Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Agarwal, Sahaj"'
Autor:
Mitra, Arindam, Del Corro, Luciano, Mahajan, Shweti, Codas, Andres, Simoes, Clarisse, Agarwal, Sahaj, Chen, Xuxi, Razdaibiedina, Anastasia, Jones, Erik, Aggarwal, Kriti, Palangi, Hamid, Zheng, Guoqing, Rosset, Corby, Khanpour, Hamed, Awadallah, Ahmed
Orca 1 learns from rich signals, such as explanation traces, allowing it to outperform conventional instruction-tuned models on benchmarks like BigBench Hard and AGIEval. In Orca 2, we continue exploring how improved training signals can enhance smal
Externí odkaz:
http://arxiv.org/abs/2311.11045
Autor:
Del Corro, Luciano, Del Giorno, Allie, Agarwal, Sahaj, Yu, Bin, Awadallah, Ahmed, Mukherjee, Subhabrata
Autoregressive large language models (LLMs) have made remarkable progress in various natural language generation tasks. However, they incur high computation cost and latency resulting from the autoregressive token-by-token generation. To address this
Externí odkaz:
http://arxiv.org/abs/2307.02628
Autor:
Mukherjee, Subhabrata, Mitra, Arindam, Jawahar, Ganesh, Agarwal, Sahaj, Palangi, Hamid, Awadallah, Ahmed
Recent research has focused on enhancing the capability of smaller models through imitation learning, drawing on the outputs generated by large foundation models (LFMs). A number of issues impact the quality of these models, ranging from limited imit
Externí odkaz:
http://arxiv.org/abs/2306.02707
Autor:
Wang, Yaqing, Agarwal, Sahaj, Mukherjee, Subhabrata, Liu, Xiaodong, Gao, Jing, Awadallah, Ahmed Hassan, Gao, Jianfeng
Standard fine-tuning of large pre-trained language models (PLMs) for downstream tasks requires updating hundreds of millions to billions of parameters, and storing a large copy of the PLM weights for every task resulting in increased cost for storing
Externí odkaz:
http://arxiv.org/abs/2210.17451
Autor:
Madarkar, Rajeshkumar1 rajesh.srknec@gmail.com, Agarwal, Sahaj1, Attar, Pirsab1, Ghosh, S.1, Rao, P. V.1
Publikováno v:
Materials & Manufacturing Processes. 2018, Vol. 33 Issue 13, p1445-1452. 8p.
Publikováno v:
International Journal of Precision Technology; 2019, Vol. 8 Issue: 2-4 p142-157, 16p