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Computer Science and Engineering: Recent submissions

  • ScribGen: generating scribble art through metaheuristics 
    Debnath, Soumyaratna; Tiwari, Ashish; Raman, Shanmuganathan (Association for Computing Machinery (ACM), 2024-12-03)
    Scribble art, arising from chaos and randomness, remains one of the exceptionally attractive forms of art. Many works bridge the gap between sketches and images, but few translate images into meaningful chaotic expressions. ...
  • Big Data and Artificial Intelligence: 12th International Conference, BDA 2024, Hyderabad, India, December 17-20, 2024, Proceedings 
    Dasgupta, Anirban; Kiran, Rage Uday; Shawi, Radwa El; Srirama, Satish Narayana; Adhikari, Mainak (Springer, 2025-03)
    This book constitutes the proceedings of the 12th International Conference on Big Data and Artificial Intelligence, BDA 2024, held in Hyderabad, India, during December 17–20, 2024. The 16 full papers and 12 short papers ...
  • Remember this event that year? assessing temporal information and reasoning in large language models 
    Beniwal, Himanshu; Patel, Dishant; Nandagopan D., Kowsik; Ladia, Hritik; Yadav, Ankit; Singh, Mayank (Association for Computational Linguistics, 2024-11-12)
    Large Language Models (LLMs) are increasingly ubiquitous, yet their ability to retain and reason about temporal information remains limited, hindering their application in real-world scenarios where understanding the ...
  • PythonSaga: redefining the benchmark to evaluate code generating LLMs 
    Yadav, Ankit; Beniwal, Himanshu; Singh, Mayank (Association for Computational Linguistics, 2024-11-12)
    Driven by the surge in code generation using large language models (LLMs), numerous benchmarks have emerged to evaluate these LLMs capabilities. We conducted a large-scale human evaluation of *HumanEval* and *MBPP*, two ...
  • LEGOBENCH: scientific leaderboard generation benchmark 
    Singh, Shruti; Alam, Shoaib; Malwat, Husain; Singh, Mayank (Association for Computational Linguistics, 2024-11-12)
    The ever-increasing volume of paper submissions makes it difficult to stay informed about the latest state-of-the-art research. To address this challenge, we introduce LEGOBench, a benchmark for evaluating systems that ...
  • Envy-free and efficient allocations for graphical valuations 
    Misra, Neeldhara; Sethia, Aditi (Springer, 2024-10-14)
    We consider the complexity of finding envy-free allocations for the class of graphical valuations. Graphical valuations were introduced by Christodoulou et al. [14] as a structured class of valuations that admit allocations ...
  • SpiroActive: active learning for efficient data acquisition for spirometry 
    Jain, Ankita Kumari; Sharma, Nitish; Kanda, Madhav; Batra, Nipun (Cornell University Library, 2024-10)
    Respiratory illnesses are a significant global health burden. Respiratory illnesses, primarily Chronic obstructive pulmonary disease (COPD), is the seventh leading cause of poor health worldwide and the third leading cause ...
  • Faster inference time for GNNs using coarsening 
    Roy, Shubhajit; Ruparel, Hrriday; Ved, Kishan; Dasgupta, Anirban (Cornell University Library, 2024-10)
    Graph Neural Networks (GNNs) have shown remarkable success in various graph-based tasks, including node classification, node regression, graph classification, and graph regression. However, their scalability remains a ...
  • Envy-free and efficient allocations for graphical valuations 
    Misra, Neeldhara; Sethia, Aditi (Cornell University Library, 2024-10)
    We consider the complexity of finding envy-free allocations for the class of graphical valuations. Graphical valuations were introduced by Christodoulou et. al.(2023) as a structured class of valuations that admit allocations ...
  • Stingray 2: a fast and modern Python library for spectral timing 
    Bachetti, Matteo; Huppenkothen, Daniela; Stevens, Abigail; Swinbank, John; Mastroserio, Guglielmo; Lucchini, Matteo; Lai, Veronica Eleonora; Buchner, Johannes; Desai, Amogh; Joshi, Gaurav; Pisanu, Francesco; Pisupati, Sri Guru Datta; Sharma, Swapnil; Tripathi, Mihir; Vats, Dhruv (Open Journals, 2024-10)
    Stingray is an Astropy-affiliated (Astropy Collaboration et al., 2013, 2022) Python package that brings advanced timing techniques to the wider astronomical community, with a focus on high-energy astrophysics, but built ...
  • Towards effective deep neural network approach for multi-trial P300-based character recognition in brain-computer interfaces 
    Shukla, Praveen Kumar; Cecotti, Hubert; Meena, Yogesh Kumar (Cornell University Library, 2024-10)
    Brain-computer interfaces (BCIs) enable direct interaction between users and computers by decoding brain signals. This study addresses the challenges of detecting P300 event-related potentials in electroencephalograms ...
  • Predictive tree-based virtual keyboard for improved gaze typing 
    Etikikota, Hrushikesh; Meena, Yogesh Kumar (Cornell University Library, 2024-10)
    On-screen keyboard eye-typing systems are limited due to the lack of predictive text and user-centred approaches, resulting in low text entry rates and frequent recalibration. This work proposes integrating the prediction ...
  • Post-training quantization in brain-computer interfaces based on event-related potential detection 
    Cecotti, Hubert; Dhaliwal, Dalvir; Singh, Hardip; Meena, Yogesh Kumar (Cornell University Library, 2024-10)
    Post-training quantization (PTQ) is a technique used to optimize and reduce the memory footprint and computational requirements of machine learning models. It has been used primarily for neural networks. For Brain-Computer ...
  • Near optimal dual fault tolerant distance oracle 
    Dey, Dipan; Gupta, Manoj (2024-09-02)
    We present a dual fault-tolerant distance oracle for undirected and unweighted graphs. Given a set F of two edges, as well as a source node s and a destination node t, our oracle returns the length of the shortest path ...
  • D-STACK: high throughput DNN inference by effective multiplexing and spatio-temporal scheduling of GPUs 
    Dhakal, Aditya; Kulkarni, Sameer G.; Ramakrishnan, K. K. (Institute of Electrical and Electronics Engineers (IEEE), 2024-10)
    Hardware accelerators such as GPUs are required for real-time, low latency inference with Deep Neural Networks (DNN). Providing inference services in the cloud can be resource intensive, and effectively utilizing accelerators ...
  • COSAEmb: contrastive section-aware aspect embeddings for scientific articles 
    Singh, Shruti; Singh, Mayank (2024-08-16)
  • Privacy performance trade-off in web services 
    Sudhan S., Hari Hara; Hanawal, Manjesh K.; Kulkarni, Sameer G. (Institute of Electrical and Electronics Engineers (IEEE), 2024-10-08)
    Security and Privacy have become fundamental requirements of modern Internet services. Over the years, both Hypertext Transfer Protocol (HTTP) and Transport Layer Security (TLS) have evolved significantly to meet the ...
  • Demo: security vulnerabilities and network service disruptions with HTTP/3 
    Sudhan S., Hari Hara; Kulkarni, Sameer G. (Institute of Electrical and Electronics Engineers (IEEE), 2024-10-08)
    In this work, we meticulously examine and demonstrate the security vulnerabilities associated with HTTP/3 and the adversities it brings to the operations of the network services (middleboxes). HTTP/3 is built using the new ...
  • Romeo and Juliet meeting in forest like regions 
    Misra, Neeldhara; Mulpuri, Manas; Tale, Prafullkumar; Viramgami, Gaurav (Springer, 2024-09)
    The game of rendezvous with adversaries is a game on a graph played by two players: Facilitator and Divider. Facilitator has two agents and Divider has a team of k ≥ 1 agents. While the initial positions of Facilitator’s ...
  • On the role of multilinearity in the computation of polynomials 
    Narayanan, Rohit (Indian Institute of Technology Gandhinagar, 2024)

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