Computer Science
The Prasthanatrayi -- the ten principal Upanisads, the Brahmasutra, and the Bhagavadgita, with Sankara's commentaries (bhasya) -- is the foundational corpus of Advaita Vedanta. Continuous euphonic combination (sandhi), long compounds…
Modular miniature robots could provide scalable function in constrained environments, but coordinating many imperfect modules remains difficult when computation, communication and reliability are limited. A central robotics challenge is to…
Harmful online communication often contains slang, coded terms, abbreviations, and community-specific expressions, which make messages difficult to interpret. This paper presents an exploratory study of interpretation difficulty in Discord…
Bubbly flows exhibit complex multiscale dynamics, with deformable bubbles interacting through the surrounding liquid and giving rise to strongly coupled kinematic and morphological behavior. We present BubbleSH, a bubbly flows dataset…
Ride-hailing mobile apps have become an essential feature in the mobility ecosystem in Africa, offering much safer and much more affordable rides. Although user bases have increased and the number of daily trips has proliferated, reports of…
Nowadays, mobile forensics is less explored in Digital Forensics case analysis due to the increase in data protection mechanisms implemented by tech companies (i.e., Google for Android and Apple for iOS). For example, the physical…
Claims about the universality of human concepts have been predominantly assessed through linguistic similarity across languages and cultures. However, words are effective as communication devices because they compress rich experiential…
Deep neural networks are widely deployed in high-stakes visual applications where interpretability is critical, yet existing explanations face a trade-off: post-hoc concept methods recover factors that are faithful to a model's behavior but…
Broadcasting in graphs refers to the information dissemination problem in which a source node has an atomic piece of information to be distributed to all the nodes of a graph. In the standard telephone model, broadcasting proceeds as a…
In many realistic scenarios, large volumes of time series data are generated with limited or expensive annotations. This limitation makes supervised learning methods difficult to apply and leads to the use of unsupervised approaches capable…
A minimal perfect hash function (minimal PHF) is a data structure mapping a static set of $n$ keys to $n$ bins without collisions. Two natural generalizations are minimal $k$-PHFs where $n$ keys are mapped to $n/k$ bins of capacity $k$…
Objective: To evaluate robotic controller interfaces for interventional neuroradiology procedures in-vitro incorporating a force-sensing platform to assess safety. Methods: A custom endovascular robot, device-mimicking controller, and…
Reinforcement learning (RL) enables the synthesis of control policies directly from data, making it highly appealing for complex cyber-physical systems (CPSs) and robotics. A persistent challenge, however, is ensuring strict, hard safety…
One of the expected abilities of vision-language models (VLMs) is spatial reasoning ability based on a given text and image. To evaluate the spatial reasoning abilities of VLMs, we focus on the use of spatial deictic expressions, which are…
Rabindra Sangeet, the body of songs written and composed by Rabindranath Tagore, occupies a distinctive position in Indian music by combining poetic expression with melodic ideas drawn from Hindustani rags, Bengali folk traditions, tappa,…
Ultrasound image segmentation is essential for delineating anatomical structures and lesions, providing the foundation for accurate diagnosis. While the Segment Anything Model (SAM) has demonstrated remarkable success on natural images, its…
This study investigates the presence and propagation of bias within Neural Networks through a comprehensive multi-level analysis spanning the learned latent space, layer activations, and the network's parameters. Based on this taxonomy, we…
Explainability remains a key issue in reinforcement learning (RL). Distilling an interpretable policy from an agent trained in a complex environment is particularly challenging when the action space is continuous. We introduce ORCAID, a…
Deep generative models offer a promising paradigm for topology optimization, enabling rapid design exploration. However, these approaches lack intrinsic physics guidance, often leading to poor generalizability across unseen boundary…
Video object segmentation (VOS) is a fundamental task in video understanding, requiring accurate delineation and consistent tracking of objects across frames. While supervised methods achieve strong performance, they rely on densely…