Zobrazeno 1 - 10
of 8 269
pro vyhledávání: '"Tsuruoka A"'
Transferring learned skills across diverse situations remains a fundamental challenge for autonomous agents, particularly when agents are not allowed to interact with an exact target setup. While prior approaches have predominantly focused on learnin
Externí odkaz:
http://arxiv.org/abs/2407.16912
Current representations used in reasoning steps of large language models can mostly be categorized into two main types: (1) natural language, which is difficult to verify; and (2) non-natural language, usually programming code, which is difficult for
Externí odkaz:
http://arxiv.org/abs/2406.17873
Which Experiences Are Influential for RL Agents? Efficiently Estimating The Influence of Experiences
In reinforcement learning (RL) with experience replay, experiences stored in a replay buffer influence the RL agent's performance. Information about how these experiences influence the agent's performance is valuable for various purposes, such as ide
Externí odkaz:
http://arxiv.org/abs/2405.14629
The problem of hallucination and omission, a long-standing problem in machine translation (MT), is more pronounced when a large language model (LLM) is used in MT because an LLM itself is susceptible to these phenomena. In this work, we mitigate the
Externí odkaz:
http://arxiv.org/abs/2405.09223
The field of cross-lingual sentence embeddings has recently experienced significant advancements, but research concerning low-resource languages has lagged due to the scarcity of parallel corpora. This paper shows that cross-lingual word representati
Externí odkaz:
http://arxiv.org/abs/2404.02490
Learning multi-lingual sentence embeddings is a fundamental task in natural language processing. Recent trends in learning both mono-lingual and multi-lingual sentence embeddings are mainly based on contrastive learning (CL) among an anchor, one posi
Externí odkaz:
http://arxiv.org/abs/2309.08929
Autor:
Yusuke Shinozaki, Kei Morikawa, Kida Hirotaka, Kazuhiro Nishiyama, Satoshi Tanaka, Hajime Tsuruoka, Shin Matsuzawa, Hiroshi Handa, Hiroki Nishine, Masamichi Mineshita
Publikováno v:
Respiratory Research, Vol 25, Iss 1, Pp 1-11 (2024)
Abstract Background and Aims Because bronchoscopy is an invasive procedure, sedatives and analgesics are commonly administered, which may suppress the patient’s spontaneous breathing and can lead to hypoventilation and hypoxemia. Few reports exist
Externí odkaz:
https://doaj.org/article/379d6bbc9c1c420ba50f16b3f2d15340
Autor:
Kazuhiro Nishiyama, Kei Morikawa, Shotaro Kaneko, Makoto Nishida, Aya Matsushima, Yoshihiro Nishi, Yu Numata, Yusuke Shinozaki, Hajime Tsuruoka, Hirotaka Kida, Hiroshi Handa, Naoki Shimada, Chie Okawa, Nobuyuki Ohike, Junki Koike, Masamichi Mineshita
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-7 (2024)
Abstract Previous studies have shown that rapid on-site evaluation (ROSE) improves the diagnostic yield of bronchoscopy using endobronchial ultrasound with a guide sheath (EBUS-GS) for peripheral pulmonary lesions (PPL). While ROSE of imprint cytolog
Externí odkaz:
https://doaj.org/article/5ef9da1dee864fa5bb0cd417ce1e1dd9
Most existing word alignment methods rely on manual alignment datasets or parallel corpora, which limits their usefulness. Here, to mitigate the dependence on manual data, we broaden the source of supervision by relaxing the requirement for correct,
Externí odkaz:
http://arxiv.org/abs/2306.05644
Recently, methods for learning diverse skills to generate various behaviors without external rewards have been actively studied as a form of unsupervised reinforcement learning. However, most of the existing methods learn a finite number of discrete
Externí odkaz:
http://arxiv.org/abs/2305.14377