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pro vyhledávání: '"Chen, Howard"'
Large language models can absorb a massive amount of knowledge through pretraining, but pretraining is inefficient for acquiring long-tailed or specialized facts. Therefore, fine-tuning on specialized or new knowledge that reflects changes in the wor
Externí odkaz:
http://arxiv.org/abs/2411.07175
Autor:
Wang, Zirui, Xia, Mengzhou, He, Luxi, Chen, Howard, Liu, Yitao, Zhu, Richard, Liang, Kaiqu, Wu, Xindi, Liu, Haotian, Malladi, Sadhika, Chevalier, Alexis, Arora, Sanjeev, Chen, Danqi
Chart understanding plays a pivotal role when applying Multimodal Large Language Models (MLLMs) to real-world tasks such as analyzing scientific papers or financial reports. However, existing datasets often focus on oversimplified and homogeneous cha
Externí odkaz:
http://arxiv.org/abs/2406.18521
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
Large language models (LLMs) have advanced in large strides due to the effectiveness of the self-attention mechanism that processes and compares all tokens at once. However, this mechanism comes with a fundamental issue -- the predetermined context w
Externí odkaz:
http://arxiv.org/abs/2310.05029
Autor:
Gu, Pin-Gao, Chen, Howard
We investigate the evolution of the deuterium-to-hydrogen (D/H) mass ratio driven by EUV photoevaporation of hydrogen-rich atmospheres of close-in sub-Neptunes around solar-type stars. For the first time, the diffusion-limited approach in conjunction
Externí odkaz:
http://arxiv.org/abs/2308.05057
Text generation under constraints have seen increasing interests in natural language processing, especially with the rapidly improving capabilities of large language models. However, existing benchmarks for constrained generation usually focus on fix
Externí odkaz:
http://arxiv.org/abs/2307.08689
Autor:
Deshpande, Ameet, Jimenez, Carlos E., Chen, Howard, Murahari, Vishvak, Graf, Victoria, Rajpurohit, Tanmay, Kalyan, Ashwin, Chen, Danqi, Narasimhan, Karthik
Semantic textual similarity (STS), a cornerstone task in NLP, measures the degree of similarity between a pair of sentences, and has broad application in fields such as information retrieval and natural language understanding. However, sentence simil
Externí odkaz:
http://arxiv.org/abs/2305.15093
Large language models (LLMs) exploit in-context learning (ICL) to solve tasks with only a few demonstrations, but its mechanisms are not yet well-understood. Some works suggest that LLMs only recall already learned concepts from pre-training, while o
Externí odkaz:
http://arxiv.org/abs/2305.09731
Climate modeling has shown that tidally influenced terrestrial exoplanets, particularly those orbiting M-dwarfs, have unique atmospheric dynamics and surface conditions that may enhance their likelihood to host viable habitats. However, sporadic libr
Externí odkaz:
http://arxiv.org/abs/2302.11561