{"date":"2025-12-12","schema_version":1,"captured_at":"2026-08-25T23:04:42.799Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":14},"attention":[{"title":"Dhurandhar","views":552465,"rank":3,"extract":"Dhurandhar is a 2025 Indian Hindi-language spy action thriller film written and directed by Aditya Dhar. It is produced by Aditya Dhar, Lokesh Dhar and Jyoti Deshpande under Jio Studios and B62 Studios. The film features an ensemble cast consisting of Ranveer ","url":"https://en.wikipedia.org/wiki/Dhurandhar","thumb":"https://upload.wikimedia.org/wikipedia/en/c/ce/Dhurandhar_poster.jpg?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail_unscaled"},{"title":"Sherrone Moore","views":443032,"rank":4,"extract":"Sherrone Banfield Moore is an American former college football head coach and player. He most recently served as the head football coach for the University of Michigan. 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[video]","points":182,"comments":178,"url":"https://www.youtube.com/watch?v=qEllWdK4l_A","discussion":"https://news.ycombinator.com/item?id=46247415"},{"title":"Guarding My Git Forge Against AI Scrapers","points":182,"comments":131,"url":"https://vulpinecitrus.info/blog/guarding-git-forge-ai-scrapers/","discussion":"https://news.ycombinator.com/item?id=46241849"}],"research":[{"title":"Dual Cluster Contrastive learning for Object Re-Identification","abstract":"Recently, cluster contrastive learning has been proven effective for object ReID by computing the contrastive loss between the individual features and the cluster memory. However, existing methods that use the individual features to momentum update the cluster memory will fluctuate over the training examples, especially for the outlier samples. Unlike the individual-based updating mechanism, the centroid-based updati","authors":["Yao, Hantao","Xu, Changsheng"],"url":"https://arxiv.org/abs/2112.04662","arxiv_id":"2112.04662","published":"2025-12-12"},{"title":"Combining Monte Carlo and Tensor-network Methods for Partial Differential Equations via Sketching","abstract":"In this paper, we propose a general framework for solving high-dimensional partial differential equations with tensor networks. Our approach uses Monte-Carlo simulations to update the solution and re-estimates the new solution from samples as a tensor-network using a recently proposed tensor train sketching technique. We showcase the versatility and flexibility of our approach by applying it to two specific scenarios","authors":["Chen, Yian","Khoo, Yuehaw","Yu, Ziang"],"url":"https://arxiv.org/abs/2305.17884","arxiv_id":"2305.17884","published":"2025-12-12"},{"title":"Multi-Robot Path Planning Combining Heuristics and Multi-Agent Reinforcement Learning","abstract":"Multi-robot path finding in dynamic environments is a highly challenging classic problem. In the movement process, robots need to avoid collisions with other moving robots while minimizing their travel distance. Previous methods for this problem either continuously replan paths using heuristic search methods to avoid conflicts or choose appropriate collision avoidance strategies based on learning approaches. The form","authors":["Peng, Shaoming"],"url":"https://arxiv.org/abs/2306.01270","arxiv_id":"2306.01270","published":"2025-12-12"},{"title":"Joint2Human: High-quality 3D Human Generation via Compact Spherical Embedding of 3D Joints","abstract":"3D human generation is increasingly significant in various applications. However, the direct use of 2D generative methods in 3D generation often results in losing local details, while methods that reconstruct geometry from generated images struggle with global view consistency. In this work, we introduce Joint2Human, a novel method that leverages 2D diffusion models to generate detailed 3D human geometry directly, en","authors":["Zhang, Muxin","Feng, Qiao","Su, Zhuo","Wen, Chao","Xue, Zhou","Li, Kun"],"url":"https://arxiv.org/abs/2312.08591","arxiv_id":"2312.08591","published":"2025-12-12"},{"title":"Noisy Spiking Actor Network for Exploration","abstract":"As a general method for exploration in deep reinforcement learning (RL), NoisyNet can produce problem-specific exploration strategies. Spiking neural networks (SNNs), due to their binary firing mechanism, have strong robustness to noise, making it difficult to realize efficient exploration with local disturbances. To solve this exploration problem, we propose a noisy spiking actor network (NoisySAN) that introduces t","authors":["Chen, Ding","Peng, Peixi","Huang, Tiejun","Tian, Yonghong"],"url":"https://arxiv.org/abs/2403.04162","arxiv_id":"2403.04162","published":"2025-12-12"},{"title":"Leveraging language models for summarizing mental state examinations: A comprehensive evaluation and dataset release","abstract":"Mental health disorders affect a significant portion of the global population, with diagnoses primarily conducted through Mental State Examinations (MSEs). MSEs serve as structured assessments to evaluate behavioral and cognitive functioning across various domains, aiding mental health professionals in diagnosis and treatment monitoring. However, in developing countries, access to mental health support is limited, le","authors":["Sahu, Nilesh Kumar","Yadav, Manjeet","Chaturvedi, Mudita","Gupta, Snehil","Lone, Haroon R"],"url":"https://arxiv.org/abs/2403.20145","arxiv_id":"2403.20145","published":"2025-12-12"},{"title":"PHLP: Sole Persistent Homology for Link Prediction - Interpretable Feature Extraction","abstract":"Link prediction (LP), inferring the connectivity between nodes, is a significant research area in graph data, where a link represents essential information on relationships between nodes. Although graph neural network (GNN)-based models have achieved high performance in LP, understanding why they perform well is challenging because most comprise complex neural networks. We employ persistent homology (PH), a topologic","authors":["You, Junwon","Heo, Eunwoo","Jung, Jae-Hun"],"url":"https://arxiv.org/abs/2404.15225","arxiv_id":"2404.15225","published":"2025-12-12"},{"title":"ObjectAdd: Adding Objects into Image via a Training-Free Diffusion Modification Fashion","abstract":"We introduce ObjectAdd, a training-free diffusion modification method to add user-expected objects into user-specified area. The motive of ObjectAdd stems from: first, describing everything in one prompt can be difficult, and second, users often need to add objects into the generated image. To accommodate with real world, our ObjectAdd maintains accurate image consistency after adding objects with technical innovatio","authors":["Zhang, Ziyue","Lin, Mingbao","Song, Quanjian","Zhang, Yuxin","Ji, Rongrong"],"url":"https://arxiv.org/abs/2404.17230","arxiv_id":"2404.17230","published":"2025-12-12"},{"title":"The Spatial Semantics of Iconic Gesture","abstract":"The current multimodal turn in linguistic theory leaves a crucial question unanswered: what is the meaning of iconic gestures, and how does it compose with speech meaning? We argue for a separation of linguistic and visual levels of meaning and introduce a spatial gesture semantics that closes this gap. Iconicity is differentiated into three aspects: Firstly, an interpretation of the form of a gesture in terms of a t","authors":["Lücking, Andy","Henlein, Alexander","Mehler, Alexander"],"url":"https://arxiv.org/abs/2404.18708","arxiv_id":"2404.18708","published":"2025-12-12"},{"title":"The SIFo Benchmark: Investigating the Sequential Instruction Following Ability of Large Language Models","abstract":"Following multiple instructions is a crucial ability for large language models (LLMs). Evaluating this ability comes with significant challenges: (i) limited coherence between multiple instructions, (ii) positional bias where the order of instructions affects model performance, and (iii) a lack of objectively verifiable tasks. To address these issues, we introduce a benchmark designed to evaluate models' abilitie","authors":["Chen, Xinyi","Liao, Baohao","Qi, Jirui","Eustratiadis, Panagiotis","Monz, Christof","Bisazza, Arianna"],"url":"https://arxiv.org/abs/2406.19999","arxiv_id":"2406.19999","published":"2025-12-12"},{"title":"Anthropocentric bias in language model evaluation","abstract":"Evaluating the cognitive capacities of large language models (LLMs) requires overcoming not only anthropomorphic but also anthropocentric biases. This article identifies two types of anthropocentric bias that have been neglected: overlooking how auxiliary factors can impede LLM performance despite competence ("auxiliary oversight"), and dismissing LLM mechanistic strategies that differ from those of humans as","authors":["Millière, Raphaël","Rathkopf, Charles"],"url":"https://arxiv.org/abs/2407.03859","arxiv_id":"2407.03859","published":"2025-12-12"},{"title":"Machine Learning for Quantifier Selection in cvc5","abstract":"In this work we considerably improve the state-of-the-art SMT solving on first-order quantified problems by efficient machine learning guidance of quantifier selection. Quantifiers represent a significant challenge for SMT and are technically a source of undecidability. In our approach, we train an efficient machine learning model that informs the solver which quantifiers should be instantiated and which not. Each qu","authors":["Jakubův, Jan","Janota, Mikoláš","Piepenbrock, Jelle","Urban, Josef"],"url":"https://arxiv.org/abs/2408.14338","arxiv_id":"2408.14338","published":"2025-12-12"},{"title":"Enhancing Large Language Models with Domain-Specific Knowledge: The Case in Topological Materials","abstract":"Large language models (LLMs), such as ChatGPT, have demonstrated impressive performance in the text generation task, showing the ability to understand and respond to complex instructions. However, the performance of naive LLMs in speciffc domains is limited due to the scarcity of domain-speciffc corpora and specialized training. Moreover, training a specialized large-scale model necessitates signiffcant hardware reso","authors":["Xu, HuangChao","Zhang, Baohua","Jin, Zhong","Zhu, Tiannian","Wu, Quansheng","Weng, Hongming"],"url":"https://arxiv.org/abs/2409.13732","arxiv_id":"2409.13732","published":"2025-12-12"},{"title":"Natural Language Processing for the Legal Domain: A Survey of Tasks, Datasets, Models, and Challenges","abstract":"Natural Language Processing (NLP) is revolutionising the way both professionals and laypersons operate in the legal field. The considerable potential for NLP in the legal sector, especially in developing computational assistance tools for various legal processes, has captured the interest of researchers for years. This survey follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework, re","authors":["Ariai, Farid","Mackenzie, Joel","Demartini, Gianluca"],"url":"https://arxiv.org/abs/2410.21306","arxiv_id":"2410.21306","published":"2025-12-12"},{"title":"How to Bridge Spatial and Temporal Heterogeneity in Link Prediction? A Contrastive Method","abstract":"Temporal Heterogeneous Networks play a crucial role in capturing the dynamics and heterogeneity inherent in various real-world complex systems, rendering them a noteworthy research avenue for link prediction. However, existing methods fail to capture the fine-grained differential distribution patterns and temporal dynamic characteristics, which we refer to as spatial heterogeneity and temporal heterogeneity. To overc","authors":["Tai, Yu","Wu, Xinglong","Yang, Hongwei","He, Hui","Chen, Duanjing","Shao, Yuanming"],"url":"https://arxiv.org/abs/2411.00612","arxiv_id":"2411.00612","published":"2025-12-12"},{"title":"Deferred Poisoning: Making the Model More Vulnerable via Hessian Singularization","abstract":"Recent studies have shown that deep learning models are very vulnerable to poisoning attacks. Many defense methods have been proposed to address this issue. However, traditional poisoning attacks are not as threatening as commonly believed. This is because they often cause differences in how the model performs on the training set compared to the validation set. Such inconsistency can alert defenders that their data h","authors":["He, Yuhao","Tian, Jinyu","Zheng, Xianwei","Dong, Li","Li, Yuanman","Zhou, Jiantao"],"url":"https://arxiv.org/abs/2411.03752","arxiv_id":"2411.03752","published":"2025-12-12"},{"title":"l0-Regularized Sparse Coding-based Interpretable Network for Multi-Modal Image Fusion","abstract":"Multi-modal image fusion (MMIF) enhances the information content of the fused image by combining the unique as well as common features obtained from different modality sensor images, improving visualization, object detection, and many more tasks. In this work, we introduce an interpretable network for the MMIF task, named FNet, based on an $\\ell_0$-regularized multi-modal convolutional sparse coding (MCSC) model. Spe","authors":["Panda, Gargi","Kundu, Soumitra","Bhattacharya, Saumik","Routray, Aurobinda"],"url":"https://arxiv.org/abs/2411.04519","arxiv_id":"2411.04519","published":"2025-12-12"},{"title":"Equivariant Test-Time Training with Operator Sketching for Imaging Inverse Problems","abstract":"Equivariant Imaging (EI) regularization has become the de-facto technique for unsupervised training of deep imaging networks, without any need of ground-truth data. Observing that the EI-based unsupervised training paradigm currently has significant computational redundancy leading to inefficiency in high-dimensional applications, we propose a sketched EI regularization which leverages the randomized sketching techni","authors":["Xu, Guixian","Li, Jinglai","Tang, Junqi"],"url":"https://arxiv.org/abs/2411.05771","arxiv_id":"2411.05771","published":"2025-12-12"},{"title":"Pointwise Mutual Information as a Performance Gauge for Retrieval-Augmented Generation","abstract":"Recent work suggests that large language models enhanced with retrieval-augmented generation are easily influenced by the order, in which the retrieved documents are presented to the model when solving tasks such as question answering (QA). However, there is no method to date that exploits this phenomenon to improve generation. We fill this gap. In this study, we show that the pointwise mutual information between a c","authors":["Liu, Tianyu","Qi, Jirui","He, Paul","Bisazza, Arianna","Sachan, Mrinmaya","Cotterell, Ryan"],"url":"https://arxiv.org/abs/2411.07773","arxiv_id":"2411.07773","published":"2025-12-12"},{"title":"A Generation Framework with Strict Constraints for Crystal Materials Design","abstract":"The design of crystal materials plays a critical role in areas such as new energy development, biomedical engineering, and semiconductors. Recent advances in data-driven methods have enabled the generation of diverse crystal structures. However, most existing approaches still rely on random sampling without strict constraints, requiring multiple post-processing steps to identify stable candidates with the desired phy","authors":["Huang, Chao","Chen, Jiahui","Chen, Chen","Chen, Chen","Chen, Chunyan","Su, Renjie"],"url":"https://arxiv.org/abs/2411.08464","arxiv_id":"2411.08464","published":"2025-12-12"},{"title":"Rethinking Normalization Strategies and Convolutional Kernels for Multimodal Image Fusion","abstract":"Multimodal image fusion (MMIF) integrates information from different modalities to obtain a comprehensive image, aiding downstream tasks. However, existing research focuses on complementary information fusion and training strategies, overlooking the critical role of underlying architectural components like normalization and convolution kernels. We reevaluate the UNet architecture for end-to-end MMIF, identifying that","authors":["He, Dan","Wang, Guofen","Li, Weisheng","Shu, Yucheng","Li, Wenbo","Yang, Lijian"],"url":"https://arxiv.org/abs/2411.10036","arxiv_id":"2411.10036","published":"2025-12-12"},{"title":"Dressing the Imagination: A Dataset for AI-Powered Translation of Text into Fashion Outfits and A Novel NeRA Adapter for Enhanced Feature Adaptation","abstract":"Specialized datasets that capture the fashion industry's rich language and styling elements can boost progress in AI-driven fashion design. We present FLORA, (Fashion Language Outfit Representation for Apparel Generation), the first comprehensive dataset containing 4,330 curated pairs of fashion outfits and corresponding textual descriptions. Each description utilizes industry-specific terminology and jargon comm","authors":["Deshmukh, Gayatri","De, Somsubhra","Sehgal, Chirag","Gupta, Jishu Sen","Mittal, Sparsh"],"url":"https://arxiv.org/abs/2411.13901","arxiv_id":"2411.13901","published":"2025-12-12"},{"title":"Lightweight Model Attribution and Detection of Synthetic Speech via Audio Residual Fingerprints","abstract":"As speech generation technologies advance, so do risks of impersonation, misinformation, and spoofing. We present a lightweight, training-free approach for detecting synthetic speech and attributing it to its source model. Our method addresses three tasks: (1) single-model attribution in an open-world setting, (2) multi-model attribution in a closed-world setting, and (3) real vs. synthetic speech classification. The","authors":["Pizarro, Matías","Laszkiewicz, Mike","Kolossa, Dorothea","Fischer, Asja"],"url":"https://arxiv.org/abs/2411.14013","arxiv_id":"2411.14013","published":"2025-12-12"},{"title":"Brain-like emergent properties in deep networks: impact of network architecture, datasets and training","abstract":"Despite the rapid pace at which deep networks are improving on standardized vision benchmarks, they are still outperformed by humans on real-world vision tasks. One solution to this problem is to make deep networks more brain-like. Although there are several benchmarks that compare the ability of deep networks to predict brain responses on natural images, they do not capture subtle but important emergent properties p","authors":["Rajesh, Niranjan","Jacob, Georgin","Arun, SP"],"url":"https://arxiv.org/abs/2411.16326","arxiv_id":"2411.16326","published":"2025-12-12"},{"title":"Object-centric proto-symbolic behavioural reasoning from pixels","abstract":"Autonomous intelligent agents must bridge computational challenges at disparate levels of abstraction, from the low-level spaces of sensory input and motor commands to the high-level domain of abstract reasoning and planning. A key question in designing such agents is how best to instantiate the representational space that will interface between these two levels -- ideally without requiring supervision in the form of","authors":["van Bergen, Ruben","Hübotter, Justus","Lago, Alma","Lanillos, Pablo"],"url":"https://arxiv.org/abs/2411.17438","arxiv_id":"2411.17438","published":"2025-12-12"}],"history":{"events":[{"year":2021,"text":"At the season-ending Abu Dhabi Grand Prix, Max Verstappen overtook Lewis Hamilton on the final lap to become World Drivers' Champion.","url":"https://en.wikipedia.org/wiki/2021_Abu_Dhabi_Grand_Prix"},{"year":2012,"text":"North Korea made its first successful satellite launch, as Kwangmyŏngsŏng-3 Unit 2 reached orbit.","url":"https://en.wikipedia.org/wiki/Kwangmy%C5%8Fngs%C5%8Fng-3_Unit_2"},{"year":2000,"text":"The U.S. Supreme Court ruled in Bush v. Gore that the recount of ballots cast in Florida for the presidential election be stopped, effectively making George W. Bush (pictured) the winner.","url":"https://en.wikipedia.org/wiki/Supreme_Court_of_the_United_States"},{"year":1988,"text":"Three trains collided near Clapham Junction railway station in London, killing 35 people and injuring 484 others.","url":"https://en.wikipedia.org/wiki/Clapham_Junction_rail_crash"},{"year":1979,"text":"A magnitude-8.2 earthquake struck just off the shore of Tumaco, Colombia, causing at least 300 deaths, mostly by the resulting tsunami.","url":"https://en.wikipedia.org/wiki/1979_Tumaco_earthquake"},{"year":1969,"text":"The Greek junta announced its withdrawal from the Council of Europe after the junta was found guilty of torture and other human-rights violations by the European Commission of Human Rights.","url":"https://en.wikipedia.org/wiki/Greek_junta"},{"year":1964,"text":"Jomo Kenyatta became the first president of the Republic of Kenya.","url":"https://en.wikipedia.org/wiki/Jomo_Kenyatta"},{"year":1942,"text":"World War II: German troops began Operation Winter Storm, an attempt to relieve encircled Axis forces during the Battle of Stalingrad.","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1941,"text":"The Holocaust: At a Nazi Party meeting in the Reich Chancellery, Adolf Hitler declared the imminent destruction of the Jewish people.","url":"https://en.wikipedia.org/wiki/The_Holocaust"},{"year":1939,"text":"The Royal Navy destroyer HMS Duchess (pictured) collided with HMS Barham, the battleship she was escorting, and Duchess sank with heavy loss of life.","url":"https://en.wikipedia.org/wiki/Royal_Navy"},{"year":1936,"text":"Republic of China leader Chiang Kai-shek was kidnapped by Marshal Chang Hsueh-liang, a former warlord of Manchuria.","url":"https://en.wikipedia.org/wiki/Republic_of_China_(1912%E2%80%931949)"},{"year":1866,"text":"England's worst mining disaster occurred when a series of explosions (depicted) caused by flammable gases ripped through the Oaks Colliery, killing 361 people.","url":"https://en.wikipedia.org/wiki/Oaks_explosion"},{"year":1388,"text":"Unable to defend her possessions, Maria of Enghien sold the lordship of Argos and Nauplia to the Republic of Venice.","url":"https://en.wikipedia.org/wiki/Mary_of_Enghien"},{"year":627,"text":"At the Battle of Nineveh, the Byzantine army under Emperor Heraclius defeated the forces of Sasanian emperor Khosrow II, commanded by Rhahzadh, near present-day Mosul, Iraq.","url":"https://en.wikipedia.org/wiki/Battle_of_Nineveh_(627)"}],"births":[{"year":2001,"text":"Michael Olise, French footballer","url":"https://en.wikipedia.org/wiki/Michael_Olise"},{"year":1997,"text":"Ed Oliver, American football player","url":"https://en.wikipedia.org/wiki/Ed_Oliver_(American_football)"},{"year":1996,"text":"Lucas Hedges, American actor","url":"https://en.wikipedia.org/wiki/Lucas_Hedges"},{"year":1994,"text":"Otto Warmbier, American student imprisoned in North Korea (died 2017)","url":"https://en.wikipedia.org/wiki/Otto_Warmbier"},{"year":1993,"text":"Zeli Ismail, English footballer","url":"https://en.wikipedia.org/wiki/Zeli_Ismail"},{"year":1991,"text":"Shohjahon Ergashev, Uzbek professional boxer","url":"https://en.wikipedia.org/wiki/Shohjahon_Ergashev"},{"year":1991,"text":"Joseph Leilua, Australian-Samoan rugby league player","url":"https://en.wikipedia.org/wiki/Joseph_Leilua"},{"year":1990,"text":"Nixon Chepseba, Kenyan runner","url":"https://en.wikipedia.org/wiki/Nixon_Chepseba"}],"deaths":[{"year":2021,"text":"Vicente Fernández, Mexican actor, ranchera singer, and film producer (born 1940)","url":"https://en.wikipedia.org/wiki/Vicente_Fern%C3%A1ndez"},{"year":2021,"text":"Bernie Fowler, American politician and environmental advocate (born 1924)","url":"https://en.wikipedia.org/wiki/Bernie_Fowler"},{"year":2021,"text":"Maʻafu Tukuiʻaulahi, Tongan politician and military officer, Deputy Prime Minister (born 1955)","url":"https://en.wikipedia.org/wiki/Ma%CA%BBafu_Tukui%CA%BBaulahi"},{"year":2020,"text":"John le Carré, English author (born 1931)","url":"https://en.wikipedia.org/wiki/John_le_Carr%C3%A9"},{"year":2020,"text":"Ann Reinking, American actress, dancer, and choreographer (born 1949)","url":"https://en.wikipedia.org/wiki/Ann_Reinking"},{"year":2019,"text":"Danny Aiello, American actor (born 1933)","url":"https://en.wikipedia.org/wiki/Danny_Aiello"},{"year":2017,"text":"Ed Lee, American politician and attorney, 43rd Mayor of San Francisco (born 1952)","url":"https://en.wikipedia.org/wiki/Ed_Lee"},{"year":2017,"text":"Pat DiNizio, American singer and songwriter (born 1955)","url":"https://en.wikipedia.org/wiki/Pat_DiNizio"}]},"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."}