{"date":"2025-11-18","schema_version":1,"captured_at":"2026-08-25T22:56:22.163Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":16},"attention":[{"title":"Google Chrome","views":326436,"rank":3,"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. 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homelessness to porting Doom (2022)","points":244,"comments":42,"url":"https://corecursive.com/doomed-to-fail-with-burger-becky/","discussion":"https://news.ycombinator.com/item?id=45973573"}],"research":[{"title":"Logit-Based Losses Limit the Effectiveness of Feature Knowledge Distillation","abstract":"Knowledge distillation (KD) methods can transfer knowledge of a parameter-heavy teacher model to a light-weight student model. The status quo for feature KD methods is to utilize loss functions based on logits (i.e., pre-softmax class scores) and intermediate layer features (i.e., latent representations). Unlike previous approaches, we propose a feature KD framework for training the student's backbone using feature-b","authors":["Nicholas Cooper","Lijun Chen","Sailesh Dwivedy","Danna Gurari"],"url":"http://arxiv.org/abs/2511.14981v1","arxiv_id":"2511.14981v1","published":"2025-11-18T23:50:31Z"},{"title":"SVBRD-LLM: Self-Verifying Behavioral Rule Discovery for Autonomous Vehicle Identification","abstract":"As autonomous vehicles (AVs) are increasingly deployed on public roads, understanding their real-world behaviors is critical for traffic safety analysis and regulatory oversight. However, many data-driven methods lack interpretability and cannot provide verifiable explanations of AV behavior in mixed traffic. This paper proposes SVBRD-LLM, a self-verifying behavioral rule discovery framework that automatically extrac","authors":["Xiangyu Li","Tianyi Wang","Junfeng Jiao","Christian Claudel","Zhaomiao Guo"],"url":"http://arxiv.org/abs/2511.14977v3","arxiv_id":"2511.14977v3","published":"2025-11-18T23:45:30Z"},{"title":"Harmful Traits of AI Companions","abstract":"Amid the growing prevalence of human-AI interaction, large language models and other AI-based entities increasingly provide forms of companionship to human users. Such AI companionship -- i.e., bonded relationships between humans and AI systems that resemble the relationships people have with family members, friends, and romantic partners -- might substantially benefit humans. Yet such relationships can also do profo","authors":["W. Bradley Knox","Katie Bradford","Samanta Varela Castro","Desmond C. Ong","Sean Williams","Jacob Romanow"],"url":"http://arxiv.org/abs/2511.14972v2","arxiv_id":"2511.14972v2","published":"2025-11-18T23:39:06Z"},{"title":"EGSA-PT:Edge-Guided Spatial Attention with Progressive Training for Monocular Depth Estimation and Segmentation of Transparent Objects","abstract":"Transparent object perception remains a major challenge in computer vision research, as transparency confounds both depth estimation and semantic segmentation. Recent work has explored multi-task learning frameworks to improve robustness, yet negative cross-task interactions often hinder performance. In this work, we introduce Edge-Guided Spatial Attention (EGSA), a fusion mechanism designed to mitigate destructive i","authors":["Gbenga Omotara","Ramy Farag","Seyed Mohamad Ali Tousi","G. N. DeSouza"],"url":"http://arxiv.org/abs/2511.14970v1","arxiv_id":"2511.14970v1","published":"2025-11-18T23:29:20Z"},{"title":"Quality-Controlled Multimodal Emotion Recognition in Conversations with Identity-Based Transfer Learning and MAMBA Fusion","abstract":"This paper addresses data quality issues in multimodal emotion recognition in conversation (MERC) through systematic quality control and multi-stage transfer learning. We implement a quality control pipeline for MELD and IEMOCAP datasets that validates speaker identity, audio-text alignment, and face detection. We leverage transfer learning from speaker and face recognition, assuming that identity-discriminative embe","authors":["Zanxu Wang","Homayoon Beigi"],"url":"http://arxiv.org/abs/2511.14969v1","arxiv_id":"2511.14969v1","published":"2025-11-18T23:24:27Z"},{"title":"MermaidSeqBench: An Evaluation Benchmark for NL-to-Mermaid Sequence Diagram Generation","abstract":"Large language models (LLMs) have shown great promise in generating structured diagrams from natural language descriptions, particularly Mermaid sequence diagrams for software engineering. However, the lack of existing benchmarks to assess the LLM's correctness on this task hinders rigorous, systematic evaluation and principled comparison of model capabilities on this task. To address this shortcoming, we introduce M","authors":["Basel Shbita","Farhan Ahmed","Chad DeLuca"],"url":"http://arxiv.org/abs/2511.14967v3","arxiv_id":"2511.14967v3","published":"2025-11-18T23:14:44Z"},{"title":"How Should the Law Treat Future AI Systems? Fictional Legal Personhood versus Legal Identity","abstract":"The law draws a sharp distinction between objects and persons, and between two kinds of persons, the ''fictional'' kind (i.e. corporations), and the ''non-fictional'' kind (individual or ''natural'' persons). This paper will assess whether we maximize overall long-term legal coherence by (A) maintaining an object classification for all future AI systems, (B) creating fictional legal persons associated with suitably a","authors":["Heather J. Alexander","Jonathan A. Simon","Frédéric Pinard"],"url":"http://arxiv.org/abs/2511.14964v1","arxiv_id":"2511.14964v1","published":"2025-11-18T23:08:28Z"},{"title":"Reinforcement Learning from Implicit Neural Feedback for Human-Aligned Robot Control","abstract":"Conventional reinforcement learning (RL) approaches often struggle to learn effective policies under sparse reward conditions, necessitating the manual design of complex, task-specific reward functions. To address this limitation, reinforcement learning from human feedback (RLHF) has emerged as a promising strategy that complements hand-crafted rewards with human-derived evaluation signals. However, most existing RLH","authors":["Suzie Kim"],"url":"http://arxiv.org/abs/2512.00050v1","arxiv_id":"2512.00050v1","published":"2025-11-18T22:50:32Z"},{"title":"Artificial intelligence approaches for energy-efficient laser cutting machines","abstract":"This research addresses the significant challenges of energy consumption and environmental impact in laser cutting by proposing novel deep learning (DL) methodologies to achieve energy reduction. Recognizing the current lack of adaptive control and the open-loop nature of CO2 laser suction pumps, this study utilizes closed-loop configurations that dynamically adjust pump power based on both the material being cut and","authors":["Mohamed Abdallah Salem","Hamdy Ahmed Ashour","Ahmed Elshenawy"],"url":"http://arxiv.org/abs/2511.14952v1","arxiv_id":"2511.14952v1","published":"2025-11-18T22:25:58Z"},{"title":"Fifty Shades of Greenwashing: The Political Economy of Climate Change Advertising on Social Media","abstract":"In this paper, we provide a novel measure for greenwashing -- i.e., climate-related misinformation -- that shows how polluting companies can use social media advertising related to climate change to redirect criticism. To do so, we identify greenwashing content in 11 million social-political ads in Meta's Ad Targeting Datset with a measurement technique that combines large language models, human coders, and advances ","authors":["Robert Kubinec","Aseem Mahajan"],"url":"http://arxiv.org/abs/2511.14930v1","arxiv_id":"2511.14930v1","published":"2025-11-18T21:32:19Z"},{"title":"On-Premise SLMs vs. Commercial LLMs: Prompt Engineering and Incident Classification in SOCs and CSIRTs","abstract":"In this study, we evaluate open-source models for security incident classification, comparing them with proprietary models. We utilize a dataset of anonymized real incidents, categorized according to the NIST SP 800-61r3 taxonomy and processed using five prompt-engineering techniques (PHP, SHP, HTP, PRP, and ZSL). The results indicate that, although proprietary models still exhibit higher accuracy, locally deployed o","authors":["Gefté Almeida","Marcio Pohlmann","Alex Severo","Diego Kreutz","Tiago Heinrich","Lourenço Pereira"],"url":"http://arxiv.org/abs/2511.14908v1","arxiv_id":"2511.14908v1","published":"2025-11-18T20:56:49Z"},{"title":"Skin-R1: Clinical Knowledge-Guided Dermatological Diagnosis Using Vision-Language Models","abstract":"Vision--language models (VLMs) have recently shown promise for assisting clinical reasoning in dermatological diagnosis. However, their trustworthiness and clinical utility remain limited by three key challenges: heterogeneous datasets with inconsistent diagnostic labels and concept annotations, the lack of grounded diagnostic rationales for reliable reasoning supervision, and limited scalability when transferring kn","authors":["Zehao Liu","Weijieying Ren","Jipeng Zhang","Tianxiang Zhao","Jingxi Zhu","Xiaoting Li"],"url":"http://arxiv.org/abs/2511.14900v2","arxiv_id":"2511.14900v2","published":"2025-11-18T20:38:36Z"},{"title":"B-Rep Distance Functions (BR-DF): How to Represent a B-Rep Model by Volumetric Distance Functions?","abstract":"This paper presents a novel geometric representation for CAD Boundary Representation (B-Rep) based on volumetric distance functions, dubbed B-Rep Distance Functions (BR-DF). BR-DF encodes the surface mesh geometry of a CAD model as signed distance function (SDF). B-Rep vertices, edges, faces and their topology information are encoded as per-face unsigned distance functions (UDFs). An extension of the Marching Cubes a","authors":["Fuyang Zhang","Pradeep Kumar Jayaraman","Xiang Xu","Yasutaka Furukawa"],"url":"http://arxiv.org/abs/2511.14870v1","arxiv_id":"2511.14870v1","published":"2025-11-18T19:40:34Z"},{"title":"On the Difficulty of Token-Level Modeling of Dysfluency and Fluency Shaping Artifacts","abstract":"Automatic transcription of stuttered speech remains a challenge, even for modern end-to-end (E2E) automatic speech recognition (ASR) frameworks. Dysfluencies and fluency-shaping artifacts are often overlooked, resulting in non-verbatim transcriptions with limited clinical and research value. We propose a parameter-efficient adaptation method to decode dysfluencies and fluency modifications as special tokens within tr","authors":["Kashaf Gulzar","Dominik Wagner","Sebastian P. Bayerl","Florian Hönig","Tobias Bocklet","Korbinian Riedhammer"],"url":"http://arxiv.org/abs/2512.02027v1","arxiv_id":"2512.02027v1","published":"2025-11-18T19:33:29Z"},{"title":"AI for Proactive Mental Health: A Multi-Institutional, Longitudinal, Randomized Controlled Trial","abstract":"Young adults today face unprecedented mental health challenges, yet many hesitate to seek support due to barriers such as accessibility, stigma, and time constraints. Bite-sized well-being interventions offer a promising solution to preventing mental distress before it escalates to clinical levels, but have not yet been delivered through personalized, interactive, and scalable technology. We conducted the first multi","authors":["Julie Y. A. Cachia","Xuan Zhao","John Hunter","Delancey Wu","Eta Lin","Julian De Freitas"],"url":"http://arxiv.org/abs/2601.11530v1","arxiv_id":"2601.11530v1","published":"2025-11-18T19:16:42Z"},{"title":"When CNNs Outperform Transformers and Mambas: Revisiting Deep Architectures for Dental Caries Segmentation","abstract":"Accurate identification and segmentation of dental caries in panoramic radiographs are critical for early diagnosis and effective treatment planning. Automated segmentation remains challenging due to low lesion contrast, morphological variability, and limited annotated data. In this study, we present the first comprehensive benchmarking of convolutional neural networks, vision transformers and state-space mamba archi","authors":["Aashish Ghimire","Jun Zeng","Roshan Paudel","Nikhil Kumar Tomar","Deepak Ranjan Nayak","Harshith Reddy Nalla"],"url":"http://arxiv.org/abs/2511.14860v1","arxiv_id":"2511.14860v1","published":"2025-11-18T19:16:21Z"},{"title":"Uncertainty-Aware Measurement of Scenario Suite Representativeness for Autonomous Systems","abstract":"Assuring the trustworthiness and safety of AI systems, e.g., autonomous vehicles (AV), depends critically on the data-related safety properties, e.g., representativeness, completeness, etc., of the datasets used for their training and testing. Among these properties, this paper focuses on representativeness-the extent to which the scenario-based data used for training and testing, reflect the operational conditions t","authors":["Robab Aghazadeh Chakherlou","Siddartha Khastgir","Xingyu Zhao","Jerein Jeyachandran","Shufeng Chen"],"url":"http://arxiv.org/abs/2511.14853v2","arxiv_id":"2511.14853v2","published":"2025-11-18T19:05:50Z"},{"title":"PolyKAN: Efficient Fused GPU Operators for Polynomial Kolmogorov-Arnold Network Variants","abstract":"Kolmogorov-Arnold Networks (KANs) promise higher expressive capability and stronger interpretability than Multi-Layer Perceptron, particularly in the domain of AI for Science. However, practical adoption has been hindered by low GPU utilization of existing parallel implementations. To address this challenge, we present a GPU-accelerated operator library, named PolyKAN which is the first general open-source implementa","authors":["Mingkun Yu","Heming Zhong","Dan Huang","Yutong Lu","Jiazhi Jiang"],"url":"http://arxiv.org/abs/2511.14852v1","arxiv_id":"2511.14852v1","published":"2025-11-18T19:05:16Z"},{"title":"Empowering Multi-Turn Tool-Integrated Agentic Reasoning with Group Turn Policy Optimization","abstract":"Training Large Language Models (LLMs) for multi-turn Tool-Integrated Reasoning (TIR) - where models iteratively reason, generate code, and verify through execution - remains challenging for existing reinforcement learning (RL) approaches. Current RL methods, exemplified by Group Relative Policy Optimization (GRPO), suffer from coarse-grained, trajectory-level rewards that provide insufficient learning signals for com","authors":["Yifeng Ding","Hung Le","Songyang Han","Kangrui Ruan","Zhenghui Jin","Varun Kumar"],"url":"http://arxiv.org/abs/2511.14846v2","arxiv_id":"2511.14846v2","published":"2025-11-18T19:01:16Z"},{"title":"ARC Is a Vision Problem!","abstract":"The Abstraction and Reasoning Corpus (ARC) is designed to promote research on abstract reasoning, a fundamental aspect of human intelligence. Common approaches to ARC treat it as a language-oriented problem, addressed by large language models (LLMs) or recurrent reasoning models. However, although the puzzle-like tasks in ARC are inherently visual, existing research has rarely approached the problem from a vision-cen","authors":["Keya Hu","Ali Cy","Linlu Qiu","Xiaoman Delores Ding","Runqian Wang","Yeyin Eva Zhu"],"url":"http://arxiv.org/abs/2511.14761v1","arxiv_id":"2511.14761v1","published":"2025-11-18T18:59:49Z"},{"title":"Implicit Bias of the JKO Scheme","abstract":"Wasserstein gradient flow provides a general framework for minimizing an energy functional $J$ over the space of probability measures on a Riemannian manifold $(M,g)$. Its canonical time-discretization, the Jordan-Kinderlehrer-Otto (JKO) scheme, produces for any step size $η>0$ a sequence of probability distributions $ρ_k^η$ that approximate to first order in $η$ Wasserstein gradient flow on $J$. But the JKO schem","authors":["Peter Halmos","Boris Hanin"],"url":"http://arxiv.org/abs/2511.14827v3","arxiv_id":"2511.14827v3","published":"2025-11-18T18:48:37Z"},{"title":"Heterogeneous Multi-Agent Proximal Policy Optimization for Power Distribution System Restoration","abstract":"Restoring power distribution systems (PDSs) after large-scale outages requires sequential switching actions that reconfigure feeder topology and coordinate distributed energy resources (DERs) under nonlinear constraints, including power balance, voltage limits, and thermal ratings. These challenges limit the scalability of conventional optimization and value-based reinforcement learning (RL) approaches. This paper ap","authors":["Parya Dolatyabi","Ali Farajzadeh Bavil","Mahdi Khodayar"],"url":"http://arxiv.org/abs/2511.14730v5","arxiv_id":"2511.14730v5","published":"2025-11-18T18:23:35Z"},{"title":"Automated proving in planar geometry based on the complex number identity method and elimination","abstract":"We improve the complex number identity proving method to a fully automated procedure, based on elimination ideals. By using declarative equations or rewriting each real-relational hypothesis $h_i$ to $h_i-r_i$, and the thesis $t$ to $t-r$, clearing the denominators and introducing an extra expression with a slack variable, we eliminate all free and relational point variables. From the obtained ideal $I$ in $\\mathbb{Q","authors":["Zoltán Kovács","Xicheng Peng"],"url":"http://arxiv.org/abs/2511.14728v1","arxiv_id":"2511.14728v1","published":"2025-11-18T18:20:17Z"},{"title":"GPS: General Per-Sample Prompter","abstract":"LLMs are sensitive to prompting, with task performance often hinging on subtle, sometimes imperceptible variations in phrasing. As a result, crafting effective prompts manually remains challenging and time-consuming. Recent automatic prompting methods mitigate this difficulty but face three key limitations: (i) for each new task, they require large datasets to train good prompts;(ii) they rely on costly optimization ","authors":["Pawel Batorski","Paul Swoboda"],"url":"http://arxiv.org/abs/2511.21714v1","arxiv_id":"2511.21714v1","published":"2025-11-18T18:10:09Z"},{"title":"Zero-shot Synthetic Video Realism Enhancement via Structure-aware Denoising","abstract":"We propose an approach to enhancing synthetic video realism, which can re-render synthetic videos from a simulator in photorealistic fashion. Our realism enhancement approach is a zero-shot framework that focuses on preserving the multi-level structures from synthetic videos into the enhanced one in both spatial and temporal domains, built upon a diffusion video foundational model without further fine-tuning. Specifi","authors":["Yifan Wang","Liya Ji","Zhanghan Ke","Harry Yang","Ser-Nam Lim","Qifeng Chen"],"url":"http://arxiv.org/abs/2511.14719v1","arxiv_id":"2511.14719v1","published":"2025-11-18T18:06:29Z"}],"history":{"events":[{"year":2017,"text":"Cyclone Numa, a rare \"medicane\", made landfall in Greece to become the worst weather event that the country had experienced since 1977.","url":"https://en.wikipedia.org/wiki/Cyclone_Numa"},{"year":2014,"text":"Two Palestinian men attacked the praying congregants of a synagogue in Jerusalem with axes, knives, and a gun, resulting in eight deaths, including the attackers themselves.","url":"https://en.wikipedia.org/wiki/2014_Jerusalem_synagogue_attack"},{"year":2011,"text":"The sandbox video game Minecraft exited beta with the official release of version 1.0.","url":"https://en.wikipedia.org/wiki/Minecraft"},{"year":2003,"text":"With its ruling in Goodridge v. Department of Public Health, the Massachusetts Supreme Judicial Court made the state the first in the U.S. to legalize same-sex marriage.","url":"https://en.wikipedia.org/wiki/Goodridge_v._Department_of_Public_Health"},{"year":1999,"text":"Texas A&M University's Aggie Bonfire collapsed (aftermath pictured), killing 12 people and injuring 27 others, and causing the university to officially declare a hiatus on the 90-year-old annual event.","url":"https://en.wikipedia.org/wiki/Texas_A%26M_University"},{"year":1991,"text":"The current flag of Uzbekistan was adopted, making the country the first newly independent republic in Central Asia to choose a new flag.","url":"https://en.wikipedia.org/wiki/Flag_of_Uzbekistan"},{"year":1991,"text":"Croatian War of Independence: The Yugoslav People's Army captured the Croatian city of Vukovar, ending an 87-day siege.","url":"https://en.wikipedia.org/wiki/Croatian_War_of_Independence"},{"year":1987,"text":"An underground fire killed 31 people at King's Cross St Pancras tube station in London.","url":"https://en.wikipedia.org/wiki/King's_Cross_fire"},{"year":1978,"text":"Jim Jones led more than 900 members of the Peoples Temple to mass murder/suicide in Jonestown, Guyana, hours after some of its members assassinated U.S. Congressman Leo Ryan.","url":"https://en.wikipedia.org/wiki/Jim_Jones"},{"year":1977,"text":"Solomon Islands ratified the adoption of a new flag (pictured).","url":"https://en.wikipedia.org/wiki/Flag_of_Solomon_Islands"},{"year":1956,"text":"At the Polish embassy in Moscow, a phrase in an address by Soviet leader Nikita Khrushchev was translated into English as \"We will bury you\", prompting Western envoys to leave the room.","url":"https://en.wikipedia.org/wiki/Nikita_Khrushchev"},{"year":1872,"text":"American suffragist Susan B. Anthony (pictured) was arrested and later fined $100 for having voted in the presidential election two weeks earlier.","url":"https://en.wikipedia.org/wiki/Women's_suffrage_in_the_United_States"},{"year":1865,"text":"\"The Celebrated Jumping Frog of Calaveras County\" was published, becoming the first great success of American author Mark Twain.","url":"https://en.wikipedia.org/wiki/The_Celebrated_Jumping_Frog_of_Calaveras_County"},{"year":1809,"text":"Napoleonic Wars: In the Bay of Bengal, a French frigate squadron captured three ships carrying recruits for the armies of the East India Company.","url":"https://en.wikipedia.org/wiki/Napoleonic_Wars"},{"year":1583,"text":"The Siege of Godes­berg, the first major siege of the Cologne War, began.","url":"https://en.wikipedia.org/wiki/Siege_of_Godesberg"},{"year":1210,"text":"Otto IV, Holy Roman Emperor, was ex­com­mu­ni­cated by Pope Innocent III after Otto commanded him to annul the Concordat of Worms.","url":"https://en.wikipedia.org/wiki/Otto_IV%2C_Holy_Roman_Emperor"}],"births":[{"year":2004,"text":"Luka Romero, Mexican-Argentine footballer","url":"https://en.wikipedia.org/wiki/Luka_Romero"},{"year":2002,"text":"Patrick Baldwin Jr., American basketball player","url":"https://en.wikipedia.org/wiki/Patrick_Baldwin_Jr."},{"year":2001,"text":"Caleb Williams, American football player","url":"https://en.wikipedia.org/wiki/Caleb_Williams"},{"year":1997,"text":"Jacob Bryson, Canadian ice hockey player","url":"https://en.wikipedia.org/wiki/Jacob_Bryson"},{"year":1997,"text":"Shea Langeliers, American baseball player","url":"https://en.wikipedia.org/wiki/Shea_Langeliers"},{"year":1997,"text":"Robert Sánchez, Spanish footballer","url":"https://en.wikipedia.org/wiki/Robert_S%C3%A1nchez"},{"year":1996,"text":"Akram Afif, Qatari footballer","url":"https://en.wikipedia.org/wiki/Akram_Afif"},{"year":1996,"text":"Christian Kirk, American football player","url":"https://en.wikipedia.org/wiki/Christian_Kirk"}],"deaths":[{"year":2024,"text":"Charles Dumont, French singer and composer (born 1929)","url":"https://en.wikipedia.org/wiki/Charles_Dumont_(singer)"},{"year":2024,"text":"Arthur Frommer, American travel writer (born 1929)","url":"https://en.wikipedia.org/wiki/Arthur_Frommer"},{"year":2024,"text":"Bob Love, American basketball player (born 1942)","url":"https://en.wikipedia.org/wiki/Bob_Love"},{"year":2024,"text":"Colin Petersen, Australian drummer, record producer and actor (born 1946)","url":"https://en.wikipedia.org/wiki/Colin_Petersen"},{"year":2022,"text":"Tabassum, Indian actress and talk show host (born 1944)","url":"https://en.wikipedia.org/wiki/Tabassum"},{"year":2020,"text":"Kirby Morrow, Canadian actor, comedian, and writer (born 1973)","url":"https://en.wikipedia.org/wiki/Kirby_Morrow"},{"year":2017,"text":"Malcolm Young, Scottish-Australian hard rock guitarist (born 1953)","url":"https://en.wikipedia.org/wiki/Malcolm_Young"},{"year":2016,"text":"Sharon Jones, American soul and funk singer (born 1956)","url":"https://en.wikipedia.org/wiki/Sharon_Jones"}]},"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."}