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To simplify the learning paradigm, most previous methods convert ambiguous annotation results into precise one-hot annotations and train FER models in an end-to-end supervised manner. In this paper, we rethink t","authors":["Wang, Weijie","Li, Bo","Sebe, Nicu","Lepri, Bruno"],"url":"https://arxiv.org/abs/2209.15402","arxiv_id":"2209.15402","published":"2025-12-04"},{"title":"Scheduling and Aggregation Design for Asynchronous Federated Learning over Wireless Networks","abstract":"Federated Learning (FL) is a collaborative machine learning (ML) framework that combines on-device training and server-based aggregation to train a common ML model among distributed agents. In this work, we propose an asynchronous FL design with periodic aggregation to tackle the straggler issue in FL systems. Considering limited wireless communication resources, we investigate the effect of different scheduling poli","authors":["Hu, Chung-Hsuan","Chen, Zheng","Larsson, Erik G."],"url":"https://arxiv.org/abs/2212.07356","arxiv_id":"2212.07356","published":"2025-12-04"},{"title":"The generalized Hierarchical Gaussian Filter","abstract":"Hierarchical Bayesian models of perception and learning feature prominently in contemporary cognitive neuroscience where, for example, they inform computational concepts of mental disorders. This includes predictive coding and hierarchical Gaussian filtering (HGF), which differ in the nature of hierarchical representations. In this work, we present a new class of artificial neural networks that unifies computational ","authors":["Weber, Lilian Aline","Waade, Peter Thestrup","Legrand, Nicolas","Møller, Anna Hedvig","Stephan, Klaas Enno","Mathys, Christoph"],"url":"https://arxiv.org/abs/2305.10937","arxiv_id":"2305.10937","published":"2025-12-04"},{"title":"Unbiased Kinetic Langevin Monte Carlo with Inexact Gradients","abstract":"We present an unbiased method for Bayesian posterior means based on kinetic Langevin dynamics that combines advanced splitting methods with enhanced gradient approximations. Our approach avoids Metropolis correction by coupling Markov chains at different discretization levels in a multilevel Monte Carlo approach. Theoretical analysis demonstrates that our proposed estimator is unbiased, attains finite variance, and s","authors":["Chada, Neil K.","Leimkuhler, Benedict","Paulin, Daniel","Whalley, Peter A."],"url":"https://arxiv.org/abs/2311.05025","arxiv_id":"2311.05025","published":"2025-12-04"},{"title":"A Group Fairness Lens for Large Language Models","abstract":"The need to assess LLMs for bias and fairness is critical, with current evaluations often being narrow, missing a broad categorical view. In this paper, we propose evaluating the bias and fairness of LLMs from a group fairness lens using a novel hierarchical schema characterizing diverse social groups. Specifically, we construct a dataset, GFAIR, encapsulating target-attribute combinations across multiple dimensions.","authors":["Bi, Guanqun","Xie, Yuqiang","Shen, Lei","Cao, Yanan"],"url":"https://arxiv.org/abs/2312.15478","arxiv_id":"2312.15478","published":"2025-12-04"},{"title":"Tree Ensembles for Contextual Bandits","abstract":"We propose a new framework for contextual multi-armed bandits based on tree ensembles. Our framework adapts two widely used bandit methods, Upper Confidence Bound and Thompson Sampling, for both standard and combinatorial settings. As part of this framework, we propose a novel method of estimating the uncertainty in tree ensemble predictions. We further demonstrate the effectiveness of our framework via several exper","authors":["Nilsson, Hannes","Johansson, Rikard","Åkerblom, Niklas","Chehreghani, Morteza Haghir"],"url":"https://arxiv.org/abs/2402.06963","arxiv_id":"2402.06963","published":"2025-12-04"},{"title":"Accelerating data-driven algorithm selection for combinatorial partitioning problems","abstract":"Data-driven algorithm selection is a powerful approach for choosing effective heuristics for computational problems. It operates by evaluating a set of candidate algorithms on a collection of representative training instances and selecting the one with the best empirical performance. However, running each algorithm on every training instance is computationally expensive, making scalability a central challenge. In pra","authors":["Chatziafratis, Vaggos","Karmarkar, Ishani","Li, Yingxi","Vitercik, Ellen"],"url":"https://arxiv.org/abs/2402.14332","arxiv_id":"2402.14332","published":"2025-12-04"},{"title":"Marginalize, Rather than Impute: Probabilistic Wind Power Forecasting with Incomplete Data","abstract":"Machine learning methods are widely and successfully used for probabilistic wind power forecasting, yet the pervasive issue of missing values (e.g., due to sensor faults or communication outages) has received limited attention. The prevailing practice is impute-then-predict, but conditioning on point imputations biases parameter estimates and fails to propagate uncertainty from missing features. Our approach treats m","authors":["Wen, Honglin","Pinson, Pierre","Gu, Jie","Jin, Zhijian"],"url":"https://arxiv.org/abs/2403.03631","arxiv_id":"2403.03631","published":"2025-12-04"},{"title":"Variational Inference of Parameters in Opinion Dynamics Models","abstract":"Despite the frequent use of agent-based models (ABMs) for studying social phenomena, parameter estimation remains a challenge, often relying on costly simulation-based heuristics. This work uses variational inference to estimate the parameters of an opinion dynamics ABM, by transforming the estimation problem into an optimization task that can be solved directly. Our proposal relies on probabilistic generative ABMs (","authors":["Lenti, Jacopo","Silvestri, Fabrizio","Morales, Gianmarco De Francisci"],"url":"https://arxiv.org/abs/2403.05358","arxiv_id":"2403.05358","published":"2025-12-04"},{"title":"LLM-based agents for automating the enhancement of user story quality: An early report","abstract":"In agile software development, maintaining high-quality user stories is crucial, but also challenging. This study explores the use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams. We developed a reference model for an Autonomous LLM-based Agent System and implemented it at the company. The quality of user stories in the study and the effectiveness of thes","authors":["Zhang, Zheying","Rayhan, Maruf","Herda, Tomas","Goisauf, Manuel","Abrahamsson, Pekka"],"url":"https://arxiv.org/abs/2403.09442","arxiv_id":"2403.09442","published":"2025-12-04"},{"title":"Are you a robot? Detecting Autonomous Vehicles from Behavior Analysis","abstract":"The tremendous hype around autonomous driving is eagerly calling for emerging and novel technologies to support advanced mobility use cases. As car manufactures keep developing SAE level 3+ systems to improve the safety and comfort of passengers, traffic authorities need to establish new procedures to manage the transition from human-driven to fully-autonomous vehicles while providing a feedback-loop mechanism to fin","authors":["Maresca, Fabio","Grazioli, Filippo","Albanese, Antonio","Sciancalepore, Vincenzo","Negri, Gianpiero","Costa-Perez, Xavier"],"url":"https://arxiv.org/abs/2403.09571","arxiv_id":"2403.09571","published":"2025-12-04"},{"title":"MAP-Former: Multi-Agent-Pair Gaussian Joint Prediction","abstract":"There is a gap in risk assessment of trajectories between the trajectory information coming from a traffic motion prediction module and what is actually needed. Closing this gap necessitates advancements in prediction beyond current practices. Existing prediction models yield joint predictions of agents' future trajectories with uncertainty weights or marginal Gaussian probability density functions (PDFs) for sin","authors":["Steiner, Marlon","Klemp, Marvin","Stiller, Christoph"],"url":"https://arxiv.org/abs/2404.19283","arxiv_id":"2404.19283","published":"2025-12-04"},{"title":"On the Volatility of Shapley-Based Contribution Metrics in Federated Learning","abstract":"Federated learning (FL) is a collaborative and privacy-preserving Machine Learning paradigm, allowing the development of robust models without the need to centralize sensitive data. A critical challenge in FL lies in fairly and accurately allocating contributions from diverse participants. Inaccurate allocation can undermine trust, lead to unfair compensation, and thus participants may lack the incentive to join or a","authors":["Geimer, Arno","Fiz, Beltran","State, Radu"],"url":"https://arxiv.org/abs/2405.08044","arxiv_id":"2405.08044","published":"2025-12-04"},{"title":"Margin-aware Preference Optimization for Aligning Diffusion Models without Reference","abstract":"Modern preference alignment methods, such as DPO, rely on divergence regularization to a reference model for training stability-but this creates a fundamental problem we call "reference mismatch." In this paper, we investigate the negative impacts of reference mismatch in aligning text-to-image (T2I) diffusion models, showing that larger reference mismatch hinders effective adaptation given the same amount of","authors":["Hong, Jiwoo","Paul, Sayak","Lee, Noah","Rasul, Kashif","Thorne, James","Jeong, Jongheon"],"url":"https://arxiv.org/abs/2406.06424","arxiv_id":"2406.06424","published":"2025-12-04"},{"title":"Rethinking Data Input for Point Cloud Upsampling","abstract":"Point cloud upsampling is crucial for tasks like 3D reconstruction. While existing methods rely on patch-based inputs, and there is no research discussing the differences and principles between point cloud model full input and patch based input. Ergo, we propose a novel approach using whole model inputs i.e. Average Segment input. Our experiments on PU1K and ABC datasets reveal that patch-based inputs consistently ou","authors":["Zhang, Tongxu"],"url":"https://arxiv.org/abs/2407.04476","arxiv_id":"2407.04476","published":"2025-12-04"},{"title":"SLO-aware GPU Frequency Scaling for Energy Efficient LLM Inference Serving","abstract":"As Large Language Models (LLMs) gain traction, their reliance on power-hungry GPUs places ever-increasing energy demands, raising environmental and monetary concerns. Inference dominates LLM workloads, presenting a critical challenge for providers: minimizing energy costs under Service-Level Objectives (SLOs) that ensure optimal user experience. In this paper, we present \\textit{throttLL'eM}, a framework that red","authors":["Kakolyris, Andreas Kosmas","Masouros, Dimosthenis","Vavaroutsos, Petros","Xydis, Sotirios","Soudris, Dimitrios"],"url":"https://arxiv.org/abs/2408.05235","arxiv_id":"2408.05235","published":"2025-12-04"},{"title":"Casper: Prompt Sanitization for Protecting User Privacy in Web-Based Large Language Models","abstract":"Web-based Large Language Model (LLM) services have been widely adopted and have become an integral part of our Internet experience. Third-party plugins enhance the functionalities of LLM by enabling access to real-world data and services. However, the privacy consequences associated with these services and their third-party plugins are not well understood. Sensitive prompt data are stored, processed, and shared by cl","authors":["Chong, Chun Jie","Hou, Chenxi","Yao, Zhihao","Talebi, Seyed Mohammadjavad Seyed"],"url":"https://arxiv.org/abs/2408.07004","arxiv_id":"2408.07004","published":"2025-12-04"},{"title":"Large Language Model-Based Agents for Software Engineering: A Survey","abstract":"The recent advance in Large Language Models (LLMs) has shaped a new paradigm of AI agents, i.e., LLM-based agents. Compared to standalone LLMs, LLM-based agents substantially extend the versatility and expertise of LLMs by enhancing LLMs with the capabilities of perceiving and utilizing external resources and tools. To date, LLM-based agents have been applied and shown remarkable effectiveness in Software Engineering","authors":["Liu, Junwei","Wang, Kaixin","Chen, Yixuan","Peng, Xin","Chen, Zhenpeng","Zhang, Lingming"],"url":"https://arxiv.org/abs/2409.02977","arxiv_id":"2409.02977","published":"2025-12-04"},{"title":"IW-Bench: Evaluating Large Multimodal Models for Converting Image-to-Web","abstract":"Recently advancements in large multimodal models have led to significant strides in image comprehension capabilities. Despite these advancements, there is a lack of the robust benchmark specifically for assessing the Image-to-Web conversion proficiency of these large models. Primarily, it is essential to ensure the integrity of the web elements generated. These elements comprise visible and invisible categories. Prev","authors":["Guo, Hongcheng","Zhang, Wei","Chen, Junhao","Gu, Yaonan","Yang, Jian","Du, Junjia"],"url":"https://arxiv.org/abs/2409.18980","arxiv_id":"2409.18980","published":"2025-12-04"},{"title":"How to Train Long-Context Language Models (Effectively)","abstract":"We study continued training and supervised fine-tuning (SFT) of a language model (LM) to make effective use of long-context information. We first establish a reliable evaluation protocol to guide model development -- instead of perplexity or simple needle-in-a-haystack (NIAH) tests, we use a broad set of long-context downstream tasks, and we evaluate models after SFT as this better reveals long-context abilities. Sup","authors":["Gao, Tianyu","Wettig, Alexander","Yen, Howard","Chen, Danqi"],"url":"https://arxiv.org/abs/2410.02660","arxiv_id":"2410.02660","published":"2025-12-04"},{"title":"The Duality of Generative AI and Reinforcement Learning in Robotics: A Review","abstract":"Recently, generative AI and reinforcement learning (RL) have been redefining what is possible for AI agents that take information flows as input and produce intelligent behavior. As a result, we are seeing similar advancements in embodied AI and robotics for control policy generation. Our review paper examines the integration of generative AI models with RL to advance robotics. Our primary focus is on the duality bet","authors":["Moroncelli, Angelo","Soni, Vishal","Forgione, Marco","Piga, Dario","Spahiu, Blerina","Roveda, Loris"],"url":"https://arxiv.org/abs/2410.16411","arxiv_id":"2410.16411","published":"2025-12-04"},{"title":"DynamicCity: Large-Scale 4D Occupancy Generation from Dynamic Scenes","abstract":"Urban scene generation has been developing rapidly recently. However, existing methods primarily focus on generating static and single-frame scenes, overlooking the inherently dynamic nature of real-world driving environments. In this work, we introduce DynamicCity, a novel 4D occupancy generation framework capable of generating large-scale, high-quality dynamic 4D scenes with semantics. DynamicCity mainly consists o","authors":["Bian, Hengwei","Kong, Lingdong","Xie, Haozhe","Pan, Liang","Qiao, Yu","Liu, Ziwei"],"url":"https://arxiv.org/abs/2410.18084","arxiv_id":"2410.18084","published":"2025-12-04"},{"title":"From Pixels to Prose: Advancing Multi-Modal Language Models for Remote Sensing","abstract":"Remote sensing has evolved from simple image acquisition to complex systems capable of integrating and processing visual and textual data. This review examines the development and application of multi-modal language models (MLLMs) in remote sensing, focusing on their ability to interpret and describe satellite imagery using natural language. We cover the technical underpinnings of MLLMs, including dual-encoder archit","authors":["Sun, Xintian","Peng, Benji","Zhang, Charles","Jin, Fei","Niu, Qian","Liu, Junyu"],"url":"https://arxiv.org/abs/2411.05826","arxiv_id":"2411.05826","published":"2025-12-04"},{"title":"StableV2V: Stablizing Shape Consistency in Video-to-Video Editing","abstract":"Recent advancements of generative AI have significantly promoted content creation and editing, where prevailing studies further extend this exciting progress to video editing. In doing so, these studies mainly transfer the inherent motion patterns from the source videos to the edited ones, where results with inferior consistency to user prompts are often observed, due to the lack of particular alignments between the ","authors":["Liu, Chang","Li, Rui","Zhang, Kaidong","Lan, Yunwei","Liu, Dong"],"url":"https://arxiv.org/abs/2411.11045","arxiv_id":"2411.11045","published":"2025-12-04"},{"title":"Concentration of Cumulative Reward in Markov Decision Processes","abstract":"In this paper, we investigate the concentration properties of cumulative reward in Markov Decision Processes (MDPs), focusing on both asymptotic and non-asymptotic settings. We introduce a unified approach to characterize reward concentration in MDPs, covering both infinite-horizon settings (i.e., average and discounted reward frameworks) and finite-horizon setting. Our asymptotic results include the law of large num","authors":["Sayedana, Borna","Caines, Peter E.","Mahajan, Aditya"],"url":"https://arxiv.org/abs/2411.18551","arxiv_id":"2411.18551","published":"2025-12-04"}],"history":{"events":[{"year":2012,"text":"\"Il Canto degli Italiani\" officially became the national anthem of Italy, 66 years after it was provisionally chosen following the birth of the Italian Republic.","url":"https://en.wikipedia.org/wiki/Canto_degli_italiani"},{"year":2006,"text":"Six black teenagers assaulted a white student in Jena, Louisiana; the subsequent court cases became a cause célèbre for perceived racial injustice in the United States.","url":"https://en.wikipedia.org/wiki/Jena_Six"},{"year":1992,"text":"U.S. president George H. W. Bush ordered American troops into Somalia to help provide humanitarian aid and restore order during the ongoing Somali Civil War.","url":"https://en.wikipedia.org/wiki/George_H._W._Bush"},{"year":1986,"text":"The MV Amazon Venture oil tanker starts leaking while at the port of Savannah, resulting in an oil spill of approximately 500,000 US gallons (1,900,000 L).","url":"https://en.wikipedia.org/wiki/Port_of_Savannah"},{"year":1980,"text":"The English rock group Led Zeppelin officially disbanded.","url":"https://en.wikipedia.org/wiki/Led_Zeppelin"},{"year":1978,"text":"Following the murder of Mayor George Moscone, Dianne Feinstein became San Francisco's first female mayor.","url":"https://en.wikipedia.org/wiki/Assassinations_of_George_Moscone_and_Harvey_Milk"},{"year":1971,"text":"The Troubles: The Ulster Volunteer Force, an Ulster-loyalist paramilitary group, detonated a bomb at a Catholic-owned pub in Belfast, Northern Ireland, killing 15 people.","url":"https://en.wikipedia.org/wiki/The_Troubles"},{"year":1971,"text":"Indo-Pakistani War: The Indian Navy launched a successful attack against the Pakistan Navy at Karachi, sinking three ships with no Indian casualties.","url":"https://en.wikipedia.org/wiki/India%E2%80%93Pakistan_war_of_1971"},{"year":1969,"text":"Fred Hampton, the leader of the Illinois chapter of the Black Panther Party, and Mark Clark were killed in a raid by Chicago police officers in what many scholars consider an illegal assassination.","url":"https://en.wikipedia.org/wiki/Fred_Hampton"},{"year":1928,"text":"Cosmo Gordon Lang was enthroned as the Archbishop of Canterbury, the first bachelor to be appointed in 150 years.","url":"https://en.wikipedia.org/wiki/Cosmo_Gordon_Lang"},{"year":1915,"text":"World War I: Senior British and French figures, including prime ministers H. H. Asquith and Aristide Briand, met at Calais to discuss the future of the Salonika Front.","url":"https://en.wikipedia.org/wiki/World_War_I"},{"year":1909,"text":"The Montreal Canadiens, the oldest professional ice hockey club in the world, were founded as a charter member of the National Hockey Association.","url":"https://en.wikipedia.org/wiki/Montreal_Canadiens"},{"year":1909,"text":"The first Grey Cup, the championship game of the Canadian Football League, was held in Toronto.","url":"https://en.wikipedia.org/wiki/1st_Grey_Cup"},{"year":1905,"text":"The Great Seimas of Vilnius met to discuss national concerns within Lithuania: they decided to demand wide political autonomy within the Russian Empire.","url":"https://en.wikipedia.org/wiki/Great_Seimas_of_Vilnius"},{"year":1893,"text":"First Matabele War: A patrol of 34 British South Africa Company soldiers was ambushed and annihilated by more than 3,000 Matabele warriors.","url":"https://en.wikipedia.org/wiki/First_Matabele_War"},{"year":1872,"text":"The American brigantine Mary Celeste was found apparently abandoned under circumstances that remain unknown.","url":"https://en.wikipedia.org/wiki/Brigantine"},{"year":1829,"text":"Sati, the Hindu funeral custom of a widow's self-immolation on her husband's pyre, was prohibited by Lord William Bentinck in parts of British India after years of campaigning by Ram Mohan Roy (pictured).","url":"https://en.wikipedia.org/wiki/Sati_(practice)"},{"year":1639,"text":"Jeremiah Horrocks and William Crabtree made the first successful observation of a transit of Venus (example pictured) from Earth.","url":"https://en.wikipedia.org/wiki/Jeremiah_Horrocks"}],"births":[{"year":2003,"text":"Jackson Holliday, American baseball player","url":"https://en.wikipedia.org/wiki/Jackson_Holliday"},{"year":2003,"text":"Kim Do-ah, South Korean singer and actress","url":"https://en.wikipedia.org/wiki/Kim_Do-ah"},{"year":2002,"text":"María Dueñas, Spanish violinist and composer","url":"https://en.wikipedia.org/wiki/Mar%C3%ADa_Due%C3%B1as_(violinist)"},{"year":1999,"text":"Kim Do-yeon, South Korean singer and actress","url":"https://en.wikipedia.org/wiki/Kim_Do-yeon_(singer)"},{"year":1999,"text":"Kang Mi-na, South Korean actress and singer","url":"https://en.wikipedia.org/wiki/Kang_Mi-na"},{"year":1996,"text":"Diogo Jota, Portuguese footballer (died 2025)","url":"https://en.wikipedia.org/wiki/Diogo_Jota"},{"year":1996,"text":"Sebastián Vegas, Chilean footballer","url":"https://en.wikipedia.org/wiki/Sebasti%C3%A1n_Vegas"},{"year":1994,"text":"Gabriel Lundberg, Danish basketball player","url":"https://en.wikipedia.org/wiki/Gabriel_Lundberg"}],"deaths":[{"year":2024,"text":"Princess Birgitta of Sweden, Swedish royal (born 1937)","url":"https://en.wikipedia.org/wiki/Princess_Birgitta_of_Sweden"},{"year":2022,"text":"Bob McGrath, American singer and actor (born 1932)","url":"https://en.wikipedia.org/wiki/Bob_McGrath"},{"year":2022,"text":"Patrick Tambay, French race car driver (born 1949)","url":"https://en.wikipedia.org/wiki/Patrick_Tambay"},{"year":2017,"text":"Shashi Kapoor, Indian actor (born 1938)","url":"https://en.wikipedia.org/wiki/Shashi_Kapoor"},{"year":2016,"text":"Patricia Robins, British writer and WAAF officer (born 1921)","url":"https://en.wikipedia.org/wiki/Patricia_Robins"},{"year":2015,"text":"Bill Bennett, Canadian lawyer and politician, 27th Premier of British Columbia (born 1932)","url":"https://en.wikipedia.org/wiki/Bill_Bennett"},{"year":2015,"text":"Robert Loggia, American actor and director (born 1930)","url":"https://en.wikipedia.org/wiki/Robert_Loggia"},{"year":2015,"text":"Yossi Sarid, Israeli journalist and politician, 15th Israeli Minister of Education (born 1940)","url":"https://en.wikipedia.org/wiki/Yossi_Sarid"}]},"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."}