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We present Pixel-UMI, a pipeline for learning environment-aware whole-body policies from human data. We first introduce Environment-Aware Retargeting (EAR), which combines reconstructed scene geometry with demonstrated head and gripper trajectories to determine robot posture and generate","authors":["Jason Jingzhou Liu","Tony Tao","Deepak Pathak","Ruslan Salakhutdinov"],"url":"https://arxiv.org/abs/2611.03647v1","arxiv_id":"2611.03647v1","published":"2026-11-02T18:59:32Z"},{"title":"Pixel: A Co-Designed Full-Stack Robot System for Learning General-Purpose Mobile Manipulation","abstract":"General-purpose mobile manipulation requires a combination of capable robot hardware, scalable demonstration collection, expressive whole-body control, and effective policy learning. Yet these components are often developed independently, creating mismatches that limit the capabilities of the complete system. We present Pixel, a co-designed full-stack system for learning general-purpose mobile manipulation. Pixel com","authors":["Tony Tao","Jason Jingzhou Liu","Ruslan Salakhutdinov","Deepak Pathak"],"url":"https://arxiv.org/abs/2611.03648v1","arxiv_id":"2611.03648v1","published":"2026-11-02T18:59:32Z"},{"title":"From Natural Language to Exact Cover: A Neuro-Symbolic Approach to Zebra Puzzles","abstract":"Chain-of-Thought (CoT) generation has substantially improved the performance of Large Language Models (LLMs) on complex reasoning tasks, including code generation, data analysis, and exam-style question answering. Despite these advances, purely neural LLMs continue to struggle with elementary logical reasoning problems and lack the determinism, soundness, and reliability characteristic of symbolic reasoning systems. ","authors":["Paulius Skaisgiris","Thomas Pammer","Veronika Semmelrock","Mykyta Ielanskyi","Maximilian Heisinger","Erich Kobler"],"url":"https://arxiv.org/abs/2611.03641v1","arxiv_id":"2611.03641v1","published":"2026-11-02T18:58:21Z"},{"title":"WebHarbor: Docking Real Websites for Evolving GUI Agent Environments","abstract":"GUI web agents require realistic and interactive environments that remain stable during both evaluation and training. Live website evaluation suffers from changing content, access restrictions, and limited coverage of authenticated workflows, while existing synthetic environments for training often lack functional depth and visual fidelity. We propose WebHarbor, a suite of 153 executable and dockerized website enviro","authors":["Zhaoyang Wang","Qianhui Wu","Boyu Gou","Demi Wang","Jiacheng Zhang","Peichun Hua"],"url":"https://arxiv.org/abs/2611.03634v1","arxiv_id":"2611.03634v1","published":"2026-11-02T18:57:36Z"},{"title":"D&A: Decoupling Description and Assessment Enables VLMs as Zero-Shot Robotic Reward Models","abstract":"Vision-Language Models (VLMs) hold promise for zero-shot video task-progress estimation in robot learning, yet existing frameworks frequently suffer from confirmation bias, hallucinating progress in failed executions due to implicit success assumptions or relative temporal ranking designs. Naive prompting of frontier models collapses into a binary success detector that fails to capture nuanced, non-linear progress an","authors":["Marius Memmel","Shawn Yin","Urvi Rutia","Angad Wadhwa","Eldon Li","Gavin Angeloff"],"url":"https://arxiv.org/abs/2611.03622v1","arxiv_id":"2611.03622v1","published":"2026-11-02T18:52:11Z"},{"title":"Strategist: Evolving Reasoning with Agents","abstract":"A model is only half of an AI agent system. The other half is the inference strategy: the reasoning procedure that turns model calls into a response. Today that second half is written by hand, and the experience of building one strategy never carries to the next. We introduce Strategist, a meta-agent that evolves inference strategies across tasks. Each strategy is written as a blueprint,executable code that other str","authors":["Taiming Lu","Qi Xu","Zhigang Hua","Zhuang Liu"],"url":"https://arxiv.org/abs/2611.03618v1","arxiv_id":"2611.03618v1","published":"2026-11-02T18:51:04Z"},{"title":"Tracing the Scientific Discovery Capacity of LLMs to Their Training Data","abstract":"Large language models (LLMs) show growing promise for scientific discovery, yet basic questions remain about what enables reliable discovery. How can we trace the scientific discovery capacity of LLMs to their training data? We study this question as one of missing probability mass and develop a theoretical account in which monofacts-the facts observed once during training-set the discovery capacity. In materials sci","authors":["Arda Uzunoglu","Mahler Revsine","Michael Schatz","Benjamin Van Durme","Mehrdad Farajtabar","Daniel Khashabi"],"url":"https://arxiv.org/abs/2611.03617v1","arxiv_id":"2611.03617v1","published":"2026-11-02T18:50:54Z"},{"title":"DiabAgent: Toward Agentic Physiological Control","abstract":"As pretraining scales, medical language models have advanced rapidly in clinical question answering. Their ability to achieve effective physiological control through sustained intervention still lacks systematic quantitative evaluation. Type 1 diabetes provides a concrete setting: impaired insulin secretion creates dependence on exogenous insulin, with dosing continually adjusted using information about meals, exerci","authors":["Chengxi Li","Shaoxuan Li","Deyao Hong","Qingle Liu","Yi Huang","Puheng Bian"],"url":"https://arxiv.org/abs/2611.03601v1","arxiv_id":"2611.03601v1","published":"2026-11-02T18:41:02Z"},{"title":"Four Bridges: Measuring Deception Propensity in a Multi-Agent Game","abstract":"AI agents are increasingly deployed in settings where they interact and coordinate with other agents, yet honesty is mostly measured in single-turn, single-agent benchmarks that pressure the model to deceive. We study deception that emerges in multi-agent interaction without any instruction to deceive. We introduce Kradle, a platform for evaluating AI models, and Four Bridges, an information asymmetry game in which f","authors":["Raphael Casey","Michael Simeone","Alberto Tosato","Florian Ernst","Kemal El Moujahid","James Tamplin"],"url":"https://arxiv.org/abs/2611.03600v1","arxiv_id":"2611.03600v1","published":"2026-11-02T18:40:47Z"},{"title":"Spacetime Emergence in the Memory of a Learning Agent","abstract":"We show that the causal structure of spacetime can emerge within the memory of a learning agent performing a quantum information task. We train a model-based reinforcement-learning agent to maximize the quantum mutual information between localized quantum probes interacting with a quantum field in Minkowski spacetime, without directly providing it with information regarding the spacetime metric or causal structure. I","authors":["Philip A. LeMaitre","T. Rick Perche"],"url":"https://arxiv.org/abs/2611.03596v1","arxiv_id":"2611.03596v1","published":"2026-11-02T18:39:52Z"},{"title":"Evaluating Uncertainty Calibration in Probabilistic Time Series Foundation Models","abstract":"Time series foundation models (TSFMs) are increasingly used for probabilistic forecasting across diverse domains, yet the reliability of their uncertainty estimates remains poorly understood. In this work, we study uncertainty calibration in probabilistic TSFMs from a broader methodological and empirical perspective. We introduce a taxonomy of how TSFMs represent predictive uncertainty and develop a fine-grained eval","authors":["Thomas Decker","Volker Tresp"],"url":"https://arxiv.org/abs/2611.03592v1","arxiv_id":"2611.03592v1","published":"2026-11-02T18:34:50Z"},{"title":"FedReady: Bounded Agents for Federation Formation","abstract":"Federated learning (FL) runtimes standardize aggregation and deployment, but each new study still requires federation formation: selecting task-eligible sites and preparing their local data and task code for federated training or analysis. This preparation recurs when the target changes, while raw records and site-private mappings are excluded from cross-site FL messages. We present FedReady, a system that performs f","authors":["Ziyue Xu","Holger R. Roth","Chester Chen","Peter Cnudde"],"url":"https://arxiv.org/abs/2611.03586v1","arxiv_id":"2611.03586v1","published":"2026-11-02T18:32:43Z"},{"title":"Sonar-MoE: In-Backward Expert Updates for Memory-Efficient Mixture-of-Experts Training","abstract":"Most parameters of a Mixture-of-Experts (MoE) model belong to its experts, and standard training keeps every expert gradient in GPU memory until the optimizer step. This memory grows with the number and size of the experts, so it rises as MoE models scale. We introduce Sonar-MoE, which updates each expert tensor during the backward pass and frees its gradient right away. It brings optimizer-in-backward from dense mod","authors":["Avni Mittal","Avinash Anand","Ashutosh Kumar","Dikshant Kukreja","Kritarth Prasad","Chaitanya Lakhchaura"],"url":"https://arxiv.org/abs/2611.03577v1","arxiv_id":"2611.03577v1","published":"2026-11-02T18:30:00Z"},{"title":"PlantVLM-Edge: Quantized Vision-Language Models for On-Device Crop Health Diagnosis","abstract":"Timely and accurate crop health diagnosis is essential for sustainable agricultural production, yet accurate diagnosis often requires expert knowledge that is not readily available. Recent vision-language models (VLMs) have demonstrated remarkable capabilities in visual understanding, reasoning, and natural-language interaction, creating new opportunities for intelligent crop health assessment. However, deploying VLM","authors":["Gaurab Wagle","Bishal Adhikari","Jiajia Li","Xiaolei Huang","Dong Chen"],"url":"https://arxiv.org/abs/2611.03557v1","arxiv_id":"2611.03557v1","published":"2026-11-02T18:19:19Z"},{"title":"MCP Tool Poisoning in Agentic AI Frameworks: A Cross-Framework Measurement Study","abstract":"The Model Context Protocol (MCP) lets agentic AI frameworks connect language models to external tool providers, but it carries attacker-controlled content (tool descriptions, schema fields, and response data) into model context without validation. Prior benchmarks measure model compliance with poisoned instructions without confirming real execution. We present the first cross-framework measurement of MCP tool poisoni","authors":["Farooq Shaikh","Biagio Montaruli"],"url":"https://arxiv.org/abs/2611.03555v1","arxiv_id":"2611.03555v1","published":"2026-11-02T18:17:08Z"},{"title":"Can LLM Agents Be Forward-Deployed Engineers? Requirement Discovery and Delivery for Enterprise Text-to-SQL","abstract":"LLM coding agents can increasingly automate model post-training, but whether they can act as forward-deployed engineer (FDE) agents, discovering customer requirements and turning them into deployment decisions, remains unclear. We study this on a real enterprise text-to-SQL engagement: a simulated customer, grounded in the real use case's requirements, starts with an ambiguous request. An agent must discover acceptan","authors":["Marianne Menglin Liu","Rongguang Wang","Zheng Wang","Yewen Wang","Leonid Boytsov","Tao Sheng"],"url":"https://arxiv.org/abs/2611.03551v1","arxiv_id":"2611.03551v1","published":"2026-11-02T18:13:38Z"},{"title":"An Agentic Framework for Automated Power System Studies and Grid Connection Assessment","abstract":"Connecting new generation and demand to the grid depends on two scarce skills: checking applications against a large, changing body of regulation, and running the network studies that decide where and how a project connects. We present Grid Agents, an AI system that brings both together, and the methodology we use to evaluate it. The Grid Ontology is its knowledge system. It represents the regulation, standards and e","authors":["MaoXun Huang","Kshitij Kapoor","Eli Louise"],"url":"https://arxiv.org/abs/2611.03534v1","arxiv_id":"2611.03534v1","published":"2026-11-02T18:00:52Z"},{"title":"Contrastive Adapter Training and Consensus Knowledge Distillation for Multi-Source-Free Domain Adaptation in Skin Cancer Diagnosis","abstract":"Skin cancer diagnosis, particularly differentiating melanoma from benign nevi, is challenging due to the visual similarity between lesions. Although convolutional neural networks (CNNs) and vision transformers (ViTs) have shown promising performance, their effectiveness often deteriorates on data from heterogeneous clinical sources. Conventional domain adaptation methods address domain shift but require access to sou","authors":["Ali Abedi","Q. M. Jonathan Wu","Ning Zhang","Farhad Pourpanah"],"url":"https://arxiv.org/abs/2611.03528v1","arxiv_id":"2611.03528v1","published":"2026-11-02T17:58:16Z"},{"title":"Library of Layers (LoL): Adaptively Ordering Transformer Layers at Runtime","abstract":"Computer programmers chain together the same reusable computational primitives, for example, conditional statements or loops, but in different orders to implement different algorithms. In contrast, existing language model architectures always execute their layers in the same order. We introduce Library of Layers (LoL), an architecture that dynamically orders its layers during inference to solve the problem at hand. L","authors":["Abdellah Rahmani","Sean McLeish","Ang Li","Sanae Lotfi","Pascal Frossard","Micah Goldblum"],"url":"https://arxiv.org/abs/2611.03526v1","arxiv_id":"2611.03526v1","published":"2026-11-02T17:57:53Z"},{"title":"Grading the Unannotated: Insights from the WorkRB Skill Extraction Challenge at RecSys-HR 2026","abstract":"Skill extraction benchmarks score models against a few human-annotated positives and treat every other skill in the vocabulary as equally wrong. At the scale of ESCO (13,939 skills) this binary view can reward models that rank the annotated positive high for the wrong reason, and hides semantically nonsensical predictions. The WorkRB Challenge at RecSys-HR 2026 replaces it with graded relevance: every candidate skill","authors":["Warre Veys","Luis Gasco","Jens-Joris Decorte"],"url":"https://arxiv.org/abs/2611.03525v1","arxiv_id":"2611.03525v1","published":"2026-11-02T17:57:53Z"},{"title":"PanoTac: A Dense Three-Axis Tactile Sensor for Robust Touch-Centric Manipulation","abstract":"Contact-rich manipulation benefits from tactile feedback that captures both detailed contact geometry and interaction forces. When scooping grains, contact patterns help infer spoon orientation, while resistance transmitted through the grasp guides motion. To provide these complementary sensing capabilities, we present PanoTac, a low-cost, compliant tactile fingertip designed for dense three-axis tactile sensing. Eac","authors":["Binglin","Wang","Xiaole","Jiang","Zicheng Teng","Xinqi Liu"],"url":"https://arxiv.org/abs/2611.03520v1","arxiv_id":"2611.03520v1","published":"2026-11-02T17:55:07Z"},{"title":"VIAS: Value-Isolating Activation Steering for Multi-Value Alignment and Compliance for Organisations","abstract":"Organisations increasingly deploy large language model agents that must follow organisational values. We check whether activation steering, which adds vectors to a model's internal activations during generation without changing its weights, can improve compliance beyond prompting alone. Since most scenarios involve several values at once, we focus on multi-value steering. A simple way to build these vectors is to con","authors":["Avni Mittal","Avinash Anand","Dikshant Kukreja","Erik Cambria","Rajiv Ratn Shah","Sandipan Dandapat"],"url":"https://arxiv.org/abs/2611.03518v1","arxiv_id":"2611.03518v1","published":"2026-11-02T17:53:26Z"},{"title":"A Cross-Domain Matrix Engine for Signal Processing and Deep Neural Net Inference","abstract":"Matrix multiplication dominates both PHY signal processing and Deep Neural Network (DNN) inference, yet these domains place opposing demands on the matrix engine. Signal processing requires low-latency execution of relatively small matrix operations, whereas DNN inference, particularly at large batch sizes, prioritizes high throughput and energy efficiency for large matrix multiplications. While offering efficient me","authors":["Mehdi Safarpour"],"url":"https://arxiv.org/abs/2611.03503v1","arxiv_id":"2611.03503v1","published":"2026-11-02T17:40:14Z"},{"title":"Can AI Do Formal Demography? Why Vaccinating the Oldest Saves Both the Most Lives and the Most Years of Life","abstract":"Can AI contribute to formal demography? We report an experiment in which an AI model, Claude, was asked to explain and then simplify the proof of an earlier result: that vaccinating the oldest against COVID-19 saves both the most lives and the most years of life, because the years saved per person treated rise with age. The model proposed a new proof that is shorter, more intuitive, and somewhat more general than the","authors":["Joshua R. Goldstein","Kenneth W. Wachter"],"url":"https://arxiv.org/abs/2611.03500v1","arxiv_id":"2611.03500v1","published":"2026-11-02T17:39:50Z"},{"title":"Online Label-Free Gradient Matching for Continual Language Model Training","abstract":"Language models in customer-facing products must be continually updated, since the data they serve shifts over time. As retraining on the full accumulated data is impractical, each update should instead run on a small set of examples carrying the training signal of all data seen so far. The strongest current methods build this set by gradient matching, which synthesizes examples whose training gradients match those o","authors":["Sajjad Pakdamansavoji","Mohammad Reza Rezaei","Ilija Subasic","Pedro Garzon","Radu Paradovschi","Zhao Chen"],"url":"https://arxiv.org/abs/2611.03496v1","arxiv_id":"2611.03496v1","published":"2026-11-02T17:37:36Z"}],"history":{"events":[{"year":2008,"text":"Lewis Hamilton overtook Timo Glock in the final corners of the Brazilian Grand Prix to become the Formula One World Drivers' Champion by one point.","url":"https://en.wikipedia.org/wiki/Lewis_Hamilton"},{"year":2000,"text":"As members of Expedition 1, American astronaut William Shepherd and Russian cosmonauts Sergei Krikalev and Yuri Gidzenko (all pictured) became the first resident crew to arrive at the International Space Station.","url":"https://en.wikipedia.org/wiki/Expedition_1"},{"year":1997,"text":"Tropical Storm Linda made landfall in the Mekong Delta in Vietnam, causing more than 3,000 deaths.","url":"https://en.wikipedia.org/wiki/Tropical_Storm_Linda_(1997)"},{"year":1994,"text":"A lightning strike ruptured three oil tanks near Dronka, Egypt, causing a flood that killed 469 people.","url":"https://en.wikipedia.org/wiki/1994_Durunka_floods_and_lightning_strike"},{"year":1984,"text":"Velma Barfield, a convicted serial killer, became the first woman to be executed in the United States since 1962.","url":"https://en.wikipedia.org/wiki/Velma_Barfield"},{"year":1963,"text":"South Vietnamese president Ngô Đình Diệm (pictured) was arrested and assassinated in Saigon, marking the culmination of a coup d'état led by Dương Văn Minh.","url":"https://en.wikipedia.org/wiki/South_Vietnam"},{"year":1957,"text":"A large number of people witnessed a fiery object in the sky near Levelland, Texas, which the United States Air Force said was ball lightning.","url":"https://en.wikipedia.org/wiki/Levelland_UFO_case"},{"year":1949,"text":"The Dutch–Indonesian Round Table Conference ended with the Netherlands agreeing to transfer sovereignty of the Dutch East Indies to the United States of Indonesia.","url":"https://en.wikipedia.org/wiki/Dutch%E2%80%93Indonesian_Round_Table_Conference"},{"year":1943,"text":"World War II: A U.S. Navy task force turned away an Imperial Japanese Navy formation at the Battle of Empress Augusta Bay, thus protecting the landings at Cape Torokina.","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1932,"text":"The Australian military began a \"war against emus\", flightless native birds blamed for widespread damage to crops in Western Australia.","url":"https://en.wikipedia.org/wiki/Australian_Defence_Force"},{"year":1917,"text":"The British government issued the Balfour Declaration in support of a Jewish homeland in Palestine, then an Ottoman region with a small Jewish minority.","url":"https://en.wikipedia.org/wiki/Balfour_Declaration"},{"year":1880,"text":"James A. Garfield was elected as president of the United States; the election is the closest to date by popular vote margin.","url":"https://en.wikipedia.org/wiki/James_A._Garfield"}],"births":[{"year":2001,"text":"Moisés Caicedo, Ecuadorian footballer","url":"https://en.wikipedia.org/wiki/Mois%C3%A9s_Caicedo"},{"year":2000,"text":"Alphonso Davies, Canadian soccer player","url":"https://en.wikipedia.org/wiki/Alphonso_Davies"},{"year":1999,"text":"Park Woo-jin, South Korean singer","url":"https://en.wikipedia.org/wiki/Park_Woo-jin"},{"year":1998,"text":"Jordan Love, American football player","url":"https://en.wikipedia.org/wiki/Jordan_Love"},{"year":1997,"text":"Filip Hronek, Czech ice hockey player","url":"https://en.wikipedia.org/wiki/Filip_Hronek"},{"year":1997,"text":"Davis Keillor-Dunn, English footballer","url":"https://en.wikipedia.org/wiki/Davis_Keillor-Dunn"},{"year":1995,"text":"Hanna Öberg, Swedish biathlete","url":"https://en.wikipedia.org/wiki/Hanna_%C3%96berg"},{"year":1994,"text":"Shaq Coulthirst, English footballer","url":"https://en.wikipedia.org/wiki/Shaq_Coulthirst"}],"deaths":[{"year":2024,"text":"Janey Godley, Scottish actor, writer and comedian (born 1961)","url":"https://en.wikipedia.org/wiki/Janey_Godley"},{"year":2024,"text":"Alan Rachins, American actor (born 1942)","url":"https://en.wikipedia.org/wiki/Alan_Rachins"},{"year":2024,"text":"Paul Stephenson, British civil rights activist (born 1937)","url":"https://en.wikipedia.org/wiki/Paul_Stephenson_(civil_rights_campaigner)"},{"year":2023,"text":"Humaira Himu, Bangladeshi actress (born 1985)","url":"https://en.wikipedia.org/wiki/Humaira_Himu"},{"year":2022,"text":"Atilio Stampone, Argentine pianist and composer (born 1926)","url":"https://en.wikipedia.org/wiki/Atilio_Stampone"},{"year":2021,"text":"Neal Smith, American politician (born 1920)","url":"https://en.wikipedia.org/wiki/Neal_Smith_(politician)"},{"year":2019,"text":"Walter Mercado, Puerto Rican television personality, astrologer, actor, and dancer (born 1932)","url":"https://en.wikipedia.org/wiki/Walter_Mercado"},{"year":2018,"text":"Raymond Chow, Hong Kong film producer (born 1927)","url":"https://en.wikipedia.org/wiki/Raymond_Chow"}]},"census":{"panel_version":2,"probed":14770,"error_rate":25.77,"degraded":false,"rates":{"head":13.7,"tail":4.5,"ai_native":74.55}},"sources":[{"id":"attention","name":"Wikipedia most-read","url":"https://api.wikimedia.org","license":"CC BY-SA 4.0","attribution":"Wikipedia contributors"},{"id":"frontier","name":"Hacker News","url":"https://news.ycombinator.com","license":"Public API — titles and links, credited","attribution":"Hacker News / Y Combinator"},{"id":"research","name":"arXiv cs.AI","url":"https://arxiv.org","license":"Open metadata, per arXiv API terms","attribution":"arXiv.org"},{"id":"history","name":"Wikipedia On this day","url":"https://api.wikimedia.org","license":"CC BY-SA 4.0","attribution":"Wikipedia contributors"}],"license":"Records are CC BY-SA 4.0, inheriting from Wikipedia. Every item links to its source."}