Zobrazeno 1 - 10
of 32 912
pro vyhledávání: '"A, Chaudhari"'
Large language models (LLMs) are susceptible to memorizing training data, raising concerns due to the potential extraction of sensitive information. Current methods to measure memorization rates of LLMs, primarily discoverable extraction (Carlini et
Externí odkaz:
http://arxiv.org/abs/2410.19482
Autor:
Yang, Ke, Liu, Yao, Chaudhary, Sapana, Fakoor, Rasool, Chaudhari, Pratik, Karypis, George, Rangwala, Huzefa
Autonomy via agents using large language models (LLMs) for personalized, standardized tasks boosts human efficiency. Automating web tasks (like booking hotels within a budget) is increasingly sought after. Fulfilling practical needs, the web agent al
Externí odkaz:
http://arxiv.org/abs/2410.13825
Autor:
He, Shizhe, Paschali, Magdalini, Ouyang, Jiahong, Masood, Adnan, Chaudhari, Akshay, Adeli, Ehsan
Publikováno v:
International Workshop on Machine Learning in Clinical Neuroimaging (MLCN) 2024
Representation learning has become increasingly important, especially as powerful models have shifted towards learning latent representations before fine-tuning for downstream tasks. This approach is particularly valuable in leveraging the structural
Externí odkaz:
http://arxiv.org/abs/2410.12053
Robustness towards adversarial attacks is a vital property for classifiers in several applications such as autonomous driving, medical diagnosis, etc. Also, in such scenarios, where the cost of misclassification is very high, knowing when to abstain
Externí odkaz:
http://arxiv.org/abs/2410.10736
Autor:
R, Renjith Kumar, Geethika, B R, Verma, Nancy, Chaudhari, Vishnu, Dave, Janvi, Joshi, Hem Chandra, Thomas, Jinto
In this work, we report an innovative pump-probe based experimental set up, to study the melting, subsequent evaporation, plasma formation and redeposition in a thin film coated on a glass substrate under different ambient conditions and laser fluenc
Externí odkaz:
http://arxiv.org/abs/2410.07755
Autor:
Hein, Dennis, Chen, Zhihong, Ostmeier, Sophie, Xu, Justin, Varma, Maya, Reis, Eduardo Pontes, Michalson, Arne Edward, Bluethgen, Christian, Shin, Hyun Joo, Langlotz, Curtis, Chaudhari, Akshay S
Radiologists play a crucial role by translating medical images into medical reports. However, the field faces staffing shortages and increasing workloads. While automated approaches using vision-language models (VLMs) show promise as assistants, they
Externí odkaz:
http://arxiv.org/abs/2410.07025
Autor:
Gandhi, Kashish, Kulkarni, Prutha, Shah, Taran, Chaudhari, Piyush, Narvekar, Meera, Ghag, Kranti
The rapid advancement of deepfake technology poses a significant threat to digital media integrity. Deepfakes, synthetic media created using AI, can convincingly alter videos and audio to misrepresent reality. This creates risks of misinformation, fr
Externí odkaz:
http://arxiv.org/abs/2410.03487
Autor:
Chaudhari, Prasad, Kumar, Aman, Raghaw, Chandravardhan Singh, Rehman, Mohammad Zia Ur, Kumar, Nagendra
Sentiment analysis and emotion recognition in videos are challenging tasks, given the diversity and complexity of the information conveyed in different modalities. Developing a highly competent framework that effectively addresses the distinct charac
Externí odkaz:
http://arxiv.org/abs/2410.12828
Evaluating policies using off-policy data is crucial for applying reinforcement learning to real-world problems such as healthcare and autonomous driving. Previous methods for off-policy evaluation (OPE) generally suffer from high variance or irreduc
Externí odkaz:
http://arxiv.org/abs/2410.02172
Autor:
Paschali, Magdalini, Jiang, Yu Hang, Siegel, Spencer, Gonzalez, Camila, Pohl, Kilian M., Chaudhari, Akshay, Zhao, Qingyu
Recent advancements in medicine have confirmed that brain disorders often comprise multiple subtypes of mechanisms, developmental trajectories, or severity levels. Such heterogeneity is often associated with demographic aspects (e.g., sex) or disease
Externí odkaz:
http://arxiv.org/abs/2410.00946