{"date":"2025-11-09","schema_version":1,"captured_at":"2026-08-25T22:56:10.537Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":15},"attention":[{"title":"Zohran Mamdani","views":427987,"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, their reliability remains a challenge, especially in long-horizon tasks, since they often produce overconfident yet wrong outputs. Conformal Prediction (CP) has been leveraged to address this issue by wrapping LLM outputs into prediction sets tha","authors":["Jun Wang","Yevgeniy Vorobeychik","Yiannis Kantaros"],"url":"http://arxiv.org/abs/2511.06575v1","arxiv_id":"2511.06575v1","published":"2025-11-09T23:38:25Z"},{"title":"SteganoSNN: SNN-Based Audio-in-Image Steganography with Encryption","abstract":"Secure data hiding remains a fundamental challenge in digital communication, requiring a careful balance between computational efficiency and perceptual transparency. The balance between security and performance is increasingly fragile with the emergence of generative AI systems capable of autonomously generating and optimising sophisticated cryptanalysis and steganalysis algorithms, thereby accelerating the exposure","authors":["Biswajit Kumar Sahoo","Pedro Machado","Isibor Kennedy Ihianle","Andreas Oikonomou","Srinivas Boppu"],"url":"http://arxiv.org/abs/2511.06573v1","arxiv_id":"2511.06573v1","published":"2025-11-09T23:31:53Z"},{"title":"Rep2Text: Decoding Full Text from a Single LLM Token Representation","abstract":"Large language models (LLMs) have achieved remarkable progress across diverse tasks, yet their internal mechanisms remain largely opaque. In this work, we investigate a fundamental question: to what extent can the original input text be recovered from a single last-token representation in an LLM? To this end, we propose Rep2Text, a novel framework for decoding text from last-token representations. Rep2Text employs a ","authors":["Haiyan Zhao","Zirui He","Yiming Tang","Fan Yang","Ali Payani","Dianbo Liu"],"url":"http://arxiv.org/abs/2511.06571v3","arxiv_id":"2511.06571v3","published":"2025-11-09T23:18:36Z"},{"title":"Breaking the Dyadic Barrier: Rethinking Fairness in Link Prediction Beyond Demographic Parity","abstract":"Link prediction is a fundamental task in graph machine learning with applications, ranging from social recommendation to knowledge graph completion. Fairness in this setting is critical, as biased predictions can exacerbate societal inequalities. Prior work adopts a dyadic definition of fairness, enforcing fairness through demographic parity between intra-group and inter-group link predictions. However, we show that ","authors":["João Mattos","Debolina Halder Lina","Arlei Silva"],"url":"http://arxiv.org/abs/2511.06568v2","arxiv_id":"2511.06568v2","published":"2025-11-09T22:58:29Z"},{"title":"Time-to-Move: Training-Free Motion Controlled Video Generation via Dual-Clock Denoising","abstract":"Diffusion-based video generation can create realistic videos, yet existing image- and text-based conditioning fails to offer precise motion control. Prior methods for motion-conditioned synthesis typically require model-specific fine-tuning, which is computationally expensive and restrictive. We introduce Time-to-Move (TTM), a training-free, plug-and-play framework for motion- and appearance-controlled video generati","authors":["Assaf Singer","Noam Rotstein","Amir Mann","Ron Kimmel","Or Litany"],"url":"http://arxiv.org/abs/2511.08633v1","arxiv_id":"2511.08633v1","published":"2025-11-09T22:47:50Z"},{"title":"LLM For Loop Invariant Generation and Fixing: How Far Are We?","abstract":"A loop invariant is a property of a loop that remains true before and after each execution of the loop. The identification of loop invariants is a critical step to support automated program safety assessment. Recent advancements in Large Language Models (LLMs) have demonstrated potential in diverse software engineering (SE) and formal verification tasks. However, we are not aware of the performance of LLMs to infer l","authors":["Mostafijur Rahman Akhond","Saikat Chakraborty","Gias Uddin"],"url":"http://arxiv.org/abs/2511.06552v1","arxiv_id":"2511.06552v1","published":"2025-11-09T21:47:45Z"},{"title":"When Are Learning Biases Equivalent? A Unifying Framework for Fairness, Robustness, and Distribution Shift","abstract":"Machine learning systems exhibit diverse failure modes: unfairness toward protected groups, brittleness to spurious correlations, poor performance on minority sub-populations, which are typically studied in isolation by distinct research communities. We propose a unifying theoretical framework that characterizes when different bias mechanisms produce quantitatively equivalent effects on model performance. By formaliz","authors":["Sushant Mehta"],"url":"http://arxiv.org/abs/2511.07485v1","arxiv_id":"2511.07485v1","published":"2025-11-09T20:48:09Z"},{"title":"Ibom NLP: A Step Toward Inclusive Natural Language Processing for Nigeria's Minority Languages","abstract":"Nigeria is the most populous country in Africa with a population of more than 200 million people. More than 500 languages are spoken in Nigeria and it is one of the most linguistically diverse countries in the world. Despite this, natural language processing (NLP) research has mostly focused on the following four languages: Hausa, Igbo, Nigerian-Pidgin, and Yoruba (i.e <1% of the languages spoken in Nigeria). This","authors":["Oluwadara Kalejaiye","Luel Hagos Beyene","David Ifeoluwa Adelani","Mmekut-Mfon Gabriel Edet","Aniefon Daniel Akpan","Eno-Abasi Urua"],"url":"http://arxiv.org/abs/2511.06531v1","arxiv_id":"2511.06531v1","published":"2025-11-09T20:33:39Z"},{"title":"TriShGAN: Enhancing Sparsity and Robustness in Multivariate Time Series Counterfactuals Explanation","abstract":"In decision-making processes, stakeholders often rely on counterfactual explanations, which provide suggestions about what should be changed in the queried instance to alter the outcome of an AI system. However, generating these explanations for multivariate time series presents challenges due to their complex, multi-dimensional nature. Traditional Nearest Unlike Neighbor-based methods typically substitute subsequenc","authors":["Hongnan Ma","Yiwei Shi","Guanxiong Sun","Mengyue Yang","Weiru Liu"],"url":"http://arxiv.org/abs/2511.06529v1","arxiv_id":"2511.06529v1","published":"2025-11-09T20:32:20Z"},{"title":"FractalBench: Diagnosing Visual-Mathematical Reasoning Through Recursive Program Synthesis","abstract":"Mathematical reasoning requires abstracting symbolic rules from visual patterns -- inferring the infinite from the finite. We investigate whether multimodal AI systems possess this capability through FractalBench, a benchmark evaluating fractal program synthesis from images. Fractals provide ideal test cases: Iterated Function Systems with only a few contraction maps generate complex self-similar patterns through sim","authors":["Jan Ondras","Marek Šuppa"],"url":"http://arxiv.org/abs/2511.06522v1","arxiv_id":"2511.06522v1","published":"2025-11-09T20:22:42Z"},{"title":"On the Analogy between Human Brain and LLMs: Spotting Key Neurons in Grammar Perception","abstract":"Artificial Neural Networks, the building blocks of AI, were inspired by the human brain's network of neurons. Over the years, these networks have evolved to replicate the complex capabilities of the brain, allowing them to handle tasks such as image and language processing. In the realm of Large Language Models, there has been a keen interest in making the language learning process more akin to that of humans. While ","authors":["Sanaz Saki Norouzi","Mohammad Masjedi","Pascal Hitzler"],"url":"http://arxiv.org/abs/2511.06519v1","arxiv_id":"2511.06519v1","published":"2025-11-09T20:08:21Z"},{"title":"Evo* 2025 -- Late-Breaking Abstracts Volume","abstract":"Volume containing the Late-Breaking Abstracts submitted to the Evo* 2025 Conference, held in Trieste (Italy) from April 23rd to 25th. These extended abstracts showcase ongoing research and preliminary findings exploring the application of various Bioinspired Methods (primarily Evolutionary Computation) to a range of problems, many of which address real-world scenarios.","authors":["A. M. Mora","A. I. Esparcia-Alcázar","M. S. Cruz"],"url":"http://arxiv.org/abs/2511.17543v1","arxiv_id":"2511.17543v1","published":"2025-11-09T19:16:04Z"},{"title":"Rethinking what Matters: Effective and Robust Multilingual Realignment for Low-Resource Languages","abstract":"Realignment is a promising strategy to improve cross-lingual transfer in multilingual language models. However, empirical results are mixed and often unreliable, particularly for typologically distant or low-resource languages (LRLs) compared to English. Moreover, word realignment tools often rely on high-quality parallel data, which can be scarce or noisy for many LRLs. In this work, we conduct an extensive empirica","authors":["Quang Phuoc Nguyen","David Anugraha","Felix Gaschi","Jun Bin Cheng","En-Shiun Annie Lee"],"url":"http://arxiv.org/abs/2511.06497v1","arxiv_id":"2511.06497v1","published":"2025-11-09T18:54:17Z"},{"title":"A Low-Rank Method for Vision Language Model Hallucination Mitigation in Autonomous Driving","abstract":"Vision Language Models (VLMs) are increasingly used in autonomous driving to help understand traffic scenes, but they sometimes produce hallucinations, which are false details not grounded in the visual input. Detecting and mitigating hallucinations is challenging when ground-truth references are unavailable and model internals are inaccessible. This paper proposes a novel self-contained low-rank approach to automati","authors":["Keke Long","Jiacheng Guo","Tianyun Zhang","Hongkai Yu","Xiaopeng Li"],"url":"http://arxiv.org/abs/2511.06496v1","arxiv_id":"2511.06496v1","published":"2025-11-09T18:50:30Z"},{"title":"Route Experts by Sequence, not by Token","abstract":"Mixture-of-Experts (MoE) architectures scale large language models (LLMs) by activating only a subset of experts per token, but the standard TopK routing assigns the same fixed number of experts to all tokens, ignoring their varying complexity. Prior adaptive routing methods introduce additional modules and hyperparameters, often requiring costly retraining from scratch. We propose Sequence-level TopK (SeqTopK), a mi","authors":["Tiansheng Wen","Yifei Wang","Aosong Feng","Long Ma","Xinyang Liu","Yifan Wang"],"url":"http://arxiv.org/abs/2511.06494v2","arxiv_id":"2511.06494v2","published":"2025-11-09T18:36:07Z"},{"title":"Explainable AI For Early Detection Of Sepsis","abstract":"Sepsis is a life-threatening condition that requires rapid detection and treatment to prevent progression to severe sepsis, septic shock, or multi-organ failure. Despite advances in medical technology, it remains a major challenge for clinicians. While recent machine learning models have shown promise in predicting sepsis onset, their black-box nature limits interpretability and clinical trust. In this study, we pres","authors":["Atharva Thakur","Shruti Dhumal"],"url":"http://arxiv.org/abs/2511.06492v1","arxiv_id":"2511.06492v1","published":"2025-11-09T18:33:06Z"},{"title":"Zooming into Comics: Region-Aware RL Improves Fine-Grained Comic Understanding in Vision-Language Models","abstract":"Complex visual narratives, such as comics, present a significant challenge to Vision-Language Models (VLMs). Despite excelling on natural images, VLMs often struggle with stylized line art, onomatopoeia, and densely packed multi-panel layouts. To address this gap, we introduce AI4VA-FG, the first fine-grained and comprehensive benchmark for VLM-based comic understanding. It spans tasks from foundational recognition a","authors":["Yule Chen","Yufan Ren","Sabine Süsstrunk"],"url":"http://arxiv.org/abs/2511.06490v1","arxiv_id":"2511.06490v1","published":"2025-11-09T18:27:45Z"},{"title":"Beyond Correctness: Confidence-Aware Reward Modeling for Enhancing Large Language Model Reasoning","abstract":"Recent advancements in large language models (LLMs) have shifted the post-training paradigm from traditional instruction tuning and human preference alignment toward reinforcement learning (RL) focused on reasoning capabilities. However, numerous technical reports indicate that purely rule-based reward RL frequently results in poor-quality reasoning chains or inconsistencies between reasoning processes and final answ","authors":["Qianxi He","Qingyu Ren","Shanzhe Lei","Xuhong Wang","Yingchun Wang"],"url":"http://arxiv.org/abs/2511.07483v1","arxiv_id":"2511.07483v1","published":"2025-11-09T17:58:40Z"},{"title":"GHOST: Solving the Traveling Salesman Problem on Graphs of Convex Sets","abstract":"We study GCS-TSP, a new variant of the Traveling Salesman Problem (TSP) defined over a Graph of Convex Sets (GCS) -- a powerful representation for trajectory planning that decomposes the configuration space into convex regions connected by a sparse graph. In this setting, edge costs are not fixed but depend on the specific trajectory selected through each convex region, making classical TSP methods inapplicable. We i","authors":["Jingtao Tang","Hang Ma"],"url":"http://arxiv.org/abs/2511.06471v2","arxiv_id":"2511.06471v2","published":"2025-11-09T17:34:15Z"},{"title":"Brain-Inspired Planning for Better Generalization in Reinforcement Learning","abstract":"Existing Reinforcement Learning (RL) systems encounter significant challenges when applied to real-world scenarios, primarily due to poor generalization across environments that differ from their training conditions. This thesis explores the direction of enhancing agents' zero-shot systematic generalization abilities by granting RL agents reasoning behaviors that are found to help systematic generalization in the hum","authors":["Mingde \"Harry\" Zhao"],"url":"http://arxiv.org/abs/2511.06470v1","arxiv_id":"2511.06470v1","published":"2025-11-09T17:32:55Z"},{"title":"EchoMark: Perceptual Acoustic Environment Transfer with Watermark-Embedded Room Impulse Response","abstract":"Acoustic Environment Matching (AEM) is the task of transferring clean audio into a target acoustic environment, enabling engaging applications such as audio dubbing and auditory immersive virtual reality (VR). Recovering similar room impulse response (RIR) directly from reverberant speech offers more accessible and flexible AEM solution. However, this capability also introduces vulnerabilities of arbitrary ``relocati","authors":["Chenpei Huang","Lingfeng Yao","Kyu In Lee","Lan Emily Zhang","Xun Chen","Miao Pan"],"url":"http://arxiv.org/abs/2511.06458v2","arxiv_id":"2511.06458v2","published":"2025-11-09T16:53:32Z"},{"title":"Alignment-Constrained Dynamic Pruning for LLMs: Identifying and Preserving Alignment-Critical Circuits","abstract":"Large Language Models require substantial computational resources for inference, posing deployment challenges. While dynamic pruning offers superior efficiency over static methods through adaptive circuit selection, it exacerbates alignment degradation by retaining only input-dependent safety-critical circuit preservation across diverse inputs. As a result, addressing these heightened alignment vulnerabilities remain","authors":["Dev Patel","Gabrielle Gervacio","Diekola Raimi","Kevin Zhu","Ryan Lagasse","Gabriel Grand"],"url":"http://arxiv.org/abs/2511.07482v1","arxiv_id":"2511.07482v1","published":"2025-11-09T16:51:45Z"},{"title":"A Multi-Agent System for Semantic Mapping of Relational Data to Knowledge Graphs","abstract":"Enterprises often maintain multiple databases for storing critical business data in siloed systems, resulting in inefficiencies and challenges with data interoperability. A key to overcoming these challenges lies in integrating disparate data sources, enabling businesses to unlock the full potential of their data. Our work presents a novel approach for integrating multiple databases using knowledge graphs, focusing o","authors":["Milena Trajanoska","Riste Stojanov","Dimitar Trajanov"],"url":"http://arxiv.org/abs/2511.06455v1","arxiv_id":"2511.06455v1","published":"2025-11-09T16:41:46Z"},{"title":"FLEX: Continuous Agent Evolution via Forward Learning from Experience","abstract":"Autonomous agents driven by Large Language Models (LLMs) have revolutionized reasoning and problem-solving but remain static after training, unable to grow with experience as intelligent beings do during deployment. We introduce Forward Learning with EXperience (FLEX), a gradient-free learning paradigm that enables LLM agents to continuously evolve through accumulated experience. Specifically, FLEX cultivates scalabl","authors":["Zhicheng Cai","Xinyuan Guo","Yu Pei","Jiangtao Feng","Jinsong Su","Jiangjie Chen"],"url":"http://arxiv.org/abs/2511.06449v2","arxiv_id":"2511.06449v2","published":"2025-11-09T16:31:39Z"},{"title":"When AI Agents Collude Online: Financial Fraud Risks by Collaborative LLM Agents on Social Platforms","abstract":"In this work, we study the risks of collective financial fraud in large-scale multi-agent systems powered by large language model (LLM) agents. We investigate whether agents can collaborate in fraudulent behaviors, how such collaboration amplifies risks, and what factors influence fraud success. To support this research, we present MultiAgentFraudBench, a large-scale benchmark for simulating financial fraud scenarios","authors":["Qibing Ren","Zhijie Zheng","Jiaxuan Guo","Junchi Yan","Lizhuang Ma","Jing Shao"],"url":"http://arxiv.org/abs/2511.06448v2","arxiv_id":"2511.06448v2","published":"2025-11-09T16:30:44Z"}],"history":{"events":[{"year":2019,"text":"Pakistani prime minister Imran Khan inaugurated the Kartarpur Corridor, a visa-free border crossing connecting the Gurdwara Darbar Sahib to the India–Pakistan border.","url":"https://en.wikipedia.org/wiki/Imran_Khan"},{"year":2019,"text":"The Alabama Crimson Tide and LSU Tigers football teams, both with undefeated records thus far that season, played in a \"Game of the Century\".","url":"https://en.wikipedia.org/wiki/Alabama_Crimson_Tide_football"},{"year":2016,"text":"A tram derailment in Croydon, London, killed seven people.","url":"https://en.wikipedia.org/wiki/2016_Croydon_tram_derailment"},{"year":1993,"text":"Bosnian War: Croatian Defence Council forces destroyed the Stari Most, a 16th-century bridge crossing the river Neretva in the city of Mostar (rebuilt bridge pictured).","url":"https://en.wikipedia.org/wiki/Bosnian_War"},{"year":1989,"text":"East German official Günter Schabowski mistakenly announced the immediate opening of the inner German border, resulting in the fall of the Berlin Wall that night (border crossing pictured).","url":"https://en.wikipedia.org/wiki/G%C3%BCnter_Schabowski"},{"year":1985,"text":"At age 22, Garry Kasparov became the then-youngest World Chess Champion by defeating then-champion Anatoly Karpov.","url":"https://en.wikipedia.org/wiki/Garry_Kasparov"},{"year":1967,"text":"The first issue of Rolling Stone, an American magazine focusing on music, politics and popular culture, was published.","url":"https://en.wikipedia.org/wiki/Rolling_Stone"},{"year":1939,"text":"World War II: A covert Sicherheitsdienst operation captured two British agents of the Secret Intelligence Service near Venlo in the Netherlands.","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1938,"text":"Kristallnacht began as SA stormtroopers and civilians destroyed and ransacked Jewish homes, businesses and synagogues in Germany and Austria, resulting in at least 90 deaths and the deportation of 30,000 men to concentration camps.","url":"https://en.wikipedia.org/wiki/Kristallnacht"},{"year":1928,"text":"The Great Mecca Feast, the first documentary film on the Hajj, premiered in the Netherlands.","url":"https://en.wikipedia.org/wiki/The_Great_Mecca_Feast"},{"year":1918,"text":"The government of the Azerbaijan Democratic Republic adopted a tricolour national flag (pictured), which is again in use today, with slight modifications, by the present-day Republic of Azerbaijan.","url":"https://en.wikipedia.org/wiki/Azerbaijan_Democratic_Republic"},{"year":1914,"text":"World War I: Off the Cocos (Keeling) Islands, the Australian light cruiser Sydney sank Emden, the last active German warship in the Indian Ocean, at the Battle of Cocos.","url":"https://en.wikipedia.org/wiki/World_War_I"},{"year":1913,"text":"A severe blizzard reached its maximum intensity in the Great Lakes Basin of North America, destroying 19 ships and 68,300 tons of cargo, and killing more than 250 people.","url":"https://en.wikipedia.org/wiki/Great_Lakes_Storm_of_1913"},{"year":1888,"text":"Mary Jane Kelly, widely believed to be the fifth and final victim of the notorious unidentified serial killer Jack the Ripper, was murdered in London.","url":"https://en.wikipedia.org/wiki/Mary_Jane_Kelly"},{"year":1822,"text":"USS Alligator engaged three pirate schooners off the coast of Cuba in one of the West Indies anti-piracy operations of the United States.","url":"https://en.wikipedia.org/wiki/USS_Alligator_(1820)"}],"births":[{"year":1999,"text":"Prithvi Shaw, Indian cricketer","url":"https://en.wikipedia.org/wiki/Prithvi_Shaw"},{"year":1996,"text":"Momo Hirai, Japanese dancer and singer","url":"https://en.wikipedia.org/wiki/Momo_Hirai"},{"year":1995,"text":"Finn Cole, English actor","url":"https://en.wikipedia.org/wiki/Finn_Cole"},{"year":1995,"text":"Daniel Naroditsky, American chess grandmaster (died 2025)","url":"https://en.wikipedia.org/wiki/Daniel_Naroditsky"},{"year":1994,"text":"Lyrica Okano, American actress","url":"https://en.wikipedia.org/wiki/Lyrica_Okano"},{"year":1993,"text":"Pete Dunne, English wrestler","url":"https://en.wikipedia.org/wiki/Pete_Dunne"},{"year":1990,"text":"Nosa Igiebor, Nigerian footballer","url":"https://en.wikipedia.org/wiki/Nosa_Igiebor"},{"year":1989,"text":"Baptiste Giabiconi, French model and singer","url":"https://en.wikipedia.org/wiki/Baptiste_Giabiconi"}],"deaths":[{"year":2024,"text":"Bobby Allison, American race car driver and businessman (born 1937)","url":"https://en.wikipedia.org/wiki/Bobby_Allison"},{"year":2024,"text":"Lou Donaldson, American saxophonist (born 1926)","url":"https://en.wikipedia.org/wiki/Lou_Donaldson"},{"year":2024,"text":"Judith Jamison, American dancer and choreographer (born 1943)","url":"https://en.wikipedia.org/wiki/Judith_Jamison"},{"year":2024,"text":"Ella Jenkins, American folk singer (born 1924)","url":"https://en.wikipedia.org/wiki/Ella_Jenkins"},{"year":2023,"text":"Junko Ohashi, Japanese singer (born 1950)","url":"https://en.wikipedia.org/wiki/Junko_Ohashi"},{"year":2021,"text":"Max Cleland, American politician (born 1942)","url":"https://en.wikipedia.org/wiki/Max_Cleland"},{"year":2017,"text":"Chuck Mosley, American singer songwriter (born 1959)","url":"https://en.wikipedia.org/wiki/Chuck_Mosley"},{"year":2017,"text":"Shyla Stylez, Canadian pornographic actress (born 1982)","url":"https://en.wikipedia.org/wiki/Shyla_Stylez"}]},"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 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Every item links to its source."}