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This holds for any approach that treats alignment as optimizing toward a fixed formal value-object, whether reward function, utility function, constitutional principles, or learned preference representation. Three philosophical results create compounding difficulties: H","authors":["Austin Spizzirri"],"url":"http://arxiv.org/abs/2512.03048v5","arxiv_id":"2512.03048v5","published":"2025-11-19T23:31:29Z"},{"title":"DiffuMamba: High-Throughput Diffusion LMs with Mamba Backbone","abstract":"Diffusion language models (DLMs) have emerged as a promising alternative to autoregressive (AR) generation, yet their reliance on Transformer backbones limits inference efficiency due to quadratic attention or KV-cache overhead. We introduce DiffuMamba, a masked diffusion language model built on a bidirectional Mamba backbone that combines the diffusion objective with linear-time sequence modeling, and DiffuMamba-H, ","authors":["Vaibhav Singh","Oleksiy Ostapenko","Pierre-André Noël","Eugene Belilovsky","Torsten Scholak"],"url":"http://arxiv.org/abs/2511.15927v4","arxiv_id":"2511.15927v4","published":"2025-11-19T23:23:49Z"},{"title":"Thinking, Faithful and Stable: Mitigating Hallucinations in LLMs","abstract":"This project develops a self correcting framework for large language models (LLMs) that detects and mitigates hallucinations during multi-step reasoning. Rather than relying solely on final answer correctness, our approach leverages fine grained uncertainty signals: 1) self-assessed confidence alignment, and 2) token-level entropy spikes to detect unreliable and unfaithful reasoning in real time. We design a composit","authors":["Chelsea Zou","Yiheng Yao","Basant Khalil"],"url":"http://arxiv.org/abs/2511.15921v1","arxiv_id":"2511.15921v1","published":"2025-11-19T23:09:26Z"},{"title":"Decomposing Theory of Mind: How Emotional Processing Mediates ToM Abilities in LLMs","abstract":"Recent work shows activation steering substantially improves language models' Theory of Mind (ToM) (Bortoletto et al. 2024), yet the mechanisms of what changes occur internally that leads to different outputs remains unclear. We propose decomposing ToM in LLMs by comparing steered versus baseline LLMs' activations using linear probes trained on 45 cognitive actions. We applied Contrastive Activation Addition (CAA) st","authors":["Ivan Chulo","Ananya Joshi"],"url":"http://arxiv.org/abs/2511.15895v1","arxiv_id":"2511.15895v1","published":"2025-11-19T21:56:00Z"},{"title":"Box6D : Zero-shot Category-level 6D Pose Estimation of Warehouse Boxes","abstract":"Accurate and efficient 6D pose estimation of novel objects under clutter and occlusion is critical for robotic manipulation across warehouse automation, bin picking, logistics, and e-commerce fulfillment. There are three main approaches in this domain; Model-based methods assume an exact CAD model at inference but require high-resolution meshes and transfer poorly to new environments; Model-free methods that rely on ","authors":["Yintao Ma","Sajjad Pakdamansavoji","Amir Rasouli","Tongtong Cao"],"url":"http://arxiv.org/abs/2511.15884v1","arxiv_id":"2511.15884v1","published":"2025-11-19T21:22:08Z"},{"title":"WALDO: Where Unseen Model-based 6D Pose Estimation Meets Occlusion","abstract":"Accurate 6D object pose estimation is vital for robotics, augmented reality, and scene understanding. For seen objects, high accuracy is often attainable via per-object fine-tuning but generalizing to unseen objects remains a challenge. To address this problem, past arts assume access to CAD models at test time and typically follow a multi-stage pipeline to estimate poses: detect and segment the object, propose an in","authors":["Sajjad Pakdamansavoji","Yintao Ma","Amir Rasouli","Tongtong Cao"],"url":"http://arxiv.org/abs/2511.15874v1","arxiv_id":"2511.15874v1","published":"2025-11-19T21:01:49Z"},{"title":"AquaSentinel: Next-Generation AI System Integrating Sensor Networks for Urban Underground Water Pipeline Anomaly Detection via Collaborative MoE-LLM Agent Architecture","abstract":"Underground pipeline leaks and infiltrations pose significant threats to water security and environmental safety. Traditional manual inspection methods provide limited coverage and delayed response, often missing critical anomalies. This paper proposes AquaSentinel, a novel physics-informed AI system for real-time anomaly detection in urban underground water pipeline networks. We introduce four key innovations: (1) s","authors":["Qiming Guo","Bishal Khatri","Wenbo Sun","Jinwen Tang","Hua Zhang","Wenlu Wang"],"url":"http://arxiv.org/abs/2511.15870v1","arxiv_id":"2511.15870v1","published":"2025-11-19T20:53:50Z"},{"title":"A Crowdsourced Study of ChatBot Influence in Value-Driven Decision Making Scenarios","abstract":"Similar to social media bots that shape public opinion, healthcare and financial decisions, LLM-based ChatBots like ChatGPT can persuade users to alter their behavior. Unlike prior work that persuades via overt-partisan bias or misinformation, we test whether framing alone suffices. We conducted a crowdsourced study, where 336 participants interacted with a neutral or one of two value-framed ChatBots while deciding t","authors":["Anthony Wise","Xinyi Zhou","Martin Reimann","Anind Dey","Leilani Battle"],"url":"http://arxiv.org/abs/2511.15857v1","arxiv_id":"2511.15857v1","published":"2025-11-19T20:25:34Z"},{"title":"Step-Audio-R1 Technical Report","abstract":"Recent advances in reasoning models have demonstrated remarkable success in text and vision domains through extended chain-of-thought deliberation. However, a perplexing phenomenon persists in audio language models: they consistently perform better with minimal or no reasoning, raising a fundamental question - can audio intelligence truly benefit from deliberate thinking? We introduce Step-Audio-R1, the first audio r","authors":["Fei Tian","Xiangyu Tony Zhang","Yuxin Zhang","Haoyang Zhang","Yuxin Li","Daijiao Liu"],"url":"http://arxiv.org/abs/2511.15848v2","arxiv_id":"2511.15848v2","published":"2025-11-19T20:12:50Z"},{"title":"The Loss of Control Playbook: Degrees, Dynamics, and Preparedness","abstract":"This research report addresses the absence of an actionable definition for Loss of Control (LoC) in AI systems by developing a novel taxonomy and preparedness framework. Despite increasing policy and research attention, existing LoC definitions vary significantly in scope and timeline, hindering effective LoC assessment and mitigation. To address this issue, we draw from an extensive literature review and propose a g","authors":["Charlotte Stix","Annika Hallensleben","Alejandro Ortega","Matteo Pistillo"],"url":"http://arxiv.org/abs/2511.15846v5","arxiv_id":"2511.15846v5","published":"2025-11-19T20:10:39Z"},{"title":"EfficientSAM3: Progressive Hierarchical Distillation for Video Concept Segmentation from SAM1, 2, and 3","abstract":"The Segment Anything Model 3 (SAM3) advances visual understanding with Promptable Concept Segmentation (PCS) across images and videos, but its unified architecture (shared vision backbone, DETR-style detector, dense-memory tracker) remains prohibitive for on-device use. We present EfficientSAM3, a family of efficient models built on Progressive Hierarchical Distillation (PHD) that transfers capability from SAM3 to li","authors":["Chengxi Zeng","Yuxuan Jiang","Aaron Zhang"],"url":"http://arxiv.org/abs/2511.15833v1","arxiv_id":"2511.15833v1","published":"2025-11-19T19:42:22Z"},{"title":"Mini Amusement Parks (MAPs): A Testbed for Modelling Business Decisions","abstract":"Despite rapid progress in artificial intelligence, current systems struggle with the interconnected challenges that define real-world decision making. Practical domains such as business management require open-ended optimization, actively learning environment dynamics from sparse experience, planning over long horizons in stochastic settings, and reasoning over spatial information. Yet no existing human--AI benchmark","authors":["Stéphane Aroca-Ouellette","Ian Berlot-Attwell","Panagiotis Lymperopoulos","Abhiramon Rajasekharan","Tongqi Zhu","Herin Kang"],"url":"http://arxiv.org/abs/2511.15830v3","arxiv_id":"2511.15830v3","published":"2025-11-19T19:38:05Z"},{"title":"IMACT-CXR: An Interactive Multi-Agent Conversational Tutoring System for Chest X-Ray Interpretation","abstract":"IMACT-CXR is an interactive multi-agent conversational tutor that helps trainees interpret chest X-rays by unifying spatial annotation, gaze analysis, knowledge retrieval, and image-grounded reasoning in a single AutoGen-based workflow. The tutor simultaneously ingests learner bounding boxes, gaze samples, and free-text observations. Specialized agents evaluate localization quality, generate Socratic coaching, retrie","authors":["Tuan-Anh Le","Anh Mai Vu","David Yang","Akash Awasthi","Hien Van Nguyen"],"url":"http://arxiv.org/abs/2511.15825v2","arxiv_id":"2511.15825v2","published":"2025-11-19T19:32:29Z"},{"title":"TopoReformer: Mitigating Adversarial Attacks Using Topological Purification in OCR Models","abstract":"Adversarially perturbed images of text can cause sophisticated OCR systems to produce misleading or incorrect transcriptions from seemingly invisible changes to humans. Some of these perturbations even survive physical capture, posing security risks to high-stakes applications such as document processing, license plate recognition, and automated compliance systems. Existing defenses, such as adversarial training, inp","authors":["Bhagyesh Kumar","A S Aravinthakashan","Akshat Satyanarayan","Ishaan Gakhar","Ujjwal Verma"],"url":"http://arxiv.org/abs/2511.15807v1","arxiv_id":"2511.15807v1","published":"2025-11-19T19:01:51Z"},{"title":"German General Social Survey Personas: A Survey-Derived Persona Prompt Collection for Population-Aligned LLM Studies","abstract":"The use of Large Language Models (LLMs) for simulating human perspectives via persona prompting is gaining traction in computational social science. However, well-curated, empirically grounded persona collections remain scarce, limiting the accuracy and representativeness of such simulations. Here, we introduce the German General Social Survey Personas (GGSS Personas) collection, a comprehensive and representative pe","authors":["Jens Rupprecht","Leon Fröhling","Claudia Wagner","Markus Strohmaier"],"url":"http://arxiv.org/abs/2511.21722v2","arxiv_id":"2511.21722v2","published":"2025-11-19T19:01:02Z"},{"title":"In-N-On: Scaling Egocentric Manipulation with in-the-wild and on-task Data","abstract":"Egocentric videos are a valuable and scalable data source to learn manipulation policies. However, due to significant data heterogeneity, most existing approaches utilize human data for simple pre-training, which does not unlock its full potential. This paper first provides a scalable recipe for collecting and using egocentric data by categorizing human data into two categories: in-the-wild and on-task alongside with","authors":["Xiongyi Cai","Ri-Zhao Qiu","Geng Chen","Lai Wei","Isabella Liu","Tianshu Huang"],"url":"http://arxiv.org/abs/2511.15704v1","arxiv_id":"2511.15704v1","published":"2025-11-19T18:59:04Z"},{"title":"Think Visually, Reason Textually: Vision-Language Synergy in ARC","abstract":"Abstract reasoning from minimal examples remains a core unsolved problem for frontier foundation models such as GPT-5 and Grok 4. These models still fail to infer structured transformation rules from a handful of examples, which is a key hallmark of human intelligence. The Abstraction and Reasoning Corpus for Artificial General Intelligence (ARC-AGI) provides a rigorous testbed for this capability, demanding conceptu","authors":["Beichen Zhang","Yuhang Zang","Xiaoyi Dong","Yuhang Cao","Haodong Duan","Dahua Lin"],"url":"http://arxiv.org/abs/2511.15703v2","arxiv_id":"2511.15703v2","published":"2025-11-19T18:59:04Z"},{"title":"Joint Semantic-Channel Coding and Modulation for Token Communications","abstract":"In recent years, the Transformer architecture has achieved outstanding performance across a wide range of tasks and modalities. Token is the unified input and output representation in Transformer-based models, which has become a fundamental information unit. In this work, we consider the problem of token communication, studying how to transmit tokens efficiently and reliably. Point cloud, a prevailing three-dimension","authors":["Jingkai Ying","Zhijin Qin","Yulong Feng","Liejun Wang","Xiaoming Tao"],"url":"http://arxiv.org/abs/2511.15699v1","arxiv_id":"2511.15699v1","published":"2025-11-19T18:56:32Z"},{"title":"Balancing Natural Language Processing Accuracy and Normalisation in Extracting Medical Insights","abstract":"Extracting structured medical insights from unstructured clinical text using Natural Language Processing (NLP) remains an open challenge in healthcare, particularly in non-English contexts where resources are scarce. This study presents a comparative analysis of NLP low-compute rule-based methods and Large Language Models (LLMs) for information extraction from electronic health records (EHR) obtained from the Voivode","authors":["Paulina Tworek","Miłosz Bargieł","Yousef Khan","Tomasz Pełech-Pilichowski","Marek Mikołajczyk","Roman Lewandowski"],"url":"http://arxiv.org/abs/2511.15778v1","arxiv_id":"2511.15778v1","published":"2025-11-19T18:51:45Z"},{"title":"Walrus: A Cross-Domain Foundation Model for Continuum Dynamics","abstract":"Foundation models have transformed machine learning for language and vision, but achieving comparable impact in physical simulation remains a challenge. Data heterogeneity and unstable long-term dynamics inhibit learning from sufficiently diverse dynamics, while varying resolutions and dimensionalities challenge efficient training on modern hardware. Through empirical and theoretical analysis, we incorporate new appr","authors":["Michael McCabe","Payel Mukhopadhyay","Tanya Marwah","Bruno Regaldo-Saint Blancard","Francois Rozet","Cristiana Diaconu"],"url":"http://arxiv.org/abs/2511.15684v2","arxiv_id":"2511.15684v2","published":"2025-11-19T18:36:03Z"},{"title":"MF-GCN: A Multi-Frequency Graph Convolutional Network for Tri-Modal Depression Detection Using Eye-Tracking, Facial, and Acoustic Features","abstract":"Depression is a prevalent global mental health disorder, characterised by persistent low mood and anhedonia. However, it remains underdiagnosed because current diagnostic methods depend heavily on subjective clinical assessments. To enable objective detection, we introduce a gold standard dataset of 103 clinically assessed participants collected through a tripartite data approach which uniquely integrated eye trackin","authors":["Sejuti Rahman","Swakshar Deb","MD. Sameer Iqbal Chowdhury","MD. Jubair Ahmed Sourov","Mohammad Shamsuddin"],"url":"http://arxiv.org/abs/2511.15675v2","arxiv_id":"2511.15675v2","published":"2025-11-19T18:18:53Z"},{"title":"VisPlay: Self-Evolving Vision-Language Models from Images","abstract":"Reinforcement learning (RL) provides a principled framework for improving Vision-Language Models (VLMs) on complex reasoning tasks. However, existing RL approaches often rely on human-annotated labels or task-specific heuristics to define verifiable rewards, both of which are costly and difficult to scale. We introduce VisPlay, a self-evolving RL framework that enables VLMs to autonomously improve their reasoning abi","authors":["Yicheng He","Chengsong Huang","Zongxia Li","Jiaxin Huang","Yonghui Yang"],"url":"http://arxiv.org/abs/2511.15661v2","arxiv_id":"2511.15661v2","published":"2025-11-19T17:55:15Z"},{"title":"GEO-Bench-2: From Performance to Capability, Rethinking Evaluation in Geospatial AI","abstract":"Geospatial Foundation Models (GeoFMs) are transforming Earth Observation (EO), but evaluation lacks standardized protocols. GEO-Bench-2 addresses this with a comprehensive framework spanning classification, segmentation, regression, object detection, and instance segmentation across 19 permissively-licensed datasets. We introduce ''capability'' groups to rank models on datasets that share common characteristics (e.g.","authors":["Naomi Simumba","Nils Lehmann","Paolo Fraccaro","Hamed Alemohammad","Geeth De Mel","Salman Khan"],"url":"http://arxiv.org/abs/2511.15658v2","arxiv_id":"2511.15658v2","published":"2025-11-19T17:45:02Z"},{"title":"Continual Reinforcement Learning for Cyber-Physical Systems: Lessons Learned and Open Challenges","abstract":"Continual learning (CL) is a branch of machine learning that aims to enable agents to adapt and generalise previously learned abilities so that these can be reapplied to new tasks or environments. This is particularly useful in multi-task settings or in non-stationary environments, where the dynamics can change over time. This is particularly relevant in cyber-physical systems such as autonomous driving. However, des","authors":["Kim N. Nolle","Ivana Dusparic","Rhodri Cusack","Vinny Cahill"],"url":"http://arxiv.org/abs/2511.15652v1","arxiv_id":"2511.15652v1","published":"2025-11-19T17:40:13Z"},{"title":"Entropy-Based Measurement of Value Drift and Alignment Work in Large Language Models","abstract":"Large language model safety is usually assessed with static benchmarks, but key failures are dynamic: value drift under distribution shift, jailbreak attacks, and slow degradation of alignment in deployment. Building on a recent Second Law of Intelligence that treats ethical entropy as a state variable which tends to increase unless countered by alignment work, we make this framework operational for large language mo","authors":["Samih Fadli"],"url":"http://arxiv.org/abs/2512.03047v1","arxiv_id":"2512.03047v1","published":"2025-11-19T17:27:16Z"}],"history":{"events":[{"year":2013,"text":"A double suicide bombing at the Iranian embassy in Beirut, Lebanon, killed 23 people and injured at least 160 others.","url":"https://en.wikipedia.org/wiki/2013_Iranian_embassy_bombing_in_Beirut"},{"year":2010,"text":"The first of four explosions occurred at the Pike River Mine in the West Coast in New Zealand's worst mining disaster in nearly a century.","url":"https://en.wikipedia.org/wiki/Pike_River_Mine_disaster"},{"year":2005,"text":"Iraq War: A group of United States Marines massacred 25 people in the town of Haditha.","url":"https://en.wikipedia.org/wiki/Iraq_War"},{"year":2002,"text":"The Greek oil tanker Prestige split in two and sank off the coast of Galicia after spilling 420 thousand barrels (17.8 million US gallons) of oil, in the worst environmental disaster in Spanish and Portuguese history.","url":"https://en.wikipedia.org/wiki/MV_Prestige"},{"year":1991,"text":"Mexican singer Luis Miguel released the album Romance, which led to a revival of interest in bolero music.","url":"https://en.wikipedia.org/wiki/Luis_Miguel"},{"year":1985,"text":"The first of five summits (pictured) between Soviet general secretary Mikhail Gorbachev and U.S. president Ronald Reagan began in Geneva.","url":"https://en.wikipedia.org/wiki/Geneva_Summit_(1985)"},{"year":1969,"text":"Playing for Santos against Vasco da Gama in Rio de Janeiro, Brazilian footballer Pelé (pictured) scored his thousandth goal.","url":"https://en.wikipedia.org/wiki/Santos_FC"},{"year":1942,"text":"World War II: Soviet troops launched Operation Uranus at the Battle of Stalingrad with the goal of encircling Axis forces, turning the tide of the battle in their favour.","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1941,"text":"World War II: The Australian light cruiser HMAS Sydney and the German auxiliary cruiser Kormoran destroyed each other in the Indian Ocean.","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1933,"text":"The Union of the Right, a coalition of right-wing parties, won the majority of seats in the 1933 Spanish general election, the first election in the country with suffrage extended to women.","url":"https://en.wikipedia.org/wiki/1933_Spanish_general_election"},{"year":1863,"text":"American Civil War: Confederate forces began the Siege of Knoxville against Union fortifications, surrounding most of the city.","url":"https://en.wikipedia.org/wiki/American_Civil_War"},{"year":1863,"text":"American Civil War: U.S. president Abraham Lincoln delivered the Gettysburg Address at the dedication of the Soldiers' National Cemetery in Gettysburg, Pennsylvania.","url":"https://en.wikipedia.org/wiki/American_Civil_War"},{"year":1824,"text":"Temenggong Abdul Rahman of Johor and Sultan Hussein Shah of Johor ceded the governance of Singapore to the British East India Company.","url":"https://en.wikipedia.org/wiki/Temenggong_Abdul_Rahman"},{"year":1794,"text":"The United States and Great Britain signed the Jay Treaty, the basis for ten years of peaceful trade between the two nations.","url":"https://en.wikipedia.org/wiki/Jay_Treaty"},{"year":1620,"text":"The Mayflower (depicted), which brought the Pilgrims from England to the New World, sighted Cape Cod.","url":"https://en.wikipedia.org/wiki/Mayflower"}],"births":[{"year":1999,"text":"Evgenia Medvedeva, Russian figure skater","url":"https://en.wikipedia.org/wiki/Evgenia_Medvedeva"},{"year":1998,"text":"Nahuel Ferraresi, Venezuelan footballer","url":"https://en.wikipedia.org/wiki/Nahuel_Ferraresi"},{"year":1997,"text":"Zach Collins, American basketball player","url":"https://en.wikipedia.org/wiki/Zach_Collins"},{"year":1997,"text":"Kotonowaka Masahiro, Japanese sumo wrestler","url":"https://en.wikipedia.org/wiki/Kotozakura_Masakatsu_II"},{"year":1996,"text":"RiceGum, American YouTuber","url":"https://en.wikipedia.org/wiki/RiceGum"},{"year":1996,"text":"FaZe Rug, American YouTuber","url":"https://en.wikipedia.org/wiki/FaZe_Rug"},{"year":1996,"text":"Fred Warner, American football player","url":"https://en.wikipedia.org/wiki/Fred_Warner_(American_football)"},{"year":1995,"text":"Vanessa Axente, Hungarian model","url":"https://en.wikipedia.org/wiki/Vanessa_Axente"}],"deaths":[{"year":2024,"text":"Tony Campolo, American sociologist and pastor (born 1935)","url":"https://en.wikipedia.org/wiki/Tony_Campolo"},{"year":2023,"text":"Rosalynn Carter, American mental health activist, First Lady of the United States (1977–1981), and of Georgia (1971–1975) (born 1927)","url":"https://en.wikipedia.org/wiki/Rosalynn_Carter"},{"year":2023,"text":"Eddie Linden, Scottish poet and publisher (born 1935)","url":"https://en.wikipedia.org/wiki/Eddie_Linden"},{"year":2022,"text":"Jason David Frank, American actor and mixed martial artist (born 1973)","url":"https://en.wikipedia.org/wiki/Jason_David_Frank"},{"year":2017,"text":"Charles Manson, American cult leader and mass murderer (born 1934)","url":"https://en.wikipedia.org/wiki/Charles_Manson"},{"year":2017,"text":"Warren \"Pete\" Moore, American singer-songwriter and record producer (born 1938)","url":"https://en.wikipedia.org/wiki/Warren_%22Pete%22_Moore"},{"year":2017,"text":"Jana Novotná, Czech tennis player (born 1968)","url":"https://en.wikipedia.org/wiki/Jana_Novotn%C3%A1"},{"year":2017,"text":"Della Reese, American singer and actress (born 1931)","url":"https://en.wikipedia.org/wiki/Della_Reese"}]},"sources":[{"id":"attention","name":"Wikipedia 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Every item links to its source."}