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pro vyhledávání: '"A. Sricharan"'
We study the problem of fair cake-cutting where each agent receives a connected piece of the cake. A division of the cake is deemed fair if it is equitable, which means that all agents derive the same value from their assigned piece. Prior work has e
Externí odkaz:
http://arxiv.org/abs/2412.13340
Molecular polaritons arise when the collective coupling between an ensemble of $N$ molecules and an optical mode exceeds individual photon and molecular linewidths. The complexity of their description stems from their multiscale nature, where the loc
Externí odkaz:
http://arxiv.org/abs/2410.14175
Businesses can benefit from customer feedback in different modalities, such as text and images, to enhance their products and services. However, it is difficult to extract actionable and relevant pairs of text segments and images from customer feedba
Externí odkaz:
http://arxiv.org/abs/2410.09999
Summarizing customer feedback to provide actionable insights for products/services at scale is an important problem for businesses across industries. Lately, the review volumes are increasing across regions and languages, therefore the challenge of a
Externí odkaz:
http://arxiv.org/abs/2410.09991
Large language models (LLMs) are proficient in capturing factual knowledge across various domains. However, refining their capabilities on previously seen knowledge or integrating new knowledge from external sources remains a significant challenge. I
Externí odkaz:
http://arxiv.org/abs/2410.09629
Autor:
Li, Zhuohang, Zhang, Jiaxin, Yan, Chao, Das, Kamalika, Kumar, Sricharan, Kantarcioglu, Murat, Malin, Bradley A.
Language models (LMs) are known to suffer from hallucinations and misinformation. Retrieval augmented generation (RAG) that retrieves verifiable information from an external knowledge corpus to complement the parametric knowledge in LMs provides a ta
Externí odkaz:
http://arxiv.org/abs/2410.08320
Privately counting distinct elements in a stream is a fundamental data analysis problem with many applications in machine learning. In the turnstile model, Jain et al. [NeurIPS2023] initiated the study of this problem parameterized by the maximum fli
Externí odkaz:
http://arxiv.org/abs/2408.11637
Autor:
Mukku, Sandeep Sricharan, Soni, Manan, Rana, Jitenkumar, Aggarwal, Chetan, Yenigalla, Promod, Patange, Rashmi, Mohan, Shyam
We propose InsightNet, a novel approach for the automated extraction of structured insights from customer reviews. Our end-to-end machine learning framework is designed to overcome the limitations of current solutions, including the absence of struct
Externí odkaz:
http://arxiv.org/abs/2405.07195
Computing the core decomposition of a graph is a fundamental problem that has recently been studied in the differentially private setting, motivated by practical applications in data mining. In particular, Dhulipala et al. [FOCS 2022] gave the first
Externí odkaz:
http://arxiv.org/abs/2402.18020
Uncertainty estimation is a crucial aspect of deploying dependable deep learning models in safety-critical systems. In this study, we introduce a novel and efficient method for deterministic uncertainty estimation called Discriminant Distance-Awarene
Externí odkaz:
http://arxiv.org/abs/2402.12664