Zobrazeno 1 - 10
of 46 996
pro vyhledávání: '"HASHEM, A"'
Autor:
Francis, John, Esnaashari, Saba, Poletaev, Anton, Chakraborty, Sukankana, Hashem, Youmna, Bright, Jonathan
Large language models (LLMs) have demonstrated remarkable capabilities in text analysis tasks, yet their evaluation on complex, real-world applications remains challenging. We define a set of tasks, Multi-Insight Multi-Document Extraction (MIMDE) tas
Externí odkaz:
http://arxiv.org/abs/2411.19689
Haptic feedback increases the realism of virtual environments. This paper proposes a wearable haptic device that renders torque feedback to the user's wrist from any angle. The device comprises a control part and a handle part. The control part consi
Externí odkaz:
http://arxiv.org/abs/2411.05153
Our system introduces a modularized pneumatic actuating unit capable of delivering vibration, pressure, and impact feedback. Designed for adaptability, these modular tactile actuating units can be rapidly customized and reconfigured to suit a wide ra
Externí odkaz:
http://arxiv.org/abs/2411.05143
Multi-mode haptic feedback is essential to achieve high realism and immersion in virtual environments. This paper proposed a novel silicone fingertip actuator integrated with a hot thermal fabric finger sleeve to render pressure, vibration, and hot t
Externí odkaz:
http://arxiv.org/abs/2411.05129
We introduce a precision polarization scheme for DNN inference that utilizes only very low and very high precision levels, assigning low precision to the majority of network weights and activations while reserving high precision paths for targeted er
Externí odkaz:
http://arxiv.org/abs/2411.05845
While large multimodal models (LMMs) have obtained strong performance on many multimodal tasks, they may still hallucinate while generating text. Their performance on detecting salient features from visual data is also unclear. In this paper, we deve
Externí odkaz:
http://arxiv.org/abs/2409.03961
Autor:
Hashem, Maeesha Binte, Parpillon, Benjamin, Kumar, Divake, Jayasuria, Dinithi, Trivedi, Amit Ranjan
In this work, we propose "TimeFloats," an efficient train-in-memory architecture that performs 8-bit floating-point scalar product operations in the time domain. While building on the compute-in-memory paradigm's integrated storage and inferential co
Externí odkaz:
http://arxiv.org/abs/2409.00495
In recent years, the integration of deep learning techniques into medical imaging has revolutionized the diagnosis and treatment of lung diseases, particularly in the context of COVID-19 and pneumonia. This paper presents a novel, lightweight deep le
Externí odkaz:
http://arxiv.org/abs/2408.06459
Autor:
Hashem, Hassan N. Al, Abraham, Amanda N., Sharma, Deepak, Chambers, Andre, Moghaddar, Mehrnoosh, Reeves, Chayla L., Srivastava, Sanjay K., Gelmi, Amy, Ahnood, Arman
The ability to form diamond electrodes on insulating polycrystalline diamond substrates using single-step laser patterning, and the use of the electrodes as a substrate that supports the adhesion and proliferation of human mesenchymal stem cells (hMS
Externí odkaz:
http://arxiv.org/abs/2407.19582
Autor:
Utsha, Rittik Basak, Alif, Muhtasim Noor, Rayhan, Yeasir, Hashem, Tanzima, Ali, Mohammad Eunus
Crime prediction is a widely studied research problem due to its importance in ensuring safety of city dwellers. Starting from statistical and classical machine learning based crime prediction methods, in recent years researchers have focused on expl
Externí odkaz:
http://arxiv.org/abs/2407.19324