检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

57,254 篇 会议
184 册 图书

馆藏范围

57,431 篇 电子文献
7 种 纸本馆藏

日期分布

学科分类号

57,035 篇 工学
- 56,756 篇 计算机科学与技术...
- 7,563 篇 控制科学与工程
- 2,548 篇 软件工程
- 2,065 篇 电气工程
- 514 篇 信息与通信工程
- 373 篇 生物医学工程（可授...
- 69 篇 机械工程
- 60 篇 土木工程
- 47 篇 生物工程
- 23 篇 石油与天然气工程
- 16 篇 仪器科学与技术
4,529 篇 理学
- 3,741 篇 数学
- 378 篇 物理学
- 305 篇 生物学
- 67 篇 统计学（可授理学、...
- 53 篇 科学技术史(分学科...
- 28 篇 系统科学
- 26 篇 化学
2,201 篇 医学
- 1,244 篇 基础医学(可授医学...
- 1,075 篇 临床医学
- 36 篇 特种医学
2,181 篇 文学
- 2,178 篇 外国语言文学
1,390 篇 管理学
- 1,266 篇 管理科学与工程(可...
- 111 篇 图书情报与档案管...
1,235 篇 教育学
- 713 篇 教育学
- 507 篇 心理学(可授教育学...
- 15 篇 体育学
63 篇 法学
- 62 篇 社会学
36 篇 艺术学
- 36 篇 音乐与舞蹈学
35 篇 哲学
- 35 篇 哲学
14 篇 经济学
1 篇 农学
1 篇 军事学

主题

1,255 篇 artificial intel...
1,104 篇 machine learning
972 篇 deep learning
919 篇 data mining
781 篇 multi agent syst...
726 篇 semantics
526 篇 classification
510 篇 reinforcement le...
475 篇 learning systems
462 篇 clustering
434 篇 neural networks
413 篇 ontology
342 篇 natural language...
257 篇 computers
249 篇 rough sets
236 篇 fuzzy sets
230 篇 feature selectio...
219 篇 computer circuit...
213 篇 knowledge repres...
205 篇 logic programmin...

机构

191 篇 univ chinese aca...
107 篇 chinese acad sci...
65 篇 harbin inst tech...
63 篇 polish acad sci ...
62 篇 wroclaw univ sci...
59 篇 soochow univ sch...
55 篇 delft univ techn...
53 篇 carnegie mellon ...
48 篇 beijing univ tec...
44 篇 chinese acad sci...
44 篇 shanghai jiao to...
43 篇 tu wien austria
42 篇 univ sci & techn...
41 篇 czech tech univ ...
40 篇 univ ulsan sch e...
39 篇 beijing jiaotong...
38 篇 tsinghua univ de...
38 篇 north carolina s...
37 篇 nanjing univ sta...
36 篇 tsinghua univ sc...

作者

47 篇 gelbukh alexande...
42 篇 wang lei
36 篇 reis luis paulo
35 篇 pelachaud cather...
35 篇 malerba donato
34 篇 liu yang
33 篇 novais paulo
33 篇 cpalka krzysztof
32 篇 li li
30 篇 ricci alessandro
27 篇 lau nuno
26 篇 wang hui
26 篇 napoli amedeo
25 篇 boryczka urszula
25 篇 rutkowski leszek
25 篇 wang jing
25 篇 pluhacek michal
25 篇 bickmore timothy
25 篇 calvo hiram
24 篇 wu bin

语言

57,321 篇 英文
116 篇 中文
1 篇 丹麦文

检索条件"丛书名=Lecture notes in artificial intelligence,"

共 57438 条记录，以下是221-230 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Mixed Multimodal Contrastive Learning for Enhancing Detection and Correction of Faked and Misspelled Chinese Characters 13th

Mixed Multimodal Contrastive Learning for Enhancing Detectio...

引用

13th International Conference on Natural Language Processing and Chinese Computing

作者： He, Rui Wang, Zhongqing Wang, Hongling Soochow Univ Nat Language Proc Lab Suzhou Peoples R China

ISBN: (纸本)9789819794423;9789819794430

Visual Chinese Character Checking (C3) aims to detect and correct errors in handwritten Chinese text images, including faked characters and misspelled characters. This task is beneficial for subsequent tasks by improving the efficiency of identifying errors in handwritten text. Recent methods are mainly based on Optical Character Recognition (OCR) and Pre-trained Language Models (PLMs). Visual Chinese Character Checking is an emerging task, and relevant research has made progress. However, we believe that existing work has not fully leveraged the inherent knowledge of pre-trained models and has not addressed the semantic bias issue between pre-trained models and the character checking task. These challenges result in deficiencies in recognizing misspelled Chinese characters and correcting misused characters. Therefore, we propose various multimodal contrastive learning methods based on image-to-image and image-to-text comparisons. These methods are used throughout the processes of character recognition, error detection, and correction. By aligning the semantic feature representations among different models, our approach makes these models more suitable for the Visual Chinese Character Checking task, thereby enhancing their capabilities.

关键词： Chinese Character Checking Chinese Spell Checking Contrastive Learning Optical Character Recognition

来源：评论

学校读者我要写书评

暂无评论

Preserving Content in Text Style Transfer via Normalizing Flow and Adversarial Learning 13th

Preserving Content in Text Style Transfer via Normalizing Fl...

引用

13th International Conference on Natural Language Processing and Chinese Computing

作者： Dai, Jinqiao Chen, Pengsen Song, Yan Liu, Jiayong Sichuan Univ Sch Cyber Sci Chengdu 610207 Peoples R China Univ Sci & Technol China Hefei 230026 Anhui Peoples R China

ISBN: (纸本)9789819794393;9789819794409

An appropriate style can enhance the impact of social posts and comments. Although existing research is effective in accurately transferring text styles, it often results in some content loss, which disrupts the original semantic information. To address the issue of content preservation in style transfer, we extend the existing normalizing flow model and proposed a style editing module. By leveraging the transformation process of latent states in the flow model, we model the sentence content and style representations. On this basis, we accomplish style editing by replacing the original style representation with the target style. Additionally, to mitigate the impact of style editing on content representation, we introduce adversarial learning on the latent states before and after style editing, further optimizing the flow model to enhance content preservation. Extensive experiments on various datasets demonstrate that our method achieved an improvement of 3.9% in content preservation compared to the latest research. Additionally, our method attained an average style accuracy of 90.1%, proving its capability to enhance content preservation while ensuring accurate style transfer(1)((1)The code is available at https://***/djqqiao/FST).

关键词： Text style transfer Content preservation Normalizing flow Adversarial learning

来源：评论

学校读者我要写书评

暂无评论

Towards a Livvi-Karelian End-to-End ASR System 26th

Towards a Livvi-Karelian End-to-End ASR System

引用

26th International Conference on Speech and Computer

作者： Kipyatkova, Irina Kagirov, Ildar Dolgushin, Mikhail Rodionova, Alexandra Russian Acad Sci SPC RAS St Petersburg Fed Res Ctr 14th Line39 St Petersburg 199178 Russia

ISBN: (纸本)9783031779602;9783031779619

This paper presents an investigation of the performance of various end-to-end ASR models trained on low-rescourced Livvi-Karelian. Several Wav2Vec 2.0 and Whisper based models were fine-tuned, tested and compared with the hybrid TDNN-F/HMM. In the course of the experiments, end-to-end Transformer-based models have demonstrated a good performance, however the best results obtained were due to a combination of N-gram and Transformer-based models. The result of 19.83% WER on the test set were obtained using the Wav2Vec 2.0 large model with N-gram augmentation, thus being on par with SOTA models for other low-resource languages. Besides, this paper presents a new language corpus of Livvi-Karelian, containing transcripts from radio broadcasts, featuring samples from 17 speakers (7 males and 10 females). Covering about 4.5 h of audio recordings, it contains 32,037words, thus being a valuable tool for linguistic research. The findings of the presented work may be of considerable interest both for low-resource ASR and field Finnougristics.

关键词： Livvi-Karelian Speech Corpora Code-Switching

来源：评论

学校读者我要写书评

暂无评论

METER: Multimodal Hallucination Detection with Mixture of Experts via Tools Ensembling and Reasoning 13th

METER: Multimodal Hallucination Detection with Mixture of Ex...

引用

13th International Conference on Natural Language Processing and Chinese Computing

作者： Zhang, Ruwen Chen, Jinglu Dai, Mingjie Jiang, Xinyi Hu, Yuxin Liu, Bo Cao, Jiuxin Southeast Univ Nanjing Peoples R China

ISBN: (纸本)9789819794423;9789819794430

The development of Large Vision-Language Models (LVLMs) has been hindered by hallucinations. Existing methods often struggle to accurately infer relationships between objects and their attributes, and frequently overlook the challenges posed by semantic duality. In this work, we develop METER, a novel multimodal hallucination detection method that utilizes a mixture of experts through tool-supported reasoning and ensembling. Specifically, our model rethinks and infers based on the decomposed reasoning steps derived from the chain-of-thought prompts, which eliminates the need for additional manual templates and recognizes attributes of hallucination step by step. We also use topics discovered from image-text pairs to distinguish ambiguous text, mitigating semantic duality. Furthermore, we investigate the effects of incorporating external tools into hallucination detection, exploring the variations and efficacy of tool ensembling in mitigating hallucinations. Additionally, we successfully alleviate hallucinations by incorporating METER's explanation into the prompt. Extensive experiments demonstrate the effectiveness of our model. Our codes are available at https://***/lambdarw/METER.

关键词： Hallucination Detection LVLMs Tools Integration CoT

来源：评论

学校读者我要写书评

暂无评论

CausalAPM: Generalizable Literal Disentanglement for NLU Debiasing 13th

CausalAPM: Generalizable Literal Disentanglement for NLU Deb...

引用

13th International Conference on Natural Language Processing and Chinese Computing

作者： Dou, Shihan Gao, Songyang Gui, Tao Zhang, Qi Fudan Univ Sch Comp Sci Shanghai Peoples R China Fudan Univ Inst Modern Languages & Linguist Shanghai Peoples R China Shanghai Collaborat Innovat Ctr Intelligent Visua Shanghai Peoples R China

ISBN: (纸本)9789819794300;9789819794317

Dataset bias, i.e., the over-reliance on dataset-specific literal heuristics, is getting increasing attention for its detrimental effect on the generalization ability of NLU models. Existing works focus on eliminating dataset bias by down-weighting problematic data in the training process, which induces the omission of valid feature information while mitigating bias. In this work, we analyze the causes of dataset bias from the perspective of causal inference and propose CausalAPM, a generalizable literal disentangling framework to ameliorate the bias problem from feature granularity. The proposed approach projects literal and semantic information into independent feature subspaces, and constrains the involvement of literal information in subsequent predictions. Extensive experiments on three NLP benchmarks (i.e., MNLI, FEVER, and QQP) demonstrate that our proposed framework significantly improves the OOD generalization performance while maintaining ID performance.

关键词： Dataset Bias NLU Debiasing

来源：评论

学校读者我要写书评

暂无评论

Generative Dialogue Sentiment and Act Recognition with Feature Denoising and Set Prediction 13th

Generative Dialogue Sentiment and Act Recognition with Featu...

引用

13th International Conference on Natural Language Processing and Chinese Computing

作者： Liu, Jiahui Li, Bobo Li, Zhuang Chai, Yuyang Li, Fei Teng, Chong Ji, Donghong Wuhan Univ Sch Cyber Sci & Engn Key Lab Aerosp Informat Secur & Trusted Comp Minist Educ Wuhan Peoples R China Monash Univ Fac Informat Technol Melbourne Vic Australia

ISBN: (纸本)9789819794423;9789819794430

Joint dialog sentiment classification and act recognition focus on the simultaneous identification of sentiment and act categories of every utterance from conversations. Current classification-based methods often rely on complex structures to model label dependencies, which can be sensitive to noisy features in dialogue contexts. In light of this, we introduce an end-to-end generative framework, termed Sentiment and Act T5 (SAT5), specifically designed to address this joint task. Our SAT5 framework simply leverages the inherent ability of generative models to adequately model label dependencies without additional structures. Meanwhile, considering the order sensitivity issues in generative models, a set loss mechanism is further incorporated to eliminate these concerns effectively. Additionally, we develop a graph-based feature optimization strategy grounded in the information bottleneck principle, aimed at minimizing the impact of noisy features. Experiments on two public datasets demonstrate that our SAT5 framework significantly outperforms previous models. In-depth analysis further validates the efficacy and rationality of our set loss mechanism and feature optimization strategy.

关键词： Generative Model Sentiment Analysis Dialogue Understanding Feature Denoising Set Prediction

来源：评论

学校读者我要写书评

暂无评论

Don't Click the Bait: Title Debiasing News Recommendation via Cross-Field Contrastive Learning 13th

Don't Click the Bait: Title Debiasing News Recommendation vi...

引用

13th International Conference on Natural Language Processing and Chinese Computing

作者： Shu, Yijie Zhang, Xiaokun Wu, Youlin Xu, Bo Yang, Liang Li, Hongfei Dalian Univ Technol Sch Comp Sci & Technol Dalian 116024 Peoples R China

ISBN: (纸本)9789819794393;9789819794409

News recommendation emerges as a primary means for users to access content of interest from the vast amount of news. The title click-bait extensively exists in news domain and increases the difficulty for news recommendation to offer satisfactory services for users. Fortunately, we find that news abstract, as a critical field of news, aligns cohesively with the news authenticity. To this end, we propose a Title Debiasing News Recommendation with Cross-field Contrastive learning (TDNR-C-2) to overcome the title bias by incorporating news abstract. Specifically, a multi-field knowledge extraction module is devised to extract multi-view knowledge about news from various fields. Afterwards, we present a cross-field contrastive learning module to conduct bias removal via contrasting learned knowledge from title and abstract fileds. Experimental results on a real-world dataset demonstrate the superiority of the proposed TDNR-C-2 over existing state-of-the-art methods. Further analysis also indicates the significance of news abstract for title debiasing.

关键词： News Recommendation Contrastive Learning Text-based sequence modeling

来源：评论

学校读者我要写书评

暂无评论

Evaluation and Analysis of the Chinese Semantic Dependency Understanding Ability of Large Language Models 13th

Evaluation and Analysis of the Chinese Semantic Dependency U...

引用

13th International Conference on Natural Language Processing and Chinese Computing

作者： Shen, Zizhuo Li, Wei Shao, Yanqiu Beijing Language & Culture Univ Beijing Peoples R China

ISBN: (纸本)9789819794362;9789819794379

Semantic Dependency Graph is a framework for representing deep semantic knowledge through flexible graph structures. While recent works indicate that large language models (LLMs) have impressive language and knowledge understanding abilities, it remains unclear whether they can understand this deep semantic knowledge. To explore this problem, we design four prompt-style probing tasks from aspects of semantic structure and semantic relations to adapt the inherent abilities of LLMs. To ensure thorough evaluation, we conduct extensive experiments in both in-context learning (ICL) and supervised fine-tuning (SFT) scenarios. Our findings indicate that the understanding of deep semantic knowledge requires larger parameter scale, especially the understanding of high-order semantic structure knowledge and semantic relation knowledge. Furthermore, our experiments reveal that while LLMs perform well on the in-domain (ID) test set via SFT, their generalization ability on out-of-domain (OOD) test set remains inadequate.

关键词： Semantic Dependency Graph Large Language Model Evaluation

来源：评论

学校读者我要写书评

暂无评论

Assessing Translation Quality of Hypotactic Structure for Chinese-to-English Machine Translation 13th

Assessing Translation Quality of Hypotactic Structure for Ch...

引用

13th International Conference on Natural Language Processing and Chinese Computing

作者： Feng, Wenhe Chen, Xiao'en Li, Nan Guangdong Univ Foreign Studies Ctr Linguist & Appl Linguist Guangzhou Peoples R China Guangdong Univ Foreign Studies Lab Language Engn & Comp Guangzhou Peoples R China

ISBN: (纸本)9789819794362;9789819794379

Hypotactic structure translation, essentially a discourse-level question, is a big challenge in Chinese-to-English (C-E) machine translation (MT). This paper explores the assessment of translation quality of hypotactic structure for C-E MT. We argue that translating a hypotactic structure in C-E translation is essentially transforming a Chinese discoursal semantic hypotactic structure (DS-hypotactic structure) to an English syntactic hypotactic structure (S-hypotactic structure). We propose a scheme to identify the Chinese DS-hypotactic structure and the corresponding English S-hypotactic structure, and formulate the assessment criteria. We then assess the translation quality of current MT systems. The results show that MT technology is still far from satisfactory in translating hypotactic structures. Finally, we discuss the criterion for identifying the Chinese DS-hypotactic structure and reasons and solutions of this MT problem.

关键词： Translation Assessment Discourse Translation Hypotactic Structure Machine Translation

来源：评论

学校读者我要写书评

暂无评论

ChildTinyTalks (CTT): A Benchmark Dataset and Baseline for Expressive Child Speech Synthesis 26th

ChildTinyTalks (CTT): A Benchmark Dataset and Baseline for E...

引用

26th International Conference on Speech and Computer

作者： Alwaisi, Shaimaa Al-Radhi, Mohammed Salah Nemeth, Geza Budapest Univ Technol & Econ Dept Telecommun & Artificial Intelligence Budapest Hungary

ISBN: (纸本)9783031779602;9783031779619

Designing expressive speech synthesis for child voice remains an unresolved problem. One of the major dilemmas faced by child TTS systems and child speech synthesis is the scarcity of datasets to train opaque data-hungry DNN-based models. Only a few datasets were proposed for the purpose of building child conversational AI agents, and many of them come with challenges such as noisy data and indiscernible speech. With this in mind, we introduce the ChildTinyTalks (CTT) dataset, comprising 2 h of speech collected from 25 kids in grades ranging from third to fourth grade, who are telling stories and sharing their experiences. The new dataset containing 1200 audio samples has been transcribed at the word level, comprising 4 classes of voice expressions. To verify the effectiveness of CTT in real-world situations, AutoVocoder models were trained and synthesized samples were generated. The models were trained on both the LJSpeech large scale dataset and our CTT dataset. Initial experimental results indicate that the CTT dataset can steadily give comparable results with acoustic model trained on a large-scale dataset with a size of less than 10% of the large dataset.

关键词： Child Speech Dataset Child Speech AutoVocoder

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共500页 << < 19 20 21 22 23 24 25 26 27 28 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：