Delve into the cutting edge of Artificial Intelligence with our dedicated Research Paper section.
Data-driven Automated Negative Control Estimation (DANCE): Search for, Validation of, and Causal Inference with Negative Controls Erich Kummerfeld, Jaewon Lim, Xu Shi; 25(229):1−35, 2024. Abstract Negative control variables are increasingly used to adjust for unmeasured confounding bias in causal inference…
arXiv:2408.08921v1 Announce Type: new Abstract: Recently, Retrieval-Augmented Generation (RAG) has achieved remarkable success in addressing the challenges of Large Language Models (LLMs) without necessitating retraining. By referencing an external knowledge base, RAG refines LLM outputs, effectively mitigating issues such as…
[Submitted on 5 Aug 2024] View a PDF of the paper titled A Classifier-Based Approach to Multi-Class Anomaly Detection Applied to Astronomical Time-Series, by Rithwik Gupta and 1 other authors View PDF HTML (experimental) Abstract:Automating anomaly detection is an open…
[Submitted on 2 Aug 2024] View a PDF of the paper titled SHARP-Net: A Refined Pyramid Network for Deficiency Segmentation in Culverts and Sewer Pipes, by Rasha Alshawi and 6 other authors View PDF HTML (experimental) Abstract:This paper introduces Semantic…
arXiv:2408.08964v1 Announce Type: new Abstract: The widespread availability of code-mixed data can provide valuable insights into low-resource languages like Bengali, which have limited datasets. Sentiment analysis has been a fundamental text classification task across several languages for code-mixed data. However,…
arXiv:2408.08998v1 Announce Type: new Abstract: Recent advances in machine learning have significantly improved prediction accuracy in various applications. However, ensuring the calibration of probabilistic predictions remains a significant challenge. Despite efforts to enhance model calibration, the rigorous statistical evaluation of…
Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds Zhenghao Xu, Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao; 25(226):1−67, 2024. Abstract Policy gradient methods equipped with deep neural networks have achieved great success in solving…
arXiv:2408.08916v1 Announce Type: new Abstract: Dung’s Abstract Argumentation Framework (AF) has emerged as a key formalism for argumentation in Artificial Intelligence. It has been extended in several directions, including the possibility to express supports, leading to the development of the…
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arXiv:2408.08332v1 Announce Type: new Abstract: We address the challenges of precise image inversion and disentangled image editing in the context of few-step diffusion models. We introduce an encoder based iterative inversion technique. The inversion network is conditioned on the input…
arXiv:2408.08374v1 Announce Type: new Abstract: As machine learning systems become more widely used, especially for safety critical applications, there is a growing need to ensure that these systems behave as intended, even in the face of adversarial examples. Adversarial examples…
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy.…