{"date":"2025-11-10","schema_version":1,"captured_at":"2026-08-25T22:55:48.432Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":16},"attention":[{"title":"Frankenstein (2025 film)","views":373070,"rank":4,"extract":"Frankenstein is a 2025 American Gothic science fiction horror film written, co-produced, and directed by Guillermo del Toro, based on the 1818 novel by Mary Shelley. The film stars Oscar Isaac as Victor Frankenstein and Jacob Elordi as the Creature, with Mia G","url":"https://en.wikipedia.org/wiki/Frankenstein_(2025_film)","thumb":"https://upload.wikimedia.org/wikipedia/en/9/94/Frankenstein_2025_film_poster.jpg?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail_unscaled"},{"title":"Google Chrome","views":308032,"rank":5,"extract":"Google Chrome is a cross-platform web browser developed by Google. 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This is especially a concern in vision-based environments where minor manipulations of high-dimensional image inputs can easily mislead the agent's behavior. To this end, various defenses have been proposed recently, with state-of-the-art approaches achieving robust performance even u","authors":["Xiaolin Sun","Feidi Liu","Zhengming Ding","ZiZhan Zheng"],"url":"http://arxiv.org/abs/2511.07701v1","arxiv_id":"2511.07701v1","published":"2025-11-10T23:52:21Z"},{"title":"CAPO: Confidence Aware Preference Optimization Learning for Multilingual Preferences","abstract":"Preference optimization is a critical post-training technique used to align large language models (LLMs) with human preferences, typically by fine-tuning on ranked response pairs. While methods like Direct Preference Optimization (DPO) have proven effective in English, they often fail to generalize robustly to multilingual settings. We propose a simple yet effective alternative, Confidence-Aware Preference Optimizati","authors":["Rhitabrat Pokharel","Yufei Tao","Ameeta Agrawal"],"url":"http://arxiv.org/abs/2511.07691v1","arxiv_id":"2511.07691v1","published":"2025-11-10T23:28:12Z"},{"title":"Towards AI-Assisted Generation of Military Training Scenarios","abstract":"Achieving expert-level performance in simulation-based training relies on the creation of complex, adaptable scenarios, a traditionally laborious and resource intensive process. Although prior research explored scenario generation for military training, pre-LLM AI tools struggled to generate sufficiently complex or adaptable scenarios. This paper introduces a multi-agent, multi-modal reasoning framework that leverage","authors":["Soham Hans","Volkan Ustun","Benjamin Nye","James Sterrett","Matthew Green"],"url":"http://arxiv.org/abs/2511.07690v1","arxiv_id":"2511.07690v1","published":"2025-11-10T23:24:35Z"},{"title":"Stress Testing Factual Consistency Metrics for Long-Document Summarization","abstract":"Evaluating the factual consistency of abstractive text summarization remains a significant challenge, particularly for long documents, where conventional metrics struggle with input length limitations and long-range dependencies. In this work, we systematically evaluate the reliability of six widely used reference-free factuality metrics, originally proposed for short-form summarization, in the long-document setting.","authors":["Zain Muhammad Mujahid","Dustin Wright","Isabelle Augenstein"],"url":"http://arxiv.org/abs/2511.07689v2","arxiv_id":"2511.07689v2","published":"2025-11-10T23:24:25Z"},{"title":"ResearchRubrics: A Benchmark of Prompts and Rubrics For Evaluating Deep Research Agents","abstract":"Deep Research (DR) is an emerging agent application that leverages large language models (LLMs) to address open-ended queries. It requires the integration of several capabilities, including multi-step reasoning, cross-document synthesis, and the generation of evidence-backed, long-form answers. Evaluating DR remains challenging because responses are lengthy and diverse, admit many valid solutions, and often depend on","authors":["Manasi Sharma","Chen Bo Calvin Zhang","Chaithanya Bandi","Clinton Wang","Ankit Aich","Huy Nghiem"],"url":"http://arxiv.org/abs/2511.07685v1","arxiv_id":"2511.07685v1","published":"2025-11-10T23:07:14Z"},{"title":"Designing and Evaluating Malinowski's Lens: An AI-Native Educational Game for Ethnographic Learning","abstract":"This study introduces 'Malinowski's Lens', the first AI-native educational game for anthropology that transforms Bronislaw Malinowski's 'Argonauts of the Western Pacific' (1922) into an interactive learning experience. The system combines Retrieval-Augmented Generation with DALL-E 3 text-to-image generation, creating consistent VGA-style visuals as players embody Malinowski during his Trobriand Islands fieldwork (191","authors":["Michael Hoffmann","Jophin John","Jan Fillies","Adrian Paschke"],"url":"http://arxiv.org/abs/2511.07682v1","arxiv_id":"2511.07682v1","published":"2025-11-10T23:03:01Z"},{"title":"AIA Forecaster: Technical Report","abstract":"This technical report describes the AIA Forecaster, a Large Language Model (LLM)-based system for judgmental forecasting using unstructured data. The AIA Forecaster approach combines three core elements: agentic search over high-quality news sources, a supervisor agent that reconciles disparate forecasts for the same event, and a set of statistical calibration techniques to counter behavioral biases in large language","authors":["Rohan Alur","Bradly C. Stadie","Daniel Kang","Ryan Chen","Matt McManus","Michael Rickert"],"url":"http://arxiv.org/abs/2511.07678v1","arxiv_id":"2511.07678v1","published":"2025-11-10T22:45:07Z"},{"title":"Speech Separation for Hearing-Impaired Children in the Classroom","abstract":"Classroom environments are particularly challenging for children with hearing impairments, where background noise, multiple talkers, and reverberation degrade speech perception. These difficulties are greater for children than adults, yet most deep learning speech separation models for assistive devices are developed using adult voices in simplified, low-reverberation conditions. This overlooks both the higher spectr","authors":["Feyisayo Olalere","Kiki van der Heijden","H. Christiaan Stronks","Jeroen Briaire","Johan H. M. Frijns","Yagmur Güçlütürk"],"url":"http://arxiv.org/abs/2511.07677v1","arxiv_id":"2511.07677v1","published":"2025-11-10T22:44:28Z"},{"title":"A survey: Information search time optimization based on RAG (Retrieval Augmentation Generation) chatbot","abstract":"Retrieval-Augmented Generation (RAG) based chatbots are not only useful for information retrieval through questionanswering but also for making complex decisions based on injected private data.we present a survey on how much search time can be saved when retrieving complex information within an organization called \"X Systems\"(a stealth mode company) by using a RAG-based chatbot compared to traditional search methods.","authors":["Jinesh Patel","Arpit Malhotra","Ajay Pande","Prateek Caire"],"url":"http://arxiv.org/abs/2601.07838v1","arxiv_id":"2601.07838v1","published":"2025-11-10T22:39:26Z"},{"title":"Making LLMs Reliable When It Matters Most: A Five-Layer Architecture for High-Stakes Decisions","abstract":"Current large language models (LLMs) excel in verifiable domains where outputs can be checked before action but prove less reliable for high-stakes strategic decisions with uncertain outcomes. This gap, driven by mutually reinforcing cognitive biases in both humans and artificial intelligence (AI) systems, threatens the defensibility of valuations and sustainability of investments in the sector. This report describes","authors":["Alejandro R. Jadad"],"url":"http://arxiv.org/abs/2511.07669v1","arxiv_id":"2511.07669v1","published":"2025-11-10T22:24:21Z"},{"title":"AI-Driven Contribution Evaluation and Conflict Resolution: A Framework & Design for Group Workload Investigation","abstract":"The equitable assessment of individual contribution in teams remains a persistent challenge, where conflict and disparity in workload can result in unfair performance evaluation, often requiring manual intervention - a costly and challenging process. We survey existing tool features and identify a gap in conflict resolution methods and AI integration. To address this, we propose a framework and implementation design ","authors":["Jakub Slapek","Mir Seyedebrahimi","Jianhua Yang"],"url":"http://arxiv.org/abs/2511.07667v2","arxiv_id":"2511.07667v2","published":"2025-11-10T22:22:55Z"},{"title":"FractalCloud: A Fractal-Inspired Architecture for Efficient Large-Scale Point Cloud Processing","abstract":"Three-dimensional (3D) point clouds are increasingly used in applications such as autonomous driving, robotics, and virtual reality (VR). Point-based neural networks (PNNs) have demonstrated strong performance in point cloud analysis, originally targeting small-scale inputs. However, as PNNs evolve to process large-scale point clouds with hundreds of thousands of points, all-to-all computation and global memory acces","authors":["Yuzhe Fu","Changchun Zhou","Hancheng Ye","Bowen Duan","Qiyu Huang","Chiyue Wei"],"url":"http://arxiv.org/abs/2511.07665v2","arxiv_id":"2511.07665v2","published":"2025-11-10T22:19:37Z"},{"title":"Cortex AISQL: A Production SQL Engine for Unstructured Data","abstract":"Snowflake's Cortex AISQL is a production SQL engine that integrates native semantic operations directly into SQL. This integration allows users to write declarative queries that combine relational operations with semantic reasoning, enabling them to query both structured and unstructured data effortlessly. However, making semantic operations efficient at production scale poses fundamental challenges. Semantic operati","authors":["Paweł Liskowski","Benjamin Han","Paritosh Aggarwal","Bowei Chen","Boxin Jiang","Nitish Jindal"],"url":"http://arxiv.org/abs/2511.07663v3","arxiv_id":"2511.07663v3","published":"2025-11-10T22:14:13Z"},{"title":"Revisiting NLI: Towards Cost-Effective and Human-Aligned Metrics for Evaluating LLMs in Question Answering","abstract":"Evaluating answers from state-of-the-art large language models (LLMs) is challenging: lexical metrics miss semantic nuances, whereas \"LLM-as-Judge\" scoring is computationally expensive. We re-evaluate a lightweight alternative -- off-the-shelf Natural Language Inference (NLI) scoring augmented by a simple lexical-match flag and find that this decades-old technique matches GPT-4o's accuracy (89.9%) on long-form QA, wh","authors":["Sai Shridhar Balamurali","Lu Cheng"],"url":"http://arxiv.org/abs/2511.07659v1","arxiv_id":"2511.07659v1","published":"2025-11-10T22:10:02Z"},{"title":"Adaptive Graph Learning with Transformer for Multi-Reservoir Inflow Prediction","abstract":"Reservoir inflow prediction is crucial for water resource management, yet existing approaches mainly focus on single-reservoir models that ignore spatial dependencies among interconnected reservoirs. We introduce AdaTrip as an adaptive, time-varying graph learning framework for multi-reservoir inflow forecasting. AdaTrip constructs dynamic graphs where reservoirs are nodes with directed edges reflecting hydrological ","authors":["Pengfei Hu","Ming Fan","Xiaoxue Han","Chang Lu","Wei Zhang","Hyun Kang"],"url":"http://arxiv.org/abs/2511.07649v1","arxiv_id":"2511.07649v1","published":"2025-11-10T21:53:32Z"},{"title":"A Self-Improving Architecture for Dynamic Safety in Large Language Models","abstract":"Context: Large Language Models (LLMs) rely on static, pre-deployment safety mechanisms that cannot adapt to adversarial threats discovered after release. Objective: To design a software architecture enabling LLM-based systems to autonomously detect safety failures and synthesize defense policies at runtime, without retraining or manual intervention. Method: We propose the Self-Improving Safety Framework (SISF), groun","authors":["Tyler Slater"],"url":"http://arxiv.org/abs/2511.07645v2","arxiv_id":"2511.07645v2","published":"2025-11-10T21:39:40Z"},{"title":"Private-RAG: Answering Multiple Queries with LLMs while Keeping Your Data Private","abstract":"Retrieval-augmented generation (RAG) enhances large language models (LLMs) by retrieving documents from an external corpus at inference time. When this corpus contains sensitive information, however, unprotected RAG systems are at risk of leaking private information. Prior work has introduced differential privacy (DP) guarantees for RAG, but only in single-query settings, which fall short of realistic usage. In this ","authors":["Ruihan Wu","Erchi Wang","Zhiyuan Zhang","Yu-Xiang Wang"],"url":"http://arxiv.org/abs/2511.07637v1","arxiv_id":"2511.07637v1","published":"2025-11-10T21:12:32Z"},{"title":"Partial Action Replacement: Tackling Distribution Shift in Offline MARL","abstract":"Offline multi-agent reinforcement learning (MARL) is severely hampered by the challenge of evaluating out-of-distribution (OOD) joint actions. Our core finding is that when the behavior policy is factorized - a common scenario where agents act fully or partially independently during data collection - a strategy of partial action replacement (PAR) can significantly mitigate this challenge. PAR updates a single or part","authors":["Yue Jin","Giovanni Montana"],"url":"http://arxiv.org/abs/2511.07629v1","arxiv_id":"2511.07629v1","published":"2025-11-10T20:56:58Z"},{"title":"One Router to Route Them All: Homogeneous Expert Routing for Heterogeneous Graph Transformers","abstract":"A common practice in heterogeneous graph neural networks (HGNNs) is to condition parameters on node/edge types, assuming types reflect semantic roles. However, this can cause overreliance on surface-level labels and impede cross-type knowledge transfer. We explore integrating Mixture-of-Experts (MoE) into HGNNs--a direction underexplored despite MoE's success in homogeneous settings. Crucially, we question the need f","authors":["Georgiy Shakirov","Albert Arakelov"],"url":"http://arxiv.org/abs/2511.07603v2","arxiv_id":"2511.07603v2","published":"2025-11-10T20:20:58Z"},{"title":"Leveraging the Power of AI and Social Interactions to Restore Trust in Public Polls","abstract":"The emergence of crowdsourced data has significantly reshaped social science, enabling extensive exploration of collective human actions, viewpoints, and societal dynamics. However, ensuring safe, fair, and reliable participation remains a persistent challenge. Traditional polling methods have seen a notable decline in engagement over recent decades, raising concerns about the credibility of collected data. Meanwhile","authors":["Amr Akmal Abouelmagd","Amr Hilal"],"url":"http://arxiv.org/abs/2511.07593v1","arxiv_id":"2511.07593v1","published":"2025-11-10T20:06:32Z"},{"title":"Beyond Fact Retrieval: Episodic Memory for RAG with Generative Semantic Workspaces","abstract":"Large Language Models (LLMs) face fundamental challenges in long-context reasoning: many documents exceed their finite context windows, while performance on texts that do fit degrades with sequence length, necessitating their augmentation with external memory frameworks. Current solutions, which have evolved from retrieval using semantic embeddings to more sophisticated structured knowledge graphs representations for","authors":["Shreyas Rajesh","Pavan Holur","Chenda Duan","David Chong","Vwani Roychowdhury"],"url":"http://arxiv.org/abs/2511.07587v2","arxiv_id":"2511.07587v2","published":"2025-11-10T19:59:34Z"},{"title":"LLM Output Drift: Cross-Provider Validation & Mitigation for Financial Workflows","abstract":"Financial institutions deploy Large Language Models (LLMs) for reconciliations, regulatory reporting, and client communications, but nondeterministic outputs (output drift) undermine auditability and trust. We quantify drift across five model architectures (7B-120B parameters) on regulated financial tasks, revealing a stark inverse relationship: smaller models (Granite-3-8B, Qwen2.5-7B) achieve 100% output consistenc","authors":["Raffi Khatchadourian","Rolando Franco"],"url":"http://arxiv.org/abs/2511.07585v1","arxiv_id":"2511.07585v1","published":"2025-11-10T19:54:00Z"},{"title":"SemanticForge: Repository-Level Code Generation through Semantic Knowledge Graphs and Constraint Satisfaction","abstract":"Large language models (LLMs) have transformed software development by enabling automated code generation, yet they frequently suffer from systematic errors that limit practical deployment. We identify two critical failure modes: \\textit{logical hallucination} (incorrect control/data-flow reasoning) and \\textit{schematic hallucination} (type mismatches, signature violations, and architectural inconsistencies). These e","authors":["Wuyang Zhang","Chenkai Zhang","Zhen Luo","Jianming Ma","Wangming Yuan","Chuqiao Gu"],"url":"http://arxiv.org/abs/2511.07584v1","arxiv_id":"2511.07584v1","published":"2025-11-10T19:53:23Z"},{"title":"Think Before You Retrieve: Learning Test-Time Adaptive Search with Small Language Models","abstract":"Effective information retrieval requires reasoning over partial evidence and refining strategies as information emerges. Yet current approaches fall short: neural retrievers lack reasoning capabilities, large language models (LLMs) provide semantic depth but at prohibitive cost, and query rewriting or decomposition limits improvement to static transformations. As a result, existing methods fail to capture the iterati","authors":["Supriti Vijay","Aman Priyanshu","Anu Vellore","Baturay Saglam","Amin Karbasi"],"url":"http://arxiv.org/abs/2511.07581v1","arxiv_id":"2511.07581v1","published":"2025-11-10T19:49:55Z"},{"title":"Procedural Knowledge Improves Agentic LLM Workflows","abstract":"Large language models (LLMs) often struggle when performing agentic tasks without substantial tool support, prom-pt engineering, or fine tuning. Despite research showing that domain-dependent, procedural knowledge can dramatically increase planning efficiency, little work evaluates its potential for improving LLM performance on agentic tasks that may require implicit planning. We formalize, implement, and evaluate an","authors":["Vincent Hsiao","Mark Roberts","Leslie Smith"],"url":"http://arxiv.org/abs/2511.07568v1","arxiv_id":"2511.07568v1","published":"2025-11-10T19:27:57Z"}],"history":{"events":[{"year":2020,"text":"The British government announced that it had removed the last land mine from the Falkland Islands, laid by Argentine forces during the 1982 Falklands War.","url":"https://en.wikipedia.org/wiki/Land_mines_in_the_Falkland_Islands"},{"year":2009,"text":"A skirmish occurred between South Korean and North Korean naval ships off Daecheong Island in the Yellow Sea.","url":"https://en.wikipedia.org/wiki/Daecheong_incident"},{"year":2007,"text":"At the Ibero-American Summit in Santiago, Chile, King Juan Carlos I of Spain asked Venezuelan president Hugo Chávez \"Why don't you shut up?\" after Chávez repeatedly interrupted a speech by Spanish prime minister José Luis Rodríguez Zapatero.","url":"https://en.wikipedia.org/wiki/Ibero-American_Summit"},{"year":2006,"text":"Nadarajah Raviraj, a prominent Sri Lankan Tamil politician and human rights lawyer, was assassinated in Colombo.","url":"https://en.wikipedia.org/wiki/Nadarajah_Raviraj"},{"year":1995,"text":"Writer and environmental activist Ken Saro-Wiwa and eight others from the Movement for the Survival of the Ogoni People were executed by the Nigerian military regime led by Sani Abacha.","url":"https://en.wikipedia.org/wiki/Ken_Saro-Wiwa"},{"year":1975,"text":"In Angola, the MPLA decisively defeated the FNLA in the Battle of Quifangondo, while Portugal simultaneously withdrew all its colonial and military personnel from Luanda.","url":"https://en.wikipedia.org/wiki/MPLA"},{"year":1975,"text":"SS Edmund Fitzgerald sank in Lake Superior, claiming all 29 of her crew's lives.","url":"https://en.wikipedia.org/wiki/SS_Edmund_Fitzgerald"},{"year":1969,"text":"The children's television series Sesame Street premiered in the United States.","url":"https://en.wikipedia.org/wiki/Sesame_Street"},{"year":1945,"text":"Indonesian National Revolution: Following the killing of Brigadier A. W. S. Mallaby on 30 October, British forces retaliated by attacking Surabaya (present-day logo depicted).","url":"https://en.wikipedia.org/wiki/Indonesian_National_Revolution"},{"year":1940,"text":"An earthquake registering 7.7 Mw struck the Vrancea region of Romania.","url":"https://en.wikipedia.org/wiki/1940_Vrancea_earthquake"},{"year":1937,"text":"Brazilian president Getúlio Vargas led a coup against his own constitutional government, establishing the dictatorial Estado Novo regime.","url":"https://en.wikipedia.org/wiki/Get%C3%BAlio_Vargas"},{"year":1898,"text":"White supremacists seized power and massacred black Americans during the Wilmington massacre,(newspaper headline depicted) the only instance of a municipal government being overthrown in United States history.","url":"https://en.wikipedia.org/wiki/White_supremacy"},{"year":1871,"text":"Journalist and explorer Henry Morton Stanley (pictured) located missing missionary and explorer David Livingstone near Lake Tanganyika in present-day Tanzania.","url":"https://en.wikipedia.org/wiki/Henry_Morton_Stanley"},{"year":1865,"text":"Henry Wirz, the Confederate superintendent of Andersonville Prison, was hanged after a controversial conviction, becoming the only American Civil War officer executed for war crimes.","url":"https://en.wikipedia.org/wiki/Henry_Wirz"},{"year":1599,"text":"At the culmination of a Swedish civil war, supporters of the deposed King Sigismund III Vasa were publicly executed in the Åbo Bloodbath.","url":"https://en.wikipedia.org/wiki/Sigismund_III_Vasa"},{"year":1202,"text":"Fourth Crusade: The Siege of Zara, the first attack on a Catholic city by Catholic crusaders, began in present-day Zadar, Croatia.","url":"https://en.wikipedia.org/wiki/Fourth_Crusade"}],"births":[{"year":2009,"text":"Christian Convery, Canadian actor","url":"https://en.wikipedia.org/wiki/Christian_Convery"},{"year":2006,"text":"Hong Eunchae, South Korean singer","url":"https://en.wikipedia.org/wiki/Hong_Eunchae"},{"year":2003,"text":"Luca Del Bel Belluz, Canadian ice hockey player","url":"https://en.wikipedia.org/wiki/Luca_Del_Bel_Belluz"},{"year":2002,"text":"Eduardo Camavinga, French footballer","url":"https://en.wikipedia.org/wiki/Eduardo_Camavinga"},{"year":2000,"text":"Mackenzie Foy, American actress and model","url":"https://en.wikipedia.org/wiki/Mackenzie_Foy"},{"year":2000,"text":"Scotty Pippen Jr., American basketball player","url":"https://en.wikipedia.org/wiki/Scotty_Pippen_Jr."},{"year":2000,"text":"Oliver Sonne, Danish-Peruvian footballer","url":"https://en.wikipedia.org/wiki/Oliver_Sonne"},{"year":1999,"text":"Armand Duplantis, Swedish-American pole vaulter","url":"https://en.wikipedia.org/wiki/Armand_Duplantis"}],"deaths":[{"year":2024,"text":"Tim Sullivan, American novelist (born 1948)","url":"https://en.wikipedia.org/wiki/Tim_Sullivan_(writer)"},{"year":2022,"text":"Kevin Conroy, American actor and voice actor, longtime voice of Batman (born 1955)","url":"https://en.wikipedia.org/wiki/Kevin_Conroy"},{"year":2021,"text":"Miroslav Žbirka, Slovak singer, songwriter and guitarist (born 1952)","url":"https://en.wikipedia.org/wiki/Miroslav_%C5%BDbirka"},{"year":2020,"text":"Saeb Erekat, Chief Palestinian negotiator (born 1955)","url":"https://en.wikipedia.org/wiki/Saeb_Erekat"},{"year":2015,"text":"Gene Amdahl, American computer scientist, physicist, and engineer, founded the Amdahl Corporation (born 1922)","url":"https://en.wikipedia.org/wiki/Gene_Amdahl"},{"year":2015,"text":"Pat Eddery, Irish jockey and trainer (born 1952)","url":"https://en.wikipedia.org/wiki/Pat_Eddery"},{"year":2015,"text":"André Glucksmann, French philosopher and author (born 1937)","url":"https://en.wikipedia.org/wiki/Andr%C3%A9_Glucksmann"},{"year":2015,"text":"Helmut Schmidt, German soldier, economist, and politician, 5th Chancellor of Germany (born 1918)","url":"https://en.wikipedia.org/wiki/Helmut_Schmidt"}]},"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."}