{"date":"2025-11-05","schema_version":1,"captured_at":"2026-08-25T22:56:04.084Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":15},"attention":[{"title":"Dick Cheney","views":959236,"rank":3,"extract":"Richard Bruce Cheney was an American politician and businessman who served as the 46th vice president of the United States under President George W. Bush from 2001 to 2009. Considered the main architect of the Iraq War, Cheney has been called the most powerful","url":"https://en.wikipedia.org/wiki/Dick_Cheney","thumb":"https://upload.wikimedia.org/wikipedia/commons/thumb/8/88/46_Dick_Cheney_3x4.jpg/330px-46_Dick_Cheney_3x4.jpg?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail"},{"title":"Zohran Mamdani","views":562214,"rank":4,"extract":"Zohran Kwame Mamdani is an American politician who has served since 2026 as the 112th mayor of New York City. 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However, achieving specific objectives with these models often requires costly adaptations such as fine-tuning, which can be resource-intensive and time-consuming. An alternative approach is inference-time control, which involves optimizing the prompt embeddings to guide the generation process without altering the model weig","authors":["Domício Pereira Neto","João Correia","Penousal Machado"],"url":"http://arxiv.org/abs/2511.03913v2","arxiv_id":"2511.03913v2","published":"2025-11-05T23:31:54Z"},{"title":"I Detect What I Don't Know: Incremental Anomaly Learning with Stochastic Weight Averaging-Gaussian for Oracle-Free Medical Imaging","abstract":"Unknown anomaly detection in medical imaging remains a fundamental challenge due to the scarcity of labeled anomalies and the high cost of expert supervision. We introduce an unsupervised, oracle-free framework that incrementally expands a trusted set of normal samples without any anomaly labels. Starting from a small, verified seed of normal images, our method alternates between lightweight adapter updates and uncer","authors":["Nand Kumar Yadav","Rodrigue Rizk","William CW Chen","KC Santosh"],"url":"http://arxiv.org/abs/2511.03912v2","arxiv_id":"2511.03912v2","published":"2025-11-05T23:28:14Z"},{"title":"SnappyMeal: Design and Longitudinal Evaluation of a Multimodal AI Food Logging Application","abstract":"Food logging, both self-directed and prescribed, plays a critical role in uncovering correlations between diet, medical, fitness, and health outcomes. Through conversations with nutritional experts and individuals who practice dietary tracking, we find current logging methods, such as handwritten and app-based journaling, are inflexible and result in low adherence and potentially inaccurate nutritional summaries. The","authors":["Liam Bakar","Zachary Englhardt","Vidya Srinivas","Girish Narayanswamy","Dilini Nissanka","Shwetak Patel"],"url":"http://arxiv.org/abs/2511.03907v1","arxiv_id":"2511.03907v1","published":"2025-11-05T23:14:22Z"},{"title":"Secure Code Generation at Scale with Reflexion","abstract":"Large language models (LLMs) are now widely used to draft and refactor code, but code that works is not necessarily secure. We evaluate secure code generation using the Instruct Prime, which eliminated compliance-required prompts and cue contamination, and evaluate five instruction-tuned code LLMs using a zero-shot baseline and a three-round reflexion prompting approach. Security is measured using the Insecure Code D","authors":["Arup Datta","Ahmed Aljohani","Hyunsook Do"],"url":"http://arxiv.org/abs/2511.03898v1","arxiv_id":"2511.03898v1","published":"2025-11-05T22:46:24Z"},{"title":"Improving Diagnostic Performance on Small and Imbalanced Datasets Using Class-Based Input Image Composition","abstract":"Small, imbalanced datasets and poor input image quality can lead to high false predictions rates with deep learning models. This paper introduces Class-Based Image Composition, an approach that allows us to reformulate training inputs through a fusion of multiple images of the same class into combined visual composites, named Composite Input Images (CoImg). That enhances the intra-class variance and improves the valu","authors":["Hlali Azzeddine","Majid Ben Yakhlef","Soulaiman El Hazzat"],"url":"http://arxiv.org/abs/2511.03891v2","arxiv_id":"2511.03891v2","published":"2025-11-05T22:34:06Z"},{"title":"Evaluating Modern Large Language Models on Low-Resource and Morphologically Rich Languages:A Cross-Lingual Benchmark Across Cantonese, Japanese, and Turkish","abstract":"Large language models (LLMs) have achieved impressive results in high-resource languages like English, yet their effectiveness in low-resource and morphologically rich languages remains underexplored. In this paper, we present a comprehensive evaluation of seven cutting-edge LLMs -- including GPT-4o, GPT-4, Claude~3.5~Sonnet, LLaMA~3.1, Mistral~Large~2, LLaMA-2~Chat~13B, and Mistral~7B~Instruct -- on a new cross-ling","authors":["Chengxuan Xia","Qianye Wu","Hongbin Guan","Sixuan Tian","Yilun Hao","Xiaoyu Wu"],"url":"http://arxiv.org/abs/2511.10664v2","arxiv_id":"2511.10664v2","published":"2025-11-05T22:09:53Z"},{"title":"Investigating Robot Control Policy Learning for Autonomous X-ray-guided Spine Procedures","abstract":"Imitation learning-based robot control policies are enjoying renewed interest in video-based robotics. However, it remains unclear whether this approach applies to X-ray-guided procedures, such as spine instrumentation, with sparse inputs. We examine the feasibility, opportunities and challenges for imitation policy learning in bi-plane-guided cannula insertion. We develop an in silico sandbox for scalable, automated","authors":["Florence Klitzner","Blanca Inigo","Benjamin D. Killeen","Lalithkumar Seenivasan","Michelle Song","Axel Krieger"],"url":"http://arxiv.org/abs/2511.03882v2","arxiv_id":"2511.03882v2","published":"2025-11-05T22:00:48Z"},{"title":"KnowThyself: An Agentic Assistant for LLM Interpretability","abstract":"We develop KnowThyself, an agentic assistant that advances large language model (LLM) interpretability. Existing tools provide useful insights but remain fragmented and code-intensive. KnowThyself consolidates these capabilities into a chat-based interface, where users can upload models, pose natural language questions, and obtain interactive visualizations with guided explanations. At its core, an orchestrator LLM f","authors":["Suraj Prasai","Mengnan Du","Ying Zhang","Fan Yang"],"url":"http://arxiv.org/abs/2511.03878v1","arxiv_id":"2511.03878v1","published":"2025-11-05T21:48:13Z"},{"title":"OMPILOT: Harnessing Transformer Models for Auto Parallelization to Shared Memory Computing Paradigms","abstract":"Recent advances in large language models (LLMs) have significantly accelerated progress in code translation, enabling more accurate and efficient transformation across programming languages. While originally developed for natural language processing, LLMs have shown strong capabilities in modeling programming language syntax and semantics, outperforming traditional rule-based systems in both accuracy and flexibility.","authors":["Arijit Bhattacharjee","Ali TehraniJamsaz","Le Chen","Niranjan Hasabnis","Mihai Capota","Nesreen Ahmed"],"url":"http://arxiv.org/abs/2511.03866v2","arxiv_id":"2511.03866v2","published":"2025-11-05T21:21:15Z"},{"title":"Levers of Power in the Field of AI","abstract":"This paper examines how decision makers in academia, government, business, and civil society navigate questions of power in implementations of artificial intelligence. The study explores how individuals experience and exercise levers of power, which are presented as social mechanisms that shape institutional responses to technological change. The study reports on the responses of personalized questionnaires designed ","authors":["Tammy Mackenzie","Sukriti Punj","Natalie Perez","Sreyoshi Bhaduri","Branislav Radeljic"],"url":"http://arxiv.org/abs/2511.03859v1","arxiv_id":"2511.03859v1","published":"2025-11-05T21:03:57Z"},{"title":"Noise Injection: Improving Out-of-Distribution Generalization for Limited Size Datasets","abstract":"Deep learned (DL) models for image recognition have been shown to fail to generalize to data from different devices, populations, etc. COVID-19 detection from Chest X-rays (CXRs), in particular, has been shown to fail to generalize to out-of-distribution (OOD) data from new clinical sources not covered in the training set. This occurs because models learn to exploit shortcuts - source-specific artifacts that do not t","authors":["Duong Mai","Lawrence Hall"],"url":"http://arxiv.org/abs/2511.03855v2","arxiv_id":"2511.03855v2","published":"2025-11-05T20:53:59Z"},{"title":"To See or To Read: User Behavior Reasoning in Multimodal LLMs","abstract":"Multimodal Large Language Models (MLLMs) are reshaping how modern agentic systems reason over sequential user-behavior data. However, whether textual or image representations of user behavior data are more effective for maximizing MLLM performance remains underexplored. We present \\texttt{BehaviorLens}, a systematic benchmarking framework for assessing modality trade-offs in user-behavior reasoning across six MLLMs b","authors":["Tianning Dong","Luyi Ma","Varun Vasudevan","Jason Cho","Sushant Kumar","Kannan Achan"],"url":"http://arxiv.org/abs/2511.03845v1","arxiv_id":"2511.03845v1","published":"2025-11-05T20:26:40Z"},{"title":"CORE -- A Cell-Level Coarse-to-Fine Image Registration Engine for Multi-stain Image Alignment","abstract":"Accurate and efficient registration of whole slide images (WSIs) is essential for high-resolution, nuclei-level analysis in multi-stained tissue slides. We propose a novel coarse-to-fine framework CORE for accurate nuclei-level registration across diverse multimodal whole-slide image (WSI) datasets. The coarse registration stage leverages prompt-based tissue mask extraction to effectively filter out artefacts and non","authors":["Esha Sadia Nasir","Behnaz Elhaminia","Mark Eastwood","Catherine King","Owen Cain","Lorraine Harper"],"url":"http://arxiv.org/abs/2511.03826v4","arxiv_id":"2511.03826v4","published":"2025-11-05T19:47:41Z"},{"title":"How Different Tokenization Algorithms Impact LLMs and Transformer Models for Binary Code Analysis","abstract":"Tokenization is fundamental in assembly code analysis, impacting intrinsic characteristics like vocabulary size, semantic coverage, and extrinsic performance in downstream tasks. Despite its significance, tokenization in the context of assembly code remains an underexplored area. This study aims to address this gap by evaluating the intrinsic properties of Natural Language Processing (NLP) tokenization models and par","authors":["Ahmed Mostafa","Raisul Arefin Nahid","Samuel Mulder"],"url":"http://arxiv.org/abs/2511.03825v1","arxiv_id":"2511.03825v1","published":"2025-11-05T19:45:26Z"},{"title":"PLLuM: A Family of Polish Large Language Models","abstract":"Large Language Models (LLMs) play a central role in modern artificial intelligence, yet their development has been primarily focused on English, resulting in limited support for other languages. We present PLLuM (Polish Large Language Model), the largest open-source family of foundation models tailored specifically for the Polish language. Developed by a consortium of major Polish research institutions, PLLuM address","authors":["Jan Kocoń","Maciej Piasecki","Arkadiusz Janz","Teddy Ferdinan","Łukasz Radliński","Bartłomiej Koptyra"],"url":"http://arxiv.org/abs/2511.03823v1","arxiv_id":"2511.03823v1","published":"2025-11-05T19:41:49Z"},{"title":"Exploring the Psychometric Validity of AI-Generated Student Responses: A Study on Virtual Personas' Learning Motivation","abstract":"This study explores whether large language models (LLMs) can simulate valid student responses for educational measurement. Using GPT -4o, 2000 virtual student personas were generated. Each persona completed the Academic Motivation Scale (AMS). Factor analyses(EFA and CFA) and clustering showed GPT -4o reproduced the AMS structure and distinct motivational subgroups.","authors":["Huanxiao Wang"],"url":"http://arxiv.org/abs/2511.07451v1","arxiv_id":"2511.07451v1","published":"2025-11-05T19:22:02Z"},{"title":"Optimizing Reasoning Efficiency through Prompt Difficulty Prediction","abstract":"Reasoning language models perform well on complex tasks but are costly to deploy due to their size and long reasoning traces. We propose a routing approach that assigns each problem to the smallest model likely to solve it, reducing compute without sacrificing accuracy. Using intermediate representations from s1.1-32B, we train lightweight predictors of problem difficulty or model correctness to guide routing across ","authors":["Bo Zhao","Berkcan Kapusuzoglu","Kartik Balasubramaniam","Sambit Sahu","Supriyo Chakraborty","Genta Indra Winata"],"url":"http://arxiv.org/abs/2511.03808v1","arxiv_id":"2511.03808v1","published":"2025-11-05T19:14:53Z"},{"title":"EvalCards: A Framework for Standardized Evaluation Reporting","abstract":"Evaluation has long been a central concern in NLP, and transparent reporting practices are more critical than ever in today's landscape of rapidly released open-access models. Drawing on a survey of recent work on evaluation and documentation, we identify three persistent shortcomings in current reporting practices: reproducibility, accessibility, and governance. We argue that existing standardization efforts remain ","authors":["Ruchira Dhar","Danae Sanchez Villegas","Antonia Karamolegkou","Alice Schiavone","Yifei Yuan","Xinyi Chen"],"url":"http://arxiv.org/abs/2511.21695v1","arxiv_id":"2511.21695v1","published":"2025-11-05T19:01:48Z"},{"title":"Expert Evaluation of LLM World Models: A High-$T_c$ Superconductivity Case Study","abstract":"Large Language Models (LLMs) show great promise as a powerful tool for scientific literature exploration. However, their effectiveness in providing scientifically accurate and comprehensive answers to complex questions within specialized domains remains an active area of research. Using the field of high-temperature cuprates as an exemplar, we evaluate the ability of LLM systems to understand the literature at the le","authors":["Haoyu Guo","Maria Tikhanovskaya","Paul Raccuglia","Alexey Vlaskin","Chris Co","Daniel J. Liebling"],"url":"http://arxiv.org/abs/2511.03782v1","arxiv_id":"2511.03782v1","published":"2025-11-05T19:00:01Z"},{"title":"Learning Interestingness in Automated Mathematical Theory Formation","abstract":"We take two key steps in automating the open-ended discovery of new mathematical theories, a grand challenge in artificial intelligence. First, we introduce $\\emph{FERMAT}$, a reinforcement learning (RL) environment that models concept discovery and theorem-proving using a set of symbolic actions, opening up a range of RL problems relevant to theory discovery. Second, we explore a specific problem through $\\emph{FERM","authors":["George Tsoukalas","Rahul Saha","Amitayush Thakur","Sabrina Reguyal","Swarat Chaudhuri"],"url":"http://arxiv.org/abs/2511.14778v1","arxiv_id":"2511.14778v1","published":"2025-11-05T18:59:17Z"},{"title":"Scaling Agent Learning via Experience Synthesis","abstract":"While reinforcement learning (RL) can empower autonomous agents by enabling self-improvement through interaction, its practical adoption remains challenging due to costly rollouts, limited task diversity, unreliable reward signals, and infrastructure complexity, all of which obstruct the collection of scalable experience data. To address these challenges, we introduce DreamGym, the first unified framework designed to","authors":["Zhaorun Chen","Zhuokai Zhao","Kai Zhang","Bo Liu","Qi Qi","Yifan Wu"],"url":"http://arxiv.org/abs/2511.03773v2","arxiv_id":"2511.03773v2","published":"2025-11-05T18:58:48Z"},{"title":"Outbidding and Outbluffing Elite Humans: Mastering Liar's Poker via Self-Play and Reinforcement Learning","abstract":"AI researchers have long focused on poker-like games as a testbed for environments characterized by multi-player dynamics, imperfect information, and reasoning under uncertainty. While recent breakthroughs have matched elite human play at no-limit Texas hold'em, the multi-player dynamics are subdued: most hands converge quickly with only two players engaged through multiple rounds of bidding. In this paper, we presen","authors":["Richard Dewey","Janos Botyanszki","Ciamac C. Moallemi","Andrew T. Zheng"],"url":"http://arxiv.org/abs/2511.03724v3","arxiv_id":"2511.03724v3","published":"2025-11-05T18:58:18Z"},{"title":"Climbing the label tree: Hierarchy-preserving contrastive learning for medical imaging","abstract":"Medical image labels are often organized by taxonomies (e.g., organ - tissue - subtype), yet standard self-supervised learning (SSL) ignores this structure. We present a hierarchy-preserving contrastive framework that makes the label tree a first-class training signal and an evaluation target. Our approach introduces two plug-in objectives: Hierarchy-Weighted Contrastive (HWC), which scales positive/negative pair str","authors":["Alif Elham Khan"],"url":"http://arxiv.org/abs/2511.03771v1","arxiv_id":"2511.03771v1","published":"2025-11-05T18:53:25Z"},{"title":"Grounded Misunderstandings in Asymmetric Dialogue: A Perspectivist Annotation Scheme for MapTask","abstract":"Collaborative dialogue relies on participants incrementally establishing common ground, yet in asymmetric settings they may believe they agree while referring to different entities. We introduce a perspectivist annotation scheme for the HCRC MapTask corpus (Anderson et al., 1991) that separately captures speaker and addressee grounded interpretations for each reference expression, enabling us to trace how understandi","authors":["Nan Li","Albert Gatt","Massimo Poesio"],"url":"http://arxiv.org/abs/2511.03718v2","arxiv_id":"2511.03718v2","published":"2025-11-05T18:52:28Z"},{"title":"The Illusion of Procedural Reasoning: Measuring Long-Horizon FSM Execution in LLMs","abstract":"Large language models (LLMs) have achieved remarkable results on tasks framed as reasoning problems, yet their true ability to perform procedural reasoning, executing multi-step, rule-based computations remains unclear. Unlike algorithmic systems, which can deterministically execute long-horizon symbolic procedures, LLMs often degrade under extended reasoning chains, but there is no controlled, interpretable benchmar","authors":["Mahdi Samiei","Mahdi Mansouri","Mahdieh Soleymani Baghshah"],"url":"http://arxiv.org/abs/2511.14777v1","arxiv_id":"2511.14777v1","published":"2025-11-05T18:44:47Z"}],"history":{"events":[{"year":2013,"text":"The Indian Space Research Organisation launched the Mars Orbiter Mission, India's first interplanetary probe.","url":"https://en.wikipedia.org/wiki/ISRO"},{"year":2009,"text":"U.S. Army major Nidal Hasan went on a shooting rampage at Fort Hood, Texas, the worst shooting ever to take place on an American military base, killing 13.","url":"https://en.wikipedia.org/wiki/United_States_Army"},{"year":2003,"text":"American serial killer Gary Ridgway pleaded guilty to 48 counts of first-degree murder.","url":"https://en.wikipedia.org/wiki/Gary_Ridgway"},{"year":1995,"text":"Aline Chrétien (pictured) thwarted André Dallaire's attempt to assassinate her husband, Canadian prime minister Jean Chrétien, by locking the bedroom door in 24 Sussex Drive, their official residence in Ottawa.","url":"https://en.wikipedia.org/wiki/Aline_Chr%C3%A9tien"},{"year":1990,"text":"Israeli ultra-nationalist rabbi Meir Kahane (pictured) was assassinated in a New York City hotel by an Arab gunman.","url":"https://en.wikipedia.org/wiki/Ultranationalism"},{"year":1952,"text":"An earthquake struck the Kamchatka Peninsula, triggering a major tsunami that affected the Kuril Islands and other parts of the Pacific Ocean.","url":"https://en.wikipedia.org/wiki/1952_Severo-Kurilsk_earthquake"},{"year":1950,"text":"Korean War: The 27th British Commonwealth Brigade succeeded in preventing a Chinese breakthrough at the Battle of Pakchon.","url":"https://en.wikipedia.org/wiki/Korean_War"},{"year":1944,"text":"World War II: Allied forces began a military campaign on Japanese-occupied Singapore.","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1943,"text":"World War II: An unknown aircraft dropped four bombs on Vatican City, which maintained neutrality during the war.","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1916,"text":"An armed confrontation in Everett, Washington, between local authorities and members of the Industrial Workers of the World resulted in seven deaths.","url":"https://en.wikipedia.org/wiki/Everett_massacre"},{"year":1854,"text":"Crimean War: Despite being severely outnumbered, and fighting in heavy foggy conditions, the allied armies of the United Kingdom and France defeated the Russians in present-day Inkerman, Ukraine.","url":"https://en.wikipedia.org/wiki/Crimean_War"},{"year":1757,"text":"Seven Years' War: Prussian forces led by Frederick the Great defeated the allied French and Habsburg armies at the Battle of Rossbach.","url":"https://en.wikipedia.org/wiki/Seven_Years'_War"},{"year":1605,"text":"The arrest of Guy Fawkes, found during a search of the Palace of Westminster, foiled the Gunpowder Plot, which planned to blow up the House of Lords.","url":"https://en.wikipedia.org/wiki/Guy_Fawkes"},{"year":1556,"text":"At the Second Battle of Panipat, forces of the Mughal emperor Akbar captured Hemu, the Hindu emperor of north India.","url":"https://en.wikipedia.org/wiki/Second_Battle_of_Panipat"},{"year":1138,"text":"Lý Anh Tông was enthroned as the emperor of Đại Việt at the age of two, beginning a 37-year reign.","url":"https://en.wikipedia.org/wiki/L%C3%BD_Anh_T%C3%B4ng"}],"births":[{"year":2002,"text":"Matty Beniers, American ice hockey player","url":"https://en.wikipedia.org/wiki/Matty_Beniers"},{"year":1998,"text":"Takehiro Tomiyasu, Japanese footballer","url":"https://en.wikipedia.org/wiki/Takehiro_Tomiyasu"},{"year":1995,"text":"Trey Lyles, Canadian basketball player","url":"https://en.wikipedia.org/wiki/Trey_Lyles"},{"year":1994,"text":"Astou Ndour-Fall, Senegalese-Spanish basketball player","url":"https://en.wikipedia.org/wiki/Astou_Ndour-Fall"},{"year":1992,"text":"Odell Beckham Jr., American football player","url":"https://en.wikipedia.org/wiki/Odell_Beckham_Jr."},{"year":1992,"text":"Marco Verratti, Italian footballer","url":"https://en.wikipedia.org/wiki/Marco_Verratti"},{"year":1991,"text":"Flume, Australian DJ and producer","url":"https://en.wikipedia.org/wiki/Flume_(musician)"},{"year":1991,"text":"Jon Gray, American baseball player","url":"https://en.wikipedia.org/wiki/Jon_Gray"}],"deaths":[{"year":2024,"text":"Ben Baldanza, American economist and business executive (born 1961)","url":"https://en.wikipedia.org/wiki/Ben_Baldanza"},{"year":2024,"text":"Elwood Edwards, American voice actor (born 1949)","url":"https://en.wikipedia.org/wiki/Elwood_Edwards"},{"year":2023,"text":"Pat E. Johnson, American martial artist and actor (born 1939)","url":"https://en.wikipedia.org/wiki/Pat_E._Johnson"},{"year":2022,"text":"Aaron Carter, American singer-songwriter, rapper, dancer and actor (born 1987)","url":"https://en.wikipedia.org/wiki/Aaron_Carter"},{"year":2021,"text":"Marília Mendonça, Brazilian singer (born 1995)","url":"https://en.wikipedia.org/wiki/Mar%C3%ADlia_Mendon%C3%A7a"},{"year":2020,"text":"Geoffrey Palmer, English actor (born 1927)","url":"https://en.wikipedia.org/wiki/Geoffrey_Palmer_(actor)"},{"year":2015,"text":"George Barris, American engineer and car designer (born 1925)","url":"https://en.wikipedia.org/wiki/George_Barris_(auto_customizer)"},{"year":2015,"text":"Nora Brockstedt, Norwegian singer (born 1923)","url":"https://en.wikipedia.org/wiki/Nora_Brockstedt"}]},"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."}