Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Prabhakar, Akshara"'
Autor:
Zhang, Jianguo, Lan, Tian, Zhu, Ming, Liu, Zuxin, Hoang, Thai, Kokane, Shirley, Yao, Weiran, Tan, Juntao, Prabhakar, Akshara, Chen, Haolin, Liu, Zhiwei, Feng, Yihao, Awalgaonkar, Tulika, Murthy, Rithesh, Hu, Eric, Chen, Zeyuan, Xu, Ran, Niebles, Juan Carlos, Heinecke, Shelby, Wang, Huan, Savarese, Silvio, Xiong, Caiming
Autonomous agents powered by large language models (LLMs) have attracted significant research interest. However, the open-source community faces many challenges in developing specialized models for agent tasks, driven by the scarcity of high-quality
Externí odkaz:
http://arxiv.org/abs/2409.03215
Chain-of-Thought (CoT) prompting has been shown to enhance the multi-step reasoning capabilities of Large Language Models (LLMs). However, debates persist about whether LLMs exhibit abstract generalization or rely on shallow heuristics when given CoT
Externí odkaz:
http://arxiv.org/abs/2407.01687
Autor:
Chevalier, Alexis, Geng, Jiayi, Wettig, Alexander, Chen, Howard, Mizera, Sebastian, Annala, Toni, Aragon, Max Jameson, Fanlo, Arturo Rodríguez, Frieder, Simon, Machado, Simon, Prabhakar, Akshara, Thieu, Ellie, Wang, Jiachen T., Wang, Zirui, Wu, Xindi, Xia, Mengzhou, Xia, Wenhan, Yu, Jiatong, Zhu, Jun-Jie, Ren, Zhiyong Jason, Arora, Sanjeev, Chen, Danqi
NLP has recently made exciting progress toward training language models (LMs) with strong scientific problem-solving skills. However, model development has not focused on real-life use-cases of LMs for science, including applications in education tha
Externí odkaz:
http://arxiv.org/abs/2402.11111
Humans write code in a fundamentally interactive manner and rely on constant execution feedback to correct errors, resolve ambiguities, and decompose tasks. While LLMs have recently exhibited promising coding capabilities, current coding benchmarks m
Externí odkaz:
http://arxiv.org/abs/2306.14898
Grounding dialogue on external knowledge and interpreting linguistic patterns in dialogue history context, such as ellipsis, anaphora, and co-references is critical for dialogue comprehension and generation. In this paper, we present a novel open-dom
Externí odkaz:
http://arxiv.org/abs/2205.13928
Developing Named Entity Recognition (NER) systems for Indian languages has been a long-standing challenge, mainly owing to the requirement of a large amount of annotated clean training instances. This paper proposes an end-to-end framework for NER fo
Externí odkaz:
http://arxiv.org/abs/2111.11815