Zobrazeno 1 - 10
of 2 201
pro vyhledávání: '"Shah, Chirag A."'
Autor:
Verma, Sahil, Rassin, Royi, Das, Arnav, Bhatt, Gantavya, Seshadri, Preethi, Shah, Chirag, Bilmes, Jeff, Hajishirzi, Hannaneh, Elazar, Yanai
Text-to-image models are trained using large datasets collected by scraping image-text pairs from the internet. These datasets often include private, copyrighted, and licensed material. Training models on such datasets enables them to generate images
Externí odkaz:
http://arxiv.org/abs/2410.15002
Publikováno v:
AIES '24: Proceedings of the Seventh AAAI/ACM Conference on AI, Ethics, and Society (AIES-24), Pages 1343-1356, 2024
Trust is not just a cognitive issue but also an emotional one, yet the research in human-AI interactions has primarily focused on the cognitive route of trust development. Recent work has highlighted the importance of studying affective trust towards
Externí odkaz:
http://arxiv.org/abs/2408.05354
Large Language Models (LLMs) attempt to imitate human behavior by responding to humans in a way that pleases them, including by adhering to their values. However, humans come from diverse cultures with different values. It is critical to understand w
Externí odkaz:
http://arxiv.org/abs/2406.14805
Theory of Mind (ToM) reasoning entails recognizing that other individuals possess their own intentions, emotions, and thoughts, which is vital for guiding one's own thought processes. Although large language models (LLMs) excel in tasks such as summa
Externí odkaz:
http://arxiv.org/abs/2406.05659
Autor:
Shah, Chirag, White, Ryen W.
The emergence of generative artificial intelligence (GenAI) is transforming information interaction. For decades, search engines such as Google and Bing have been the primary means of locating relevant information for the general population. They hav
Externí odkaz:
http://arxiv.org/abs/2405.12923
Autor:
Kaur, Kirandeep, Shah, Chirag
Conventional recommendation systems (RSs) are typically optimized to enhance performance metrics uniformly across all training samples. This makes it hard for data-driven RSs to cater to a diverse set of users due to the varying properties of these u
Externí odkaz:
http://arxiv.org/abs/2405.00824
Autor:
Suri, Siddharth, Counts, Scott, Wang, Leijie, Chen, Chacha, Wan, Mengting, Safavi, Tara, Neville, Jennifer, Shah, Chirag, White, Ryen W., Andersen, Reid, Buscher, Georg, Manivannan, Sathish, Rangan, Nagu, Yang, Longqi
Until recently, search engines were the predominant method for people to access online information. The recent emergence of large language models (LLMs) has given machines new capabilities such as the ability to generate new digital artifacts like te
Externí odkaz:
http://arxiv.org/abs/2404.04268
Autor:
Wan, Mengting, Safavi, Tara, Jauhar, Sujay Kumar, Kim, Yujin, Counts, Scott, Neville, Jennifer, Suri, Siddharth, Shah, Chirag, White, Ryen W, Yang, Longqi, Andersen, Reid, Buscher, Georg, Joshi, Dhruv, Rangan, Nagu
Transforming unstructured text into structured and meaningful forms, organized by useful category labels, is a fundamental step in text mining for downstream analysis and application. However, most existing methods for producing label taxonomies and
Externí odkaz:
http://arxiv.org/abs/2403.12173
Autor:
Dammu, Preetam Prabhu Srikar, Naidu, Himanshu, Dewan, Mouly, Kim, YoungMin, Roosta, Tanya, Chadha, Aman, Shah, Chirag
In the midst of widespread misinformation and disinformation through social media and the proliferation of AI-generated texts, it has become increasingly difficult for people to validate and trust information they encounter. Many fact-checking approa
Externí odkaz:
http://arxiv.org/abs/2403.09724
Autor:
Amirizaniani, Maryam, Yao, Jihan, Lavergne, Adrian, Okada, Elizabeth Snell, Chadha, Aman, Roosta, Tanya, Shah, Chirag
As Large Language Models (LLMs) become more pervasive across various users and scenarios, identifying potential issues when using these models becomes essential. Examples of such issues include: bias, inconsistencies, and hallucination. Although audi
Externí odkaz:
http://arxiv.org/abs/2402.09346