protect individual privacy, and remain accountable to stakeholders. Achieving all three is difficult: differential privacy ca","authors":["David Sanchez","Holly Lopez","Michelle Buraczyk","Anantaa Kotal"],"url":"http://arxiv.org/abs/2511.08702v1","arxiv_id":"2511.08702v1","published":"2025-11-11T19:07:46Z"},{"title":"How Modality Shapes Perception and Reasoning: A Study of Error Propagation in ARC-AGI","abstract":"ARC-AGI and ARC-AGI-2 measure generalization-through-composition on small color-quantized grids, and their prize competitions make progress on these harder held-out tasks a meaningful proxy for systematic generalization. Recent instruction-first systems translate grids into concise natural-language or DSL rules executed in generate-execute-select loops, yet we lack a principled account of how encodings shape model pe","authors":["Bo Wen","Chen Wang","Erhan Bilal"],"url":"http://arxiv.org/abs/2511.15717v1","arxiv_id":"2511.15717v1","published":"2025-11-11T19:06:41Z"},{"title":"MACIE: Multi-Agent Causal Intelligence Explainer for Collective Behavior Understanding","abstract":"As Multi Agent Reinforcement Learning systems are used in safety critical applications. Understanding why agents make decisions and how they achieve collective behavior is crucial. Existing explainable AI methods struggle in multi agent settings. They fail to attribute collective outcomes to individuals, quantify emergent behaviors, or capture complex interactions. We present MACIE Multi Agent Causal Intelligence Exp","authors":["Abraham Itzhak Weinberg"],"url":"http://arxiv.org/abs/2511.15716v1","arxiv_id":"2511.15716v1","published":"2025-11-11T19:04:22Z"},{"title":"Simulating the Visual World with Artificial Intelligence: A Roadmap","abstract":"The landscape of video generation is shifting, from a focus on generating visually appealing clips to building virtual environments that support interaction and maintain physical plausibility. These developments point toward the emergence of video foundation models that function not only as visual generators but also as implicit world models, models that simulate the physical dynamics, agent-environment interactions,","authors":["Jingtong Yue","Ziqi Huang","Zhaoxi Chen","Xintao Wang","Pengfei Wan","Ziwei Liu"],"url":"http://arxiv.org/abs/2511.08585v4","arxiv_id":"2511.08585v4","published":"2025-11-11T18:59:50Z"},{"title":"DeepProofLog: Efficient Proving in Deep Stochastic Logic Programs","abstract":"Neurosymbolic (NeSy) AI aims to combine the strengths of neural architectures and symbolic reasoning to improve the accuracy, interpretability, and generalization capability of AI models. While logic inference on top of subsymbolic modules has been shown to effectively guarantee these properties, this often comes at the cost of reduced scalability, which can severely limit the usability of NeSy models. This paper int","authors":["Ying Jiao","Rodrigo Castellano Ontiveros","Luc De Raedt","Marco Gori","Francesco Giannini","Michelangelo Diligenti"],"url":"http://arxiv.org/abs/2511.08581v2","arxiv_id":"2511.08581v2","published":"2025-11-11T18:58:03Z"}],"history":{"events":[{"year":2008,"text":"After 30 years in power, Maumoon Abdul Gayoom was succeeded by Mohamed Nasheed as president of the Maldives.","url":"https://en.wikipedia.org/wiki/Maumoon_Abdul_Gayoom"},{"year":1999,"text":"The House of Lords Act was given royal assent, removing most hereditary peers from the British House of Lords.","url":"https://en.wikipedia.org/wiki/House_of_Lords_Act_1999"},{"year":1975,"text":"During a constitutional crisis, Governor-General Sir John Kerr (pictured) dismissed Prime Minister Gough Whitlam's government and dissolved the Parliament of Australia for a double-dissolution election.","url":"https://en.wikipedia.org/wiki/1975_Australian_constitutional_crisis"},{"year":1965,"text":"Rhodesia, led by Prime Minister Ian Smith (pictured), unilaterally declared independence from the United Kingdom.","url":"https://en.wikipedia.org/wiki/Rhodesia"},{"year":1960,"text":"A coup attempt by the Army of the Republic of Vietnam against President Ngô Đình Diệm was crushed after he falsely promised reform, allowing loyalists to rescue him.","url":"https://en.wikipedia.org/wiki/1960_South_Vietnamese_coup_attempt"},{"year":1940,"text":"Second World War: The Royal Navy launched the first all-aircraft ship-to-ship naval attack in history against the Italians in the Battle of Taranto.","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1934,"text":"The Shrine of Remembrance (pictured), a memorial to all Australians who have served in war, opened in Melbourne.","url":"https://en.wikipedia.org/wiki/Shrine_of_Remembrance"},{"year":1926,"text":"The plan for the United States Numbered Highway System was approved by the American Association of State Highway Officials.","url":"https://en.wikipedia.org/wiki/United_States_Numbered_Highway_System"},{"year":1920,"text":"In London, the Cenotaph was unveiled and the Unknown Warrior was buried in Westminster Abbey in remembrance of the First World War.","url":"https://en.wikipedia.org/wiki/The_Cenotaph"},{"year":1918,"text":"The armistice between the German Empire and the Allies was signed in a railway carriage in the Forest of Compiègne of France (signatories pictured).","url":"https://en.wikipedia.org/wiki/Armistice_of_11_November_1918"},{"year":1918,"text":"Józef Piłsudski, appointed the commander-in-chief of Polish forces by the Regency Council, was entrusted with the creation of a national government for the newly independent Poland.","url":"https://en.wikipedia.org/wiki/J%C3%B3zef_Pi%C5%82sudski"},{"year":1880,"text":"Australian bushranger and outlaw Ned Kelly was hanged in Melbourne, in spite of sympathizers holding rallies for his reprieve.","url":"https://en.wikipedia.org/wiki/Bushranger"},{"year":1813,"text":"War of 1812: British–Canadian forces repelled an American attack at the Battle of Crysler's Farm, forcing the United States to give up their attempt to capture Montreal.","url":"https://en.wikipedia.org/wiki/War_of_1812"},{"year":1805,"text":"War of the Third Coalition: French, Austrian and Russian units suffered heavy losses at the Battle of Dürenstein.","url":"https://en.wikipedia.org/wiki/War_of_the_Third_Coalition"},{"year":1778,"text":"American Revolutionary War: British forces and their Iroquois allies attacked a fort and the village of Cherry Valley, New York, killing 14 soldiers and 30 civilians.","url":"https://en.wikipedia.org/wiki/American_Revolutionary_War"}],"births":[{"year":2005,"text":"Ben Gannon-Doak, Scottish footballer","url":"https://en.wikipedia.org/wiki/Ben_Gannon-Doak"},{"year":2004,"text":"Oakes Fegley, American actor","url":"https://en.wikipedia.org/wiki/Oakes_Fegley"},{"year":1999,"text":"X González, American activist","url":"https://en.wikipedia.org/wiki/X_Gonz%C3%A1lez"},{"year":1998,"text":"Liudmila Samsonova, Russian tennis player","url":"https://en.wikipedia.org/wiki/Liudmila_Samsonova"},{"year":1996,"text":"Tye Sheridan, American actor and producer","url":"https://en.wikipedia.org/wiki/Tye_Sheridan"},{"year":1995,"text":"Josh Aloiai, New Zealand rugby league player","url":"https://en.wikipedia.org/wiki/Josh_Aloiai"},{"year":1995,"text":"Yuriko Miyazaki, British tennis player","url":"https://en.wikipedia.org/wiki/Lily_Miyazaki"},{"year":1995,"text":"Shin Seung-ho, South Korean actor and model","url":"https://en.wikipedia.org/wiki/Shin_Seung-ho"}],"deaths":[{"year":2024,"text":"Frank Auerbach, German-British painter (born 1931)","url":"https://en.wikipedia.org/wiki/Frank_Auerbach"},{"year":2024,"text":"John Robinson, American football player and coach (born 1935)","url":"https://en.wikipedia.org/wiki/John_Robinson_(American_football)"},{"year":2021,"text":"F. W. de Klerk, South African lawyer and politician, former State President of South Africa, Nobel Prize laureate (born 1936)","url":"https://en.wikipedia.org/wiki/F._W._de_Klerk"},{"year":2017,"text":"Chiquito de la Calzada, Spanish singer, actor and comedian (born 1932)","url":"https://en.wikipedia.org/wiki/Chiquito_de_la_Calzada"},{"year":2016,"text":"Victor Bailey, American singer and bass player (born 1960)","url":"https://en.wikipedia.org/wiki/Victor_Bailey_(musician)"},{"year":2016,"text":"Robert Vaughn, American actor (born 1932)","url":"https://en.wikipedia.org/wiki/Robert_Vaughn"},{"year":2015,"text":"Rita Gross, American theologian and author (born 1943)","url":"https://en.wikipedia.org/wiki/Rita_Gross"},{"year":2015,"text":"Nathaniel Marston, American actor and producer (born 1975)","url":"https://en.wikipedia.org/wiki/Nathaniel_Marston"}]},"sources":[{"id":"attention","name":"Wikipedia most-read","url":"https://api.wikimedia.org","licence":"CC BY-SA 4.0","attribution":"Wikipedia contributors"},{"id":"frontier","name":"Hacker News","url":"https://news.ycombinator.com","licence":"Public API — titles and links, credited","attribution":"Hacker News / Y Combinator"},{"id":"research","name":"arXiv cs.AI","url":"https://arxiv.org","licence":"Open metadata, per arXiv API terms","attribution":"arXiv.org"},{"id":"history","name":"Wikipedia On this day","url":"https://api.wikimedia.org","licence":"CC BY-SA 4.0","attribution":"Wikipedia contributors"}],"licence":"Records are CC BY-SA 4.0, inheriting from Wikipedia. Every item links to its source."}