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Despite their remarkable progress, further capabilities are expected in order to achieve more general types of intelligence. A critical distinction in this context is between factual knowledge, which can be evaluated against true or false answers (e.g., \"what is t","authors":["Drago Plecko","Patrik Okanovic","Shreyas Havaldar","Torsten Hoefler","Elias Bareinboim"],"url":"http://arxiv.org/abs/2511.03070v2","arxiv_id":"2511.03070v2","published":"2025-11-04T23:34:52Z"},{"title":"Reading Between the Lines: The One-Sided Conversation Problem","abstract":"Conversational AI is constrained in many real-world settings where only one side of a dialogue can be recorded, such as telemedicine, call centers, and smart glasses. We formalize this as the one-sided conversation problem (1SC): inferring and learning from one side of a conversation. We study two tasks: (1) reconstructing the missing speaker's turns for real-time use cases, and (2) generating summaries from one-side","authors":["Victoria Ebert","Rishabh Singh","Tuochao Chen","Noah A. Smith","Shyamnath Gollakota"],"url":"http://arxiv.org/abs/2511.03056v2","arxiv_id":"2511.03056v2","published":"2025-11-04T22:53:57Z"},{"title":"No-Human in the Loop: Agentic Evaluation at Scale for Recommendation","abstract":"Evaluating large language models (LLMs) as judges is increasingly critical for building scalable and trustworthy evaluation pipelines. We present ScalingEval, a large-scale benchmarking study that systematically compares 36 LLMs, including GPT, Gemini, Claude, and Llama, across multiple product categories using a consensus-driven evaluation protocol. Our multi-agent framework aggregates pattern audits and issue codes","authors":["Tao Zhang","Kehui Yao","Luyi Ma","Jiao Chen","Reza Yousefi Maragheh","Kai Zhao"],"url":"http://arxiv.org/abs/2511.03051v1","arxiv_id":"2511.03051v1","published":"2025-11-04T22:49:39Z"},{"title":"Fine-Tuning Vision-Language Models for Multimodal Polymer Property Prediction","abstract":"Vision-Language Models (VLMs) have shown strong performance in tasks like visual question answering and multimodal text generation, but their effectiveness in scientific domains such as materials science remains limited. While some machine learning methods have addressed specific challenges in this field, there is still a lack of foundation models designed for broad tasks like polymer property prediction using multim","authors":["An Vuong","Minh-Hao Van","Prateek Verma","Chen Zhao","Xintao Wu"],"url":"http://arxiv.org/abs/2511.05577v1","arxiv_id":"2511.05577v1","published":"2025-11-04T22:32:53Z"},{"title":"Federated Learning with Gramian Angular Fields for Privacy-Preserving ECG Classification on Heterogeneous IoT Devices","abstract":"This study presents a federated learning (FL) framework for privacy-preserving electrocardiogram (ECG) classification in Internet of Things (IoT) healthcare environments. By transforming 1D ECG signals into 2D Gramian Angular Field (GAF) images, the proposed approach enables efficient feature extraction through Convolutional Neural Networks (CNNs) while ensuring that sensitive medical data remain local to each device","authors":["Youssef Elmir","Yassine Himeur","Abbes Amira"],"url":"http://arxiv.org/abs/2511.03753v2","arxiv_id":"2511.03753v2","published":"2025-11-04T22:23:59Z"},{"title":"PublicAgent: Multi-Agent Design Principles From an LLM-Based Open Data Analysis Framework","abstract":"Open data repositories hold potential for evidence-based decision-making, yet are inaccessible to non-experts lacking expertise in dataset discovery, schema mapping, and statistical analysis. Large language models show promise for individual tasks, but end-to-end analytical workflows expose fundamental limitations: attention dilutes across growing contexts, specialized reasoning patterns interfere, and errors propaga","authors":["Sina Montazeri","Yunhe Feng","Kewei Sha"],"url":"http://arxiv.org/abs/2511.03023v1","arxiv_id":"2511.03023v1","published":"2025-11-04T21:48:11Z"},{"title":"Adaptive-Sensorless Monitoring of Shipping Containers","abstract":"Monitoring the internal temperature and humidity of shipping containers is essential to preventing quality degradation during cargo transportation. Sensorless monitoring -- machine learning models that predict the internal conditions of the containers using exogenous factors -- shows promise as an alternative to monitoring using sensors. However, it does not incorporate telemetry information and correct for systemati","authors":["Lingqing Shen","Chi Heem Wong","Misaki Mito","Arnab Chakrabarti"],"url":"http://arxiv.org/abs/2511.03022v1","arxiv_id":"2511.03022v1","published":"2025-11-04T21:47:00Z"},{"title":"Exploratory Analysis of Cyberattack Patterns on E-Commerce Platforms Using Statistical Methods","abstract":"Cyberattacks on e-commerce platforms have grown in sophistication, threatening consumer trust and operational continuity. This research presents a hybrid analytical framework that integrates statistical modelling and machine learning for detecting and forecasting cyberattack patterns in the e-commerce domain. Using the Verizon Community Data Breach (VCDB) dataset, the study applies Auto ARIMA for temporal forecasting","authors":["Fatimo Adenike Adeniya"],"url":"http://arxiv.org/abs/2511.03020v1","arxiv_id":"2511.03020v1","published":"2025-11-04T21:38:59Z"},{"title":"SLIP: Structural-aware Language-Image Pretraining for Vision-Language Alignment","abstract":"Vision-Language Pretraining (VLP) has achieved remarkable success across various downstream tasks, but such gains are largely driven by scaling up on training data. Yet, literature methods treat image-text pairs as isolated training examples; this neglects the rich relational structure naturally present in many domains, such as e-commerce product co-purchase graphs and social recommendation networks. Inspired by neur","authors":["Wenbo Lu"],"url":"http://arxiv.org/abs/2511.03019v1","arxiv_id":"2511.03019v1","published":"2025-11-04T21:33:57Z"},{"title":"Prioritize Economy or Climate Action? Investigating ChatGPT Response Differences Based on Inferred Political Orientation","abstract":"Large Language Models (LLMs) distinguish themselves by quickly delivering information and providing personalized responses through natural language prompts. However, they also infer user demographics, which can raise ethical concerns about bias and implicit personalization and create an echo chamber effect. This study aims to explore how inferred political views impact the responses of ChatGPT globally, regardless of","authors":["Pelin Karadal","Dilara Kekulluoglu"],"url":"http://arxiv.org/abs/2511.04706v1","arxiv_id":"2511.04706v1","published":"2025-11-04T21:07:01Z"},{"title":"Evaluating Control Protocols for Untrusted AI Agents","abstract":"As AI systems become more capable and widely deployed as agents, ensuring their safe operation becomes critical. AI control offers one approach to mitigating the risk from untrusted AI agents by monitoring their actions and intervening or auditing when necessary. Evaluating the safety of these protocols requires understanding both their effectiveness against current attacks and their robustness to adaptive adversarie","authors":["Jon Kutasov","Chloe Loughridge","Yuqi Sun","Henry Sleight","Buck Shlegeris","Tyler Tracy"],"url":"http://arxiv.org/abs/2511.02997v1","arxiv_id":"2511.02997v1","published":"2025-11-04T21:04:49Z"},{"title":"Systematizing LLM Persona Design: A Four-Quadrant Technical Taxonomy for AI Companion Applications","abstract":"The design and application of LLM-based personas in AI companionship is a rapidly expanding but fragmented field, spanning from virtual emotional companions and game NPCs to embodied functional robots. This diversity in objectives, modality, and technical stacks creates an urgent need for a unified framework. To address this gap, this paper systematizes the field by proposing a Four-Quadrant Technical Taxonomy for AI","authors":["Esther Sun","Zichu Wu"],"url":"http://arxiv.org/abs/2511.02979v2","arxiv_id":"2511.02979v2","published":"2025-11-04T20:37:13Z"},{"title":"Value of Information-Enhanced Exploration in Bootstrapped DQN","abstract":"Efficient exploration in deep reinforcement learning remains a fundamental challenge, especially in environments characterized by high-dimensional states and sparse rewards. Traditional exploration strategies that rely on random local policy noise, such as $ε$-greedy and Boltzmann exploration methods, often struggle to efficiently balance exploration and exploitation. In this paper, we integrate the notion of (expect","authors":["Stergios Plataniotis","Charilaos Akasiadis","Georgios Chalkiadakis"],"url":"http://arxiv.org/abs/2511.02969v2","arxiv_id":"2511.02969v2","published":"2025-11-04T20:22:58Z"},{"title":"EvtSlowTV -- A Large and Diverse Dataset for Event-Based Depth Estimation","abstract":"Event cameras, with their high dynamic range (HDR) and low latency, offer a promising alternative for robust depth estimation in challenging environments. However, many event-based depth estimation approaches are constrained by small-scale annotated datasets, limiting their generalizability to real-world scenarios. To bridge this gap, we introduce EvtSlowTV, a large-scale event camera dataset curated from publicly av","authors":["Sadiq Layi Macaulay","Nimet Kaygusuz","Simon Hadfield"],"url":"http://arxiv.org/abs/2511.02953v1","arxiv_id":"2511.02953v1","published":"2025-11-04T19:56:26Z"},{"title":"Power Constrained Nonstationary Bandits with Habituation and Recovery Dynamics","abstract":"A common challenge for decision makers is selecting actions whose rewards are unknown and evolve over time based on prior policies. For instance, repeated use may reduce an action's effectiveness (habituation), while inactivity may restore it (recovery). These nonstationarities are captured by the Reducing or Gaining Unknown Efficacy (ROGUE) bandit framework, which models real-world settings such as behavioral health","authors":["Fengxu Li","Stephanie M. Carpenter","Matthew P. Buman","Yonatan Mintz"],"url":"http://arxiv.org/abs/2511.02944v1","arxiv_id":"2511.02944v1","published":"2025-11-04T19:46:42Z"},{"title":"From Narrow to Wide: Autoencoding Transformers for Ultrasound Bandwidth Recovery","abstract":"Conventional pulse-echo ultrasound suffers when low-cost probes deliver only narrow fractional bandwidths, elongating pulses and erasing high-frequency detail. We address this limitation by learning a data-driven mapping from band-limited to broadband spectrogram of radio-frequency (RF) lines. To this end, a variation of Tiny Vision Transform (ViT) auto-encoder is trained on simulation data using a curriculum-weighte","authors":["Sepideh KhakzadGharamaleki","Hassan Rivaz","Brandon Helfield"],"url":"http://arxiv.org/abs/2511.02938v1","arxiv_id":"2511.02938v1","published":"2025-11-04T19:34:18Z"},{"title":"Zero-shot data citation function classification using transformer-based large language models (LLMs)","abstract":"Efforts have increased in recent years to identify associations between specific datasets and the scientific literature that incorporates them. Knowing that a given publication cites a given dataset, the next logical step is to explore how or why that data was used. Advances in recent years with pretrained, transformer-based large language models (LLMs) offer potential means for scaling the description of data use ca","authors":["Neil Byers","Ali Zaidi","Valerie Skye","Chris Beecroft","Kjiersten Fagnan"],"url":"http://arxiv.org/abs/2511.02936v1","arxiv_id":"2511.02936v1","published":"2025-11-04T19:33:30Z"},{"title":"DualLaguerreNet: A Decoupled Spectral Filter GNN and the Uncovering of the Flexibility-Stability Trade-off","abstract":"Graph Neural Networks (GNNs) based on spectral filters, such as the Adaptive Orthogonal Polynomial Filter (AOPF) class (e.g., LaguerreNet), have shown promise in unifying the solutions for heterophily and over-smoothing. However, these single-filter models suffer from a \"compromise\" problem, as their single adaptive parameter (e.g., alpha) must learn a suboptimal, averaged response across the entire graph spectrum. I","authors":["Huseyin Goksu"],"url":"http://arxiv.org/abs/2511.13729v1","arxiv_id":"2511.13729v1","published":"2025-11-04T19:33:29Z"},{"title":"Generative Hints","abstract":"Data augmentation is widely used in vision to introduce variation and mitigate overfitting, by enabling models to learn invariant properties. However, augmentation only indirectly captures these properties and does not explicitly constrain the learned function to satisfy them beyond the empirical training set. We propose generative hints, a training methodology that directly enforces known functional invariances over","authors":["Andy Dimnaku","Abdullah Yusuf Kavranoglu","Yaser Abu-Mostafa"],"url":"http://arxiv.org/abs/2511.02933v2","arxiv_id":"2511.02933v2","published":"2025-11-04T19:31:36Z"},{"title":"Agent-Omni: Test-Time Multimodal Reasoning via Model Coordination for Understanding Anything","abstract":"Multimodal large language models (MLLMs) have shown strong capabilities but remain limited to fixed modality pairs and require costly fine-tuning with large aligned datasets. Building fully omni-capable models that can integrate text, images, audio, and video remains impractical and lacks robust reasoning support. In this paper, we propose an Agent-Omni framework that coordinates existing foundation models through a ","authors":["Huawei Lin","Yunzhi Shi","Tong Geng","Weijie Zhao","Wei Wang","Ravender Pal Singh"],"url":"http://arxiv.org/abs/2511.02834v2","arxiv_id":"2511.02834v2","published":"2025-11-04T18:59:09Z"},{"title":"Neurosymbolic Deep Learning Semantics","abstract":"Artificial Intelligence (AI) is a powerful new language of science as evidenced by recent Nobel Prizes in chemistry and physics that recognized contributions to AI applied to those areas. Yet, this new language lacks semantics, which makes AI's scientific discoveries unsatisfactory at best. With the purpose of uncovering new facts but also improving our understanding of the world, AI-based science requires formalizat","authors":["Artur d'Avila Garcez","Simon Odense"],"url":"http://arxiv.org/abs/2511.02825v1","arxiv_id":"2511.02825v1","published":"2025-11-04T18:51:04Z"},{"title":"Kosmos: An AI Scientist for Autonomous Discovery","abstract":"Data-driven scientific discovery requires iterative cycles of literature search, hypothesis generation, and data analysis. Substantial progress has been made towards AI agents that can automate scientific research, but all such agents remain limited in the number of actions they can take before losing coherence, thus limiting the depth of their findings. Here we present Kosmos, an AI scientist that automates data-dri","authors":["Ludovico Mitchener","Angela Yiu","Benjamin Chang","Mathieu Bourdenx","Tyler Nadolski","Arvis Sulovari"],"url":"http://arxiv.org/abs/2511.02824v2","arxiv_id":"2511.02824v2","published":"2025-11-04T18:50:52Z"},{"title":"Optimizing AI Agent Attacks With Synthetic Data","abstract":"As AI deployments become more complex and high-stakes, it becomes increasingly important to be able to estimate their risk. AI control is one framework for doing so. However, good control evaluations require eliciting strong attack policies. This can be challenging in complex agentic environments where compute constraints leave us data-poor. In this work, we show how to optimize attack policies in SHADE-Arena, a data","authors":["Chloe Loughridge","Paul Colognese","Avery Griffin","Tyler Tracy","Jon Kutasov","Joe Benton"],"url":"http://arxiv.org/abs/2511.02823v1","arxiv_id":"2511.02823v1","published":"2025-11-04T18:48:56Z"},{"title":"Orion-MSP: Multi-Scale Sparse Attention for Tabular In-Context Learning","abstract":"Tabular data remain the predominant format for real-world applications. Yet, developing effective neural models for tabular data remains challenging due to heterogeneous feature types and complex interactions occurring at multiple scales. Recent advances in tabular in-context learning (ICL), such as TabPFN and TabICL, have achieved state-of-the-art performance comparable to gradient-boosted trees (GBTs) without task-","authors":["Mohamed Bouadi","Pratinav Seth","Aditya Tanna","Vinay Kumar Sankarapu"],"url":"http://arxiv.org/abs/2511.02818v3","arxiv_id":"2511.02818v3","published":"2025-11-04T18:43:44Z"},{"title":"Oolong: Evaluating Long Context Reasoning and Aggregation Capabilities","abstract":"As model context lengths continue to grow, concerns about whether models effectively use the full context length have persisted. While several carefully designed long-context evaluations have recently been released, these evaluations tend to rely on retrieval from one or more sections of the context, which allows nearly all of the context tokens to be disregarded as noise. This represents only one type of task that m","authors":["Amanda Bertsch","Adithya Pratapa","Teruko Mitamura","Graham Neubig","Matthew R. Gormley"],"url":"http://arxiv.org/abs/2511.02817v1","arxiv_id":"2511.02817v1","published":"2025-11-04T18:42:12Z"}],"history":{"events":[{"year":2025,"text":"A UPS Airlines plane crashed in Louisville, Kentucky, killing at least twelve people.","url":"https://en.wikipedia.org/wiki/UPS_Airlines"},{"year":2016,"text":"The Paris Agreement, under the United Nations Framework Convention on Climate Change, came into effect.","url":"https://en.wikipedia.org/wiki/Paris_Agreement"},{"year":2010,"text":"In the first aviation incident involving an Airbus A380, Qantas Flight 32 suffered an uncontained engine failure and made an emergency landing at Changi Airport in Singapore with no casualties.","url":"https://en.wikipedia.org/wiki/Aviation_accidents_and_incidents"},{"year":2008,"text":"Barack Obama (pictured) became the first person of biracial or African-American descent to be elected President of the United States.","url":"https://en.wikipedia.org/wiki/Barack_Obama"},{"year":1995,"text":"Israeli prime minister Yitzhak Rabin (pictured) was assassinated by Yigal Amir, a right-wing extremist, at a peace rally at Kings of Israel Square in Tel Aviv.","url":"https://en.wikipedia.org/wiki/Yitzhak_Rabin"},{"year":1970,"text":"Authorities in California discovered a 13-year-old feral child, pseudonymously known as Genie, who had spent nearly her entire life in social isolation.","url":"https://en.wikipedia.org/wiki/Feral_child"},{"year":1964,"text":"Ruhollah Khomeini was arrested by SAVAK, the Iranian secret police, and exiled to Turkey.","url":"https://en.wikipedia.org/wiki/Ruhollah_Khomeini"},{"year":1952,"text":"Robert A. Lovett, United States Secretary of Defense, issued a memorandum establishing the National Security Agency, with responsibility for all communications intelligence for the government.","url":"https://en.wikipedia.org/wiki/Robert_A._Lovett"},{"year":1944,"text":"Second World War: Allied forces completed Operation Pheasant, a major operation to clear German troops from the province of North Brabant in the Netherlands.","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1938,"text":"The Hlinka Guard and Slovakian police began the deportation of several thousand Jews from the country.","url":"https://en.wikipedia.org/wiki/Hlinka_Guard"},{"year":1924,"text":"In a special election in Wyoming, Nellie Tayloe Ross became the first woman to be elected as a governor in the United States.","url":"https://en.wikipedia.org/wiki/1924_Wyoming_gubernatorial_special_election"},{"year":1922,"text":"The tomb of Tutankhamun (pictured) was discovered by a team led by British Egyptologist Howard Carter.","url":"https://en.wikipedia.org/wiki/Tomb_of_Tutankhamun"},{"year":1921,"text":"The remains of an unknown soldier were buried with an eternal flame at the Altare della Patria in Rome.","url":"https://en.wikipedia.org/wiki/Tomb_of_the_Unknown_Soldier_(Italy)"},{"year":1912,"text":"The keel of USS Nevada was laid down, beginning construction on the United States Navy's first \"super-dreadnought\".","url":"https://en.wikipedia.org/wiki/Keel"},{"year":1890,"text":"The City and South London Railway (carriage pictured), the first deep-level underground railway in the world, officially opened, running 3.2 mi (5.1 km) between the City of London and Stockwell.","url":"https://en.wikipedia.org/wiki/City_and_South_London_Railway"},{"year":1864,"text":"American Civil War: Nathan Bedford Forrest led a cavalry division in an attack on a Union Army supply base at Johnsonville, Tennessee, resulting in the capture of 150 prisoners.","url":"https://en.wikipedia.org/wiki/American_Civil_War"},{"year":1780,"text":"Túpac Amaru II led a rebellion of Aymara, Quechua, and mestizo peasants in protest against the Bourbon Reforms in the Spanish Viceroyalty of Peru.","url":"https://en.wikipedia.org/wiki/T%C3%BApac_Amaru_II"}],"births":[{"year":2006,"text":"Darja Varfolomeev, Russian-German rhythmic gymnast","url":"https://en.wikipedia.org/wiki/Darja_Varfolomeev"},{"year":2000,"text":"Tyrese Maxey, American basketball player","url":"https://en.wikipedia.org/wiki/Tyrese_Maxey"},{"year":2000,"text":"Sun Yingsha, Chinese table tennis player","url":"https://en.wikipedia.org/wiki/Sun_Yingsha"},{"year":1999,"text":"Emma Maltais, Canadian ice hockey player","url":"https://en.wikipedia.org/wiki/Emma_Maltais"},{"year":1998,"text":"Achraf Hakimi, Moroccan footballer","url":"https://en.wikipedia.org/wiki/Achraf_Hakimi"},{"year":1996,"text":"Kaitlin Hawayek, American ice dancer","url":"https://en.wikipedia.org/wiki/Kaitlin_Hawayek"},{"year":1996,"text":"Michael Christian Martinez, Filipino figure skater","url":"https://en.wikipedia.org/wiki/Michael_Christian_Martinez"},{"year":1996,"text":"John Olive, Australian rugby league player","url":"https://en.wikipedia.org/wiki/John_Olive_(rugby_league)"}],"deaths":[{"year":2024,"text":"Bernard Marcus, American billionaire businessman and philanthropist (born 1929)","url":"https://en.wikipedia.org/wiki/Bernard_Marcus"},{"year":2024,"text":"Murray Sinclair, Canadian lawyer and politician (born 1951)","url":"https://en.wikipedia.org/wiki/Murray_Sinclair"},{"year":2023,"text":"Akbar Golpayegani, Iranian vocalist (born 1934)","url":"https://en.wikipedia.org/wiki/Akbar_Golpayegani"},{"year":2020,"text":"Ken Hensley, English rock singer-songwriter and musician (born 1945)","url":"https://en.wikipedia.org/wiki/Ken_Hensley"},{"year":2019,"text":"Gay Byrne, Irish broadcaster (born 1934)","url":"https://en.wikipedia.org/wiki/Gay_Byrne"},{"year":2017,"text":"Isabel Granada, Filipino-Spanish actress and singer (born 1976)","url":"https://en.wikipedia.org/wiki/Isabel_Granada"},{"year":2017,"text":"Ned Romero, American actor and opera singer (born 1926)","url":"https://en.wikipedia.org/wiki/Ned_Romero"},{"year":2016,"text":"Catherine Davani, first female Papua New Guinean judge (born 1960)","url":"https://en.wikipedia.org/wiki/Catherine_Davani"}]},"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."}