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In this paper, we formulate a framework for word embedding, referred to as Word-Context Classification (WCC), that generalizes SGN to a wide family of models. The framework, which uses some ``noise examples'', is justified through theoretical analysis. The impact of noise distribution on the ","authors":["Liu, Dezhi","Zhang, Richong","Wang, Ziqiao"],"url":"https://arxiv.org/abs/2009.04413","arxiv_id":"2009.04413","published":"2025-12-03"},{"title":"DA-MUSIC: Data-Driven DoA Estimation via Deep Augmented MUSIC Algorithm","abstract":"Direction of arrival (DoA) estimation of multiple signals is pivotal in sensor array signal processing. A popular multi-signal DoA estimation method is the multiple signal classification (MUSIC) algorithm, which enables high-performance super-resolution DoA recovery while being highly applicable in practice. MUSIC is a model-based algorithm, relying on an accurate mathematical description of the relationship between ","authors":["Merkofer, Julian P.","Revach, Guy","Shlezinger, Nir","Routtenberg, Tirza","van Sloun, Ruud J. G."],"url":"https://arxiv.org/abs/2109.10581","arxiv_id":"2109.10581","published":"2025-12-03"},{"title":"Learning Robust Convolutional Neural Networks with Relevant Feature Focusing via Explanations","abstract":"Existing image recognition techniques based on convolutional neural networks (CNNs) basically assume that the training and test datasets are sampled from i.i.d distributions. However, this assumption is easily broken in the real world because of the distribution shift that occurs when the co-occurrence relations between objects and backgrounds in input images change. Under this type of distribution shift, CNNs learn ","authors":["Adachi, Kazuki","Yamaguchi, Shin'ya"],"url":"https://arxiv.org/abs/2202.04237","arxiv_id":"2202.04237","published":"2025-12-03"},{"title":"Gaussian and Non-Gaussian Universality of Data Augmentation","abstract":"We provide universality results that quantify how data augmentation affects the variance and limiting distribution of estimates through simple surrogates, and analyze several specific models in detail. The results confirm some observations made in machine learning practice, but also lead to unexpected findings: Data augmentation may increase rather than decrease the uncertainty of estimates, such as the empirical pre","authors":["Huang, Kevin Han","Orbanz, Peter","Austern, Morgane"],"url":"https://arxiv.org/abs/2202.09134","arxiv_id":"2202.09134","published":"2025-12-03"},{"title":"Covariance-aware Feature Alignment with Pre-computed Source Statistics for Test-time Adaptation to Multiple Image Corruptions","abstract":"Real-world image recognition systems often face corrupted input images, which cause distribution shifts and degrade the performance of models. These systems often use a single prediction model in a central server and process images sent from various environments, such as cameras distributed in cities or cars. Such single models face images corrupted in heterogeneous ways in test time. Thus, they require to instantly ","authors":["Adachi, Kazuki","Yamaguchi, Shin'ya","Kumagai, Atsutoshi"],"url":"https://arxiv.org/abs/2204.13263","arxiv_id":"2204.13263","published":"2025-12-03"},{"title":"Permutation-Aware Action Segmentation via Unsupervised Frame-to-Segment Alignment","abstract":"This paper presents an unsupervised transformer-based framework for temporal activity segmentation which leverages not only frame-level cues but also segment-level cues. This is in contrast with previous methods which often rely on frame-level information only. Our approach begins with a frame-level prediction module which estimates framewise action classes via a transformer encoder. The frame-level prediction module","authors":["Tran, Quoc-Huy","Mehmood, Ahmed","Ahmed, Muhammad","Naufil, Muhammad","Zafar, Anas","Konin, Andrey"],"url":"https://arxiv.org/abs/2305.19478","arxiv_id":"2305.19478","published":"2025-12-03"},{"title":"Global universal approximation of functional input maps on weighted spaces","abstract":"We introduce so-called functional input neural networks defined on a possibly infinite dimensional weighted space with values also in a possibly infinite dimensional output space. To this end, we use an additive family to map the input weighted space to the hidden layer, on which a non-linear scalar activation function is applied to each neuron, and finally return the output via some linear readouts. Relying on Stone","authors":["Cuchiero, Christa","Schmocker, Philipp","Teichmann, Josef"],"url":"https://arxiv.org/abs/2306.03303","arxiv_id":"2306.03303","published":"2025-12-03"},{"title":"Predicting Human Perceptions of Robot Performance During Navigation Tasks","abstract":"Understanding human perceptions of robot performance is crucial for designing socially intelligent robots that can adapt to human expectations. Current approaches often rely on surveys, which can disrupt ongoing human-robot interactions. As an alternative, we explore predicting people's perceptions of robot performance using non-verbal behavioral cues and machine learning techniques. We contribute the SEAN TOGETH","authors":["Zhang, Qiping","Tsoi, Nathan","Nagib, Mofeed","Choi, Booyeon","Tan, Jie","Chiang, Hao-Tien Lewis"],"url":"https://arxiv.org/abs/2310.11590","arxiv_id":"2310.11590","published":"2025-12-03"},{"title":"Large Language Models for Robotics: A Survey","abstract":"The human ability to learn, generalize, and control complex manipulation tasks through multi-modality feedback suggests a unique capability, which we refer to as dexterity intelligence. Understanding and assessing this intelligence is a complex task. Amidst the swift progress and extensive proliferation of large language models (LLMs), their applications in the field of robotics have garnered increasing attention. LL","authors":["Zeng, Fanlong","Gan, Wensheng","Huai, Zezheng","Sun, Lichao","Chen, Hechang","Wang, Yongheng"],"url":"https://arxiv.org/abs/2311.07226","arxiv_id":"2311.07226","published":"2025-12-03"},{"title":"Computational Copyright: Towards A Royalty Model for Music Generative AI","abstract":"The rapid rise of generative AI has intensified copyright and economic tensions in creative industries, particularly in music. Current approaches addressing this challenge often focus on preventing infringement or establishing one-time licensing, which fail to provide the sustainable, recurring economic incentives necessary to maintain creative ecosystems. To address this gap, we propose Generative Content ID, a fram","authors":["Deng, Junwei","Jiang, Xirui","Zhang, Shiyuan","Zhang, Shichang","Lakkaraju, Himabindu","Gao, Ruijiang"],"url":"https://arxiv.org/abs/2312.06646","arxiv_id":"2312.06646","published":"2025-12-03"},{"title":"PERP: Rethinking the Prune-Retrain Paradigm in the Era of LLMs","abstract":"Neural Networks can be effectively compressed through pruning, significantly reducing storage and compute demands while maintaining predictive performance. Simple yet effective methods like magnitude pruning remove less important parameters and typically require a costly retraining procedure to restore performance. However, with the rise of LLMs, full retraining has become infeasible due to memory and compute constra","authors":["Zimmer, Max","Andoni, Megi","Spiegel, Christoph","Pokutta, Sebastian"],"url":"https://arxiv.org/abs/2312.15230","arxiv_id":"2312.15230","published":"2025-12-03"},{"title":"Diffusion model for relational inference","abstract":"Dynamical behaviors of complex interacting systems, including brain activities, financial price movements, and physical collective phenomena, are associated with underlying interactions between the system's components. The issue of uncovering interaction relations in such systems using observable dynamics is called relational inference. In this study, we propose a Diffusion model for Relational Inference (DiffRI)","authors":["Zheng, Shuhan","Li, Ziqiang","Fujiwara, Kantaro","Tanaka, Gouhei"],"url":"https://arxiv.org/abs/2401.16755","arxiv_id":"2401.16755","published":"2025-12-03"},{"title":"Unifying Linear-Time Attention via Latent Probabilistic Modelling","abstract":"Transformers have achieved state-of-the-art results across a range of domains, but their quadratic attention mechanism poses significant challenges for long-sequence modelling. Recent efforts to design linear-time attention mechanisms have yielded more scalable alternatives, yet often at the cost of performance, particularly on discrete data such as language. In this work, we revisit linear attention through the lens","authors":["Dolga, Rares","Maystre, Lucas","Cobzarenco, Marius","Barber, David"],"url":"https://arxiv.org/abs/2402.17512","arxiv_id":"2402.17512","published":"2025-12-03"},{"title":"ContourDiff: Unpaired Medical Image Translation with Structural Consistency","abstract":"Accurately translating medical images between different modalities, such as Computed Tomography (CT) to Magnetic Resonance Imaging (MRI), has numerous downstream clinical and machine learning applications. While several methods have been proposed to achieve this, they often prioritize perceptual quality with respect to output domain features over preserving anatomical fidelity. However, maintaining anatomy during tra","authors":["Chen, Yuwen","Konz, Nicholas","Gu, Hanxue","Dong, Haoyu","Chen, Yaqian","Li, Lin"],"url":"https://arxiv.org/abs/2403.10786","arxiv_id":"2403.10786","published":"2025-12-03"},{"title":"Test-time Similarity Modification for Person Re-identification toward Temporal Distribution Shift","abstract":"Person re-identification (re-id), which aims to retrieve images of the same person in a given image from a database, is one of the most practical image recognition applications. In the real world, however, the environments that the images are taken from change over time. This causes a distribution shift between training and testing and degrades the performance of re-id. To maintain re-id performance, models should co","authors":["Adachi, Kazuki","Enomoto, Shohei","Sasaki, Taku","Yamaguchi, Shin'ya"],"url":"https://arxiv.org/abs/2403.14114","arxiv_id":"2403.14114","published":"2025-12-03"},{"title":"Brain-aligning of semantic vectors improves neural decoding of visual stimuli","abstract":"The development of algorithms to accurately decode neural information has long been a research focus in the field of neuroscience. Brain decoding typically involves training machine learning models to map neural data onto a preestablished vector representation of stimulus features. These vectors are usually derived from image- and/or text-based feature spaces. Nonetheless, the intrinsic characteristics of these vecto","authors":["Vafaei, Shirin","Fukuma, Ryohei","Yanagisawa, Takufumi","Yang, Huixiang","Oshino, Satoru","Tani, Naoki"],"url":"https://arxiv.org/abs/2403.15176","arxiv_id":"2403.15176","published":"2025-12-03"},{"title":"CT-GLIP: 3D Grounded Language-Image Pretraining with CT Scans and Radiology Reports for Full-Body Scenarios","abstract":"3D medical vision-language (VL) pretraining has shown potential in radiology by leveraging large-scale multimodal datasets with CT-report pairs. However, existing methods primarily rely on a global VL alignment directly adapted from 2D scenarios. The entire 3D image is transformed into one global embedding, resulting in a loss of sparse but critical semantics essential for accurately aligning with the corresponding d","authors":["Lin, Jingyang","Xia, Yingda","Zhang, Jianpeng","Yan, Ke","Cao, Kai","Lu, Le"],"url":"https://arxiv.org/abs/2404.15272","arxiv_id":"2404.15272","published":"2025-12-03"},{"title":"Anomalous Change Point Detection Using Probabilistic Predictive Coding","abstract":"Change point detection (CPD) and anomaly detection (AD) are essential techniques in various fields to identify abrupt changes or abnormal data instances. However, existing methods are often constrained to univariate data, face scalability challenges with large datasets due to computational demands, and experience reduced performance with high-dimensional or intricate data, as well as hidden anomalies. Furthermore, th","authors":["Hup, Roelof G.","Merkofer, Julian P.","Bhogal, Alex A.","van Sloun, Ruud J. G.","Haakma, Reinder","Vullings, Rik"],"url":"https://arxiv.org/abs/2405.15727","arxiv_id":"2405.15727","published":"2025-12-03"},{"title":"XXLTraffic: Expanding and Extremely Long Traffic forecasting beyond test adaptation","abstract":"Traffic forecasting is crucial for smart cities and intelligent transportation initiatives, where deep learning has made significant progress in modeling complex spatio-temporal patterns in recent years. However, current public datasets have limitations in reflecting the distribution shift nature of real-world scenarios, characterized by continuously evolving infrastructures, varying temporal distributions, and long ","authors":["Yin, Du","Xue, Hao","Prabowo, Arian","Ao, Shuang","Salim, Flora"],"url":"https://arxiv.org/abs/2406.12693","arxiv_id":"2406.12693","published":"2025-12-03"},{"title":"Aligning Diffusion Models with Noise-Conditioned Perception","abstract":"Recent advancements in human preference optimization, initially developed for Language Models (LMs), have shown promise for text-to-image Diffusion Models, enhancing prompt alignment, visual appeal, and user preference. Unlike LMs, Diffusion Models typically optimize in pixel or VAE space, which does not align well with human perception, leading to slower and less efficient training during the preference alignment st","authors":["Gambashidze, Alexander","Kulikov, Anton","Sosnin, Yuriy","Makarov, Ilya"],"url":"https://arxiv.org/abs/2406.17636","arxiv_id":"2406.17636","published":"2025-12-03"},{"title":"Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach","abstract":"A major challenge facing the world is the provision of equitable and universal access to quality education. Recent advances in generative AI (gen AI) have created excitement about the potential of new technologies to offer a personal tutor for every learner and a teaching assistant for every teacher. The full extent of this dream, however, has not yet materialised. We argue that this is primarily due to the difficult","authors":["Jurenka, Irina","Kunesch, Markus","McKee, Kevin R.","Gillick, Daniel","Zhu, Shaojian","Wiltberger, Sara"],"url":"https://arxiv.org/abs/2407.12687","arxiv_id":"2407.12687","published":"2025-12-03"},{"title":"A process algebraic framework for multi-agent dynamic epistemic systems","abstract":"This paper combines the classical model of labeled transition systems with the epistemic model for reasoning about knowledge. The result is a unifying framework for modeling and analyzing multi-agent, knowledge-based, dynamic systems. On the modeling side, we propose a process algebraic, agent-oriented specification language that makes such a framework easy to use for practical purposes. On the verification side, we ","authors":["Aldini, Alessandro"],"url":"https://arxiv.org/abs/2407.17537","arxiv_id":"2407.17537","published":"2025-12-03"},{"title":"Pre-trained Language Models Improve the Few-shot Prompt Ability of Decision Transformer","abstract":"Decision Transformer (DT) has emerged as a promising class of algorithms in offline reinforcement learning (RL) tasks, leveraging pre-collected datasets and Transformer's capability to model long sequences. Recent works have demonstrated that using parts of trajectories from training tasks as prompts in DT enhances its performance on unseen tasks, giving rise to Prompt-DT methods. However, collecting data from sp","authors":["Yang, Yu","Xu, Pan"],"url":"https://arxiv.org/abs/2408.01402","arxiv_id":"2408.01402","published":"2025-12-03"},{"title":"Mutually-Aware Feature Learning for Few-Shot Object Counting","abstract":"Few-shot object counting has garnered significant attention for its practicality as it aims to count target objects in a query image based on given exemplars without additional training. However, the prevailing extract-and-match approach has a shortcoming: query and exemplar features lack interaction during feature extraction since they are extracted independently and later correlated based on similarity. This can le","authors":["Jeon, Yerim","Lee, Subeen","Kim, Jihwan","Heo, Jae-Pil"],"url":"https://arxiv.org/abs/2408.09734","arxiv_id":"2408.09734","published":"2025-12-03"},{"title":"Towards a vision foundation model for comprehensive assessment of Cardiac MRI","abstract":"Cardiac magnetic resonance imaging (CMR), considered the gold standard for noninvasive cardiac assessment, is a diverse and complex modality requiring a wide variety of image processing tasks for comprehensive assessment of cardiac morphology and function. Advances in deep learning have enabled the development of state-of-the-art (SoTA) models for these tasks. However, model training is challenging due to data and la","authors":["Jacob, Athira J","Borgohain, Indraneel","Chitiboi, Teodora","Sharma, Puneet","Comaniciu, Dorin","Rueckert, Daniel"],"url":"https://arxiv.org/abs/2410.01665","arxiv_id":"2410.01665","published":"2025-12-03"}],"history":{"events":[{"year":2024,"text":"South Korean President Yoon Suk Yeol (pictured) declares martial law.","url":"https://en.wikipedia.org/wiki/Yoon_Suk_Yeol"},{"year":2009,"text":"A suicide bombing in Mogadishu, Somalia, killed 25 people, including three ministers of the Transitional Federal Government.","url":"https://en.wikipedia.org/wiki/2009_Hotel_Shamo_bombing"},{"year":1999,"text":"NASA lost contact with the Mars Polar Lander moments before it reached the atmosphere of Mars and disappeared.","url":"https://en.wikipedia.org/wiki/NASA"},{"year":1994,"text":"Sony released the PlayStation, the first computer entertainment platform to ship 100 million units.","url":"https://en.wikipedia.org/wiki/Sony_Interactive_Entertainment"},{"year":1990,"text":"Mary Robinson took office as the first female president of Ireland.","url":"https://en.wikipedia.org/wiki/Mary_Robinson"},{"year":1979,"text":"Following the result of a two-day referendum, the current Constitution of Iran was adopted.","url":"https://en.wikipedia.org/wiki/1979_Iranian_constitutional_referendum"},{"year":1979,"text":"Eleven people were crushed in a human stampede at a concert by British rock band the Who in Cincinnati, Ohio, U.S.","url":"https://en.wikipedia.org/wiki/The_Who_concert_disaster"},{"year":1976,"text":"Jamaican reggae musician Bob Marley survived an assassination attempt by seven gunmen in Kingston.","url":"https://en.wikipedia.org/wiki/Reggae"},{"year":1971,"text":"With the Pakistani Air Force launching the unsuccessful pre-emptive airstrikes on several forward Indian Air Force airbases and radar installations, the 1971 India-Pakistan War begins and India also joins the Bangladesh Liberation War, siding with Bangladesh.","url":"https://en.wikipedia.org/wiki/Pakistan_Air_Force"},{"year":1968,"text":"American singer Elvis Presley's first television special and first live performance in seven years, Singer Presents ... Elvis, was broadcast by NBC.","url":"https://en.wikipedia.org/wiki/Elvis_Presley"},{"year":1967,"text":"Cardiac surgeon Christiaan Barnard (pictured) performed the first successful human heart transplant on Louis Washkansky at Groote Schuur Hospital in Cape Town, South Africa.","url":"https://en.wikipedia.org/wiki/Cardiothoracic_surgery"},{"year":1959,"text":"The current flag and coat of arms of Singapore (pictured) were adopted, six months after the island became self-governing within the British Empire.","url":"https://en.wikipedia.org/wiki/Flag_of_Singapore"},{"year":1937,"text":"Rupert Bruce-Mitford, the spiritus rector of research on the Sutton Hoo ship burial, joined the British Museum.","url":"https://en.wikipedia.org/wiki/Rupert_Bruce-Mitford"},{"year":1927,"text":"Putting Pants on Philip, the first official film featuring the British-American comedy duo Laurel and Hardy, was released.","url":"https://en.wikipedia.org/wiki/Putting_Pants_on_Philip"},{"year":1910,"text":"Freda Du Faur became the first woman to climb Aoraki / Mount Cook, the highest peak in New Zealand.","url":"https://en.wikipedia.org/wiki/Freda_Du_Faur"},{"year":1904,"text":"Himalia, Jupiter's largest irregular moon, was discovered by Charles Dillon Perrine at the Lick Observatory in California.","url":"https://en.wikipedia.org/wiki/Himalia_(moon)"},{"year":1800,"text":"War of the Second Coalition: French forces defeated Austrian and Bavarian troops at the Battle of Hohenlinden, eventually resulting in the Austrians signing the Treaty of Lunéville.","url":"https://en.wikipedia.org/wiki/War_of_the_Second_Coalition"},{"year":1283,"text":"During the First Mongol invasion of Burma, the fort at Ngasaunggyan was overrun after a two-month siege.","url":"https://en.wikipedia.org/wiki/First_Mongol_invasion_of_Burma"}],"births":[{"year":1995,"text":"Julius Honka, Finnish ice hockey player","url":"https://en.wikipedia.org/wiki/Julius_Honka"},{"year":1995,"text":"Angèle, Belgian singer","url":"https://en.wikipedia.org/wiki/Ang%C3%A8le_(singer)"},{"year":1994,"text":"Jake T. Austin, American actor","url":"https://en.wikipedia.org/wiki/Jake_T._Austin"},{"year":1994,"text":"Lil Baby, American rapper","url":"https://en.wikipedia.org/wiki/Lil_Baby"},{"year":1994,"text":"Solomone Kata, New Zealand rugby league player","url":"https://en.wikipedia.org/wiki/Solomone_Kata"},{"year":1994,"text":"Bernarda Pera, American tennis player","url":"https://en.wikipedia.org/wiki/Bernarda_Pera"},{"year":1992,"text":"Cristian Ceballos, Spanish footballer","url":"https://en.wikipedia.org/wiki/Cristian_Ceballos"},{"year":1992,"text":"Joseph McManners, English singer-songwriter, musician and actor[citation needed]","url":"https://en.wikipedia.org/wiki/Joseph_McManners"}],"deaths":[{"year":2024,"text":"Mohamed Ali Yusuf, Somali politician (born 1944)","url":"https://en.wikipedia.org/wiki/Mohamed_Ali_Yusuf"},{"year":2019,"text":"Ragnar Ulstein, Norwegian journalist and war historian (born 1920)","url":"https://en.wikipedia.org/wiki/Ragnar_Ulstein"},{"year":2015,"text":"Gladstone Anderson, Jamaican singer and pianist (born 1934)","url":"https://en.wikipedia.org/wiki/Gladstone_Anderson"},{"year":2015,"text":"Scott Weiland, American singer-songwriter (born 1967)","url":"https://en.wikipedia.org/wiki/Scott_Weiland"},{"year":2014,"text":"Herman Badillo, Puerto Rican-American lawyer and politician (born 1929)","url":"https://en.wikipedia.org/wiki/Herman_Badillo"},{"year":2012,"text":"Jules Mikhael Al-Jamil, Iraqi-Lebanese archbishop (born 1938)","url":"https://en.wikipedia.org/wiki/Jules_Mikhael_Al-Jamil"},{"year":2011,"text":"Dev Anand, Indian actor, director, and producer (born 1923)","url":"https://en.wikipedia.org/wiki/Dev_Anand"},{"year":2010,"text":"Abdumalik Bahori, Azerbaijani poet and author (born 1927)","url":"https://en.wikipedia.org/wiki/Abdumalik_Bahori"}]},"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."}