Zobrazeno 1 - 10
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pro vyhledávání: '"Murali Krishna, P."'
Autor:
Xie, Zhaoyang, Li, Chi, Murali, Krishna, Yu, Haoyi, Liu, Changxu, Lu, Yiqing, Maier, Stefan A., Bhaskaran, Madhu, Ren, Haoran
Phase-change materials (PCMs) are increasingly recognised as promising platforms for tunable photonic devices due to their ability to modulate optical properties through solid-state phase transitions. Ultrathin and low-loss PCMs are highly valued for
Externí odkaz:
http://arxiv.org/abs/2410.02413
In this study, we address the issue of API hallucinations in various software engineering contexts. We introduce CloudAPIBench, a new benchmark designed to measure API hallucination occurrences. CloudAPIBench also provides annotations for frequencies
Externí odkaz:
http://arxiv.org/abs/2407.09726
Autor:
Zhang, Yuhao, Wang, Shiqi, Qian, Haifeng, Wang, Zijian, Shang, Mingyue, Liu, Linbo, Gouda, Sanjay Krishna, Ray, Baishakhi, Ramanathan, Murali Krishna, Ma, Xiaofei, Deoras, Anoop
Code generation models are not robust to small perturbations, which often lead to incorrect generations and significantly degrade the performance of these models. Although improving the robustness of code generation models is crucial to enhancing use
Externí odkaz:
http://arxiv.org/abs/2405.01567
Recent advances in retrieval-augmented generation (RAG) have initiated a new era in repository-level code completion. However, the invariable use of retrieval in existing methods exposes issues in both efficiency and robustness, with a large proporti
Externí odkaz:
http://arxiv.org/abs/2403.10059
Autor:
Ryan, Gabriel, Jain, Siddhartha, Shang, Mingyue, Wang, Shiqi, Ma, Xiaofei, Ramanathan, Murali Krishna, Ray, Baishakhi
Testing plays a pivotal role in ensuring software quality, yet conventional Search Based Software Testing (SBST) methods often struggle with complex software units, achieving suboptimal test coverage. Recent works using large language models (LLMs) f
Externí odkaz:
http://arxiv.org/abs/2402.00097
Autor:
Ding, Yangruibo, Wang, Zijian, Ahmad, Wasi Uddin, Ding, Hantian, Tan, Ming, Jain, Nihal, Ramanathan, Murali Krishna, Nallapati, Ramesh, Bhatia, Parminder, Roth, Dan, Xiang, Bing
Code completion models have made significant progress in recent years, yet current popular evaluation datasets, such as HumanEval and MBPP, predominantly focus on code completion tasks within a single file. This over-simplified setting falls short of
Externí odkaz:
http://arxiv.org/abs/2310.11248
Autor:
Jayesh Amin, Naga Sandhya Alle, Ami Patel, Bansi Prajapathi, Paresh Makwana, Jaya Prakash, Kota Murali Krishna
Publikováno v:
International Journal of Reproductive BioMedicine, Vol 22, Iss 7, Pp 539-552 (2024)
Abstract Background: Follicle-stimulating hormone receptor (FSHR) and luteinizing hormone/choriogonadotropin receptor (LHCGR) are integral to ovarian function, facilitating follicle development and maturation through their respective hormonal interac
Externí odkaz:
https://doaj.org/article/3904372f12074d62a63bb722ccf608e3
Scattering dynamics influence the graphenes transport properties and inhibits the charge carrier deterministic behaviour. The intra or inter-band scattering mechanisms are vital for graphenes optical conductivity response under specific consideration
Externí odkaz:
http://arxiv.org/abs/2307.15945
Autor:
Yadav, Prateek, Sun, Qing, Ding, Hantian, Li, Xiaopeng, Zhang, Dejiao, Tan, Ming, Ma, Xiaofei, Bhatia, Parminder, Nallapati, Ramesh, Ramanathan, Murali Krishna, Bansal, Mohit, Xiang, Bing
Large-scale code generation models such as Codex and CodeT5 have achieved impressive performance. However, libraries are upgraded or deprecated very frequently and re-training large-scale language models is computationally expensive. Therefore, Conti
Externí odkaz:
http://arxiv.org/abs/2307.02435
Autor:
Ding, Hantian, Kumar, Varun, Tian, Yuchen, Wang, Zijian, Kwiatkowski, Rob, Li, Xiaopeng, Ramanathan, Murali Krishna, Ray, Baishakhi, Bhatia, Parminder, Sengupta, Sudipta, Roth, Dan, Xiang, Bing
Large language models trained on code have shown great potential to increase productivity of software developers. Several execution-based benchmarks have been proposed to evaluate functional correctness of model-generated code on simple programming p
Externí odkaz:
http://arxiv.org/abs/2306.03203