標(biāo)題: Titlebook: Masters Theses in the Pure and Applied Sciences; Accepted by Colleges Wade H. Shafer Book 1986 Plenum Press, New York 1986 astronomy.calcul [打印本頁] 作者: sulfonylureas 時間: 2025-3-21 19:25
書目名稱Masters Theses in the Pure and Applied Sciences影響因子(影響力)
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書目名稱Masters Theses in the Pure and Applied Sciences被引頻次
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書目名稱Masters Theses in the Pure and Applied Sciences讀者反饋
書目名稱Masters Theses in the Pure and Applied Sciences讀者反饋學(xué)科排名
作者: Chagrin 時間: 2025-3-21 22:15 作者: 商談 時間: 2025-3-22 01:39 作者: opportune 時間: 2025-3-22 06:28
Wade H. Shaferl set. A majority of labels only have a few training instances due to large label dimensionality in XMTC. To solve this data sparsity issue, most existing XMTC methods take advantage of fixed label clusters obtained in early stage to balance performance on tail labels and head labels. However, such 作者: 縮減了 時間: 2025-3-22 10:35
Wade H. Shaferteractive performance requirement. A typical solution is to retrieve the answer by finding the optimal query graph, which is a sub-graph of the knowledge graph. However, existing methods usually generate a considerable number of sub-graph candidates, then fail to find the optimal one effectively, re作者: 議程 時間: 2025-3-22 13:02
Wade H. Shaferpted to utilize techniques in Hierarchical Multi-label Text Classification (HMTC) to classify scientific literature. Although there have been many advances, some problems still cannot be effectively solved in HMTC tasks, such as the difficulty in capturing the dependencies of hierarchical labels and作者: FIN 時間: 2025-3-22 17:59 作者: 意外的成功 時間: 2025-3-22 23:59 作者: 含鐵 時間: 2025-3-23 04:33
Wade H. Shaferiety of reasoning tasks. Still, due to the demand for low costs, research on the upper bound of small language models in reasoning tasks and the limitation of the knowledge they can accommodate has drawn attention. In line with previous work on math word problems, we discover that models that only l作者: 好開玩笑 時間: 2025-3-23 05:38
Wade H. Shaferng MWPs with two types of solvers: tree-based solver and large language model (LLM) solver. However, these approaches always solve MWPs by a single solver, which will bring the following problems: (1) Single type of solver is hard to solve all types of MWPs well. (2) A single solver will result in p作者: 欺騙手段 時間: 2025-3-23 13:44
Wade H. Shaferng MWPs with two types of solvers: tree-based solver and large language model (LLM) solver. However, these approaches always solve MWPs by a single solver, which will bring the following problems: (1) Single type of solver is hard to solve all types of MWPs well. (2) A single solver will result in p作者: 轉(zhuǎn)折點 時間: 2025-3-23 16:04
Wade H. Shafers of TCM relies heavily on doctors’ experience, which can affect the accuracy of diagnosis in practice. With the development of natural language processing technology, its mechanism can learn from a large amount of unstructured text to obtain a comprehensive and unified classification model. In this作者: 無脊椎 時間: 2025-3-23 19:49
Wade H. Shaferiety of reasoning tasks. Still, due to the demand for low costs, research on the upper bound of small language models in reasoning tasks and the limitation of the knowledge they can accommodate has drawn attention. In line with previous work on math word problems, we discover that models that only l作者: 得意人 時間: 2025-3-24 01:42 作者: Cursory 時間: 2025-3-24 03:13
Wade H. Shafer (D-CPT) structure is proposed to better represent the dependency relations in a CPT-style structure, which employs dependency relation types instead of phrase labels in CPT. In this way, D-CPT not only keeps the dependency relationship information in the dependency parse tree (DPT) structure but al作者: 感情脆弱 時間: 2025-3-24 08:47
Wade H. Shaferords and thus lead to the loss of some important semantics. In this paper, we propose a new method to exploit word structure and integrate lexical semantics into character representations of pre-trained models. Specifically, we project a word’s embedding into its internal characters’ embeddings acco作者: canvass 時間: 2025-3-24 14:19
Wade H. Shaferso very brittle and easily falter when fed with noisy sentences, i.e., from automatic speech recognition (ASR) output. Due to the lack of Chinese-to-English translation test set with natural Chinese-side ASR output, related studies artificially add noise into Chinese sentences to evaluation translat作者: 預(yù)知 時間: 2025-3-24 15:25 作者: 陳列 時間: 2025-3-24 19:30 作者: 任意 時間: 2025-3-25 00:08 作者: 小丑 時間: 2025-3-25 06:31 作者: gout109 時間: 2025-3-25 09:10 作者: 問到了燒瓶 時間: 2025-3-25 11:39 作者: ALIAS 時間: 2025-3-25 17:47 作者: trigger 時間: 2025-3-25 21:30
se text readability auto-evaluation, shows that word abstractness is an important feature in investigating cognitive differences and text complexity. The large-scale Chinese abstractness lexicon constructed in this paper has important application values.作者: profligate 時間: 2025-3-26 00:23 作者: 我怕被刺穿 時間: 2025-3-26 05:07 作者: 翻動 時間: 2025-3-26 09:42 作者: Stress 時間: 2025-3-26 13:24 作者: 男生戴手銬 時間: 2025-3-26 20:00
Wade H. Shafere of LLM is poor in experiments, they possess excellent logical abilities. With the training set becoming more diverse and the methods for training set data augmentation becoming more refined, the supervised fine-tuning (SFT) mode trained LLMs are expected to achieve significant improvements in CGEC作者: 推測 時間: 2025-3-26 22:18 作者: nautical 時間: 2025-3-27 04:10
Wade H. Shafer and LLM solver to improve their performance. For the tree-based solver, we propose an ensemble learning framework based on ten-fold cross-validation and voting mechanism. In the LLM solver, we adopt self-consistency (SC) method to improve answer selection. Experimental results demonstrate the effec作者: uncertain 時間: 2025-3-27 07:18
Wade H. Shafer and LLM solver to improve their performance. For the tree-based solver, we propose an ensemble learning framework based on ten-fold cross-validation and voting mechanism. In the LLM solver, we adopt self-consistency (SC) method to improve answer selection. Experimental results demonstrate the effec作者: malapropism 時間: 2025-3-27 13:08 作者: HARP 時間: 2025-3-27 16:09
Wade H. Shafertail about how consistent solutions training affects the work process of beam search. In addition, we found significant differences between models trained using consistent solutions and those trained without consistent solutions, so the model ensemble technique is applied to improve model performanc作者: Inoperable 時間: 2025-3-27 20:00
Wade H. Shaferstopwords removing of TCM cases, which improved 0.087 compared with no TCM stopwords removing. This paper introduces natural language processing into the TCM auxiliary diagnosis problem, in order to improve the informationization, standardization and intelligence of TCM in the new era.作者: RODE 時間: 2025-3-28 01:52
Wade H. Shafere-of-art feature-based ones. This indicates the effectiveness of the novel D-CPT structure for better representation of dependency relations in tree kernel-based methods. To our knowledge, this is the first research of tree kernel-based SRL on effectively exploring dependency relationship informatio作者: 死亡 時間: 2025-3-28 05:12
