Zobrazeno 1 - 10
of 1 613
pro vyhledávání: '"Kannappan, P."'
Autor:
Lebouteiller, V., Richardson, C. T., Polimera, M. S., Carr, D. S., Hutchens, Z. L., Kannappan, S. J., Ramambason, L., Moffett, A. J., Varese, M., Madden, S. C.
Deriving physical parameters from integrated galaxy spectra is paramount to interpret the cosmic evolution of star formation, chemical enrichment, and energetic sources. We develop modeling techniques to characterize the ionized gas properties in the
Externí odkaz:
http://arxiv.org/abs/2412.15860
Autor:
Deshpande, Darshan, Ravi, Selvan Sunitha, CH-Wang, Sky, Mielczarek, Bartosz, Kannappan, Anand, Qian, Rebecca
The LLM-as-judge paradigm is increasingly being adopted for automated evaluation of model outputs. While LLM judges have shown promise on constrained evaluation tasks, closed source LLMs display critical shortcomings when deployed in real world appli
Externí odkaz:
http://arxiv.org/abs/2412.14140
Retrieval Augmented Generation (RAG) techniques aim to mitigate hallucinations in Large Language Models (LLMs). However, LLMs can still produce information that is unsupported or contradictory to the retrieved contexts. We introduce LYNX, a SOTA hall
Externí odkaz:
http://arxiv.org/abs/2407.08488
Autor:
Carr, Derrick S., Kannappan, Sheila J., Norris, Mark A., Sinha, Manodeep, Palumbo III, Michael L., Eckert, Kathleen D., Moffett, Amanda J., Polimera, Mugdha S., Bernstein, Joel I., Hutchens, Zackary L.
We present a complete census of candidate nuggets, i.e., dense galaxies likely formed by compaction with intense gas influx, within the volume-limited $z \sim 0$ REsolved Spectroscopy Of a Local VolumE (RESOLVE) survey. These nuggets span all evoluti
Externí odkaz:
http://arxiv.org/abs/2406.04547
Autor:
Surya, Ramakrishna, Koerner, Gordon L., Hajilounezhad, Taher, Safavigerdin, Kaveh, Calyam, Prasad, Bunyak, Filiz, Palaniappan, Kannappan, Maschmann, Matthew R.
Understanding the dynamic self-assembly mechanisms of carbon nanotube (CNT) forests is necessary to advance their technological promise. Here, in-situ environmental scanning electron microscope (ESEM) chemical vapor deposition (CVD) synthesis observe
Externí odkaz:
http://arxiv.org/abs/2402.19336
FinanceBench is a first-of-its-kind test suite for evaluating the performance of LLMs on open book financial question answering (QA). It comprises 10,231 questions about publicly traded companies, with corresponding answers and evidence strings. The
Externí odkaz:
http://arxiv.org/abs/2311.11944
Autor:
Vidgen, Bertie, Scherrer, Nino, Kirk, Hannah Rose, Qian, Rebecca, Kannappan, Anand, Hale, Scott A., Röttger, Paul
The past year has seen rapid acceleration in the development of large language models (LLMs). However, without proper steering and safeguards, LLMs will readily follow malicious instructions, provide unsafe advice, and generate toxic content. We intr
Externí odkaz:
http://arxiv.org/abs/2311.08370
Autor:
Safavigerdini, Kaveh, Nouduri, Koundinya, Surya, Ramakrishna, Reinhard, Andrew, Quinlan, Zach, Bunyak, Filiz, Maschmann, Matthew R., Palaniappan, Kannappan
We present a pipeline for predicting mechanical properties of vertically-oriented carbon nanotube (CNT) forest images using a deep learning model for artificial intelligence (AI)-based materials discovery. Our approach incorporates an innovative data
Externí odkaz:
http://arxiv.org/abs/2307.07912
Autor:
Soltanikazemi, Elham, Dhakal, Ashwin, Hatuwal, Bijaya Kumar, Toubal, Imad Eddine, Aboah, Armstrong, Palaniappan, Kannappan
Publikováno v:
2023 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)
This research focuses on real-time surveillance systems as a means for tackling the issue of non-compliance with helmet regulations, a practice that considerably amplifies the risk for motorcycle drivers or riders. Despite the well-established advant
Externí odkaz:
http://arxiv.org/abs/2304.09248
Autor:
Shiyao Yuan, Asma Rahim, Suvetha Kannappan, Amol Dongre, Animesh Jain, Sitanshu Sekhar Kar, Snigdha Mukherjee, Rashmi Vyas
Publikováno v:
BMC Medical Education, Vol 24, Iss 1, Pp 1-10 (2024)
Abstract Background Faculty development programs (FDPs) in health professions education (HPE) are instrumental in supporting, promoting, and improving HPE curricula and activities that target individual- and system-level capacity strengthening. FAIME
Externí odkaz:
https://doaj.org/article/f6f7012768c44162805bf8c86aa50889
