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41-50 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：

Benchmarking Whisper Under Diverse Audio Transformations and Real-Time Constraints 26th

Benchmarking Whisper Under Diverse Audio Transformations and...

引用

26th International Conference on Speech and Computer

作者： Katkov, Sergei Liotta, Antonio Vietti, Alessandro Free Univ Bozen Bolzano I-39100 Bolzano Italy

ISBN: (纸本)9783031779602;9783031779619

The automatic speech recognition (ASR) domain has advanced considerably with the emergence of large transformer-based models, such as OpenAI'sWhisper. This paper presents an experimental-based evaluation of the Whisper models, focusing on its performance under various acoustic conditions and input configurations. We specifically examine the effects of audio transformations such as white and Gaussian noise, reverberation, time stretch, and pitch shift, as well as the impact of varying chunk lengths. The findings suggest that while Whisper models are capable of dealing with minimal background noise and demonstrate commendable performance in clean audio conditions, their performance degrades rapidly when subjected to more severe audio transformations and noise, particularly when using shorter chunk lengths. This study contributes valuable insights into the Whisper model's capabilities and limitations, particularly when it comes to real-time speech recognition, offering guidance for future improvements in ASR technology.

关键词： Automatic speech recognition

来源：评论

学校读者我要写书评

暂无评论

Language-Emphasized Cross-Lingual In-Context Learning for Multilingual LLM 13th

Language-Emphasized Cross-Lingual In-Context Learning for Mu...

引用

13th International Conference on Natural Language Processing and Chinese Computing

作者： Li, Jun Wei, Xiao Wang, Xiaobao Zhuang, Ning Wang, Longbiao Dang, Jianwu Tianjin Univ Tianjin Key Lab Cognit Comp & Applicat Coll Intelligence & Comp Tianjin 300350 Peoples R China

ISBN: (纸本)9789819794362;9789819794379

With the recent rise of large language models (LLMs), in-context learning (ICL) has shown remarkable performance, eliminating the need for fine-tuning parameters and reducing the reliance on extensive labeled data. However, the intricacies of cross-lingual ICL remain underexplored. Prior studies on cross-lingual ICL overlooked the significance of language-specific nuances, neglecting the intrinsic linguistic properties of sentences and the interlingual connections between sentences in different languages. In this paper, we propose a novel cross-lingual prompt structure: Language-Emphasized cross-lingual In-context learning (LEI). LEI teaches LLMs how to adapt to language conversion by adding explicit language conversion examples in demonstrations. Specifically, LEI introduces a third language (example language) as an example of language conversion to adapt LLMs to language conversion in cross-lingual tasks. In addition, language alignment of demonstrations is achieved by adding language aligners and label aligners. Extensive experiments validate the state-of-the-art performance of LEI on 42 cross-lingual tasks.

关键词： Large Language Models In-context Learning Cross-Lingual

来源：评论

学校读者我要写书评

暂无评论

Influence of Linguistic and Sociolinguistic Factors on Speech Rate Perception 26th

Influence of Linguistic and Sociolinguistic Factors on Speec...

引用

26th International Conference on Speech and Computer

作者： Ananeva, Anastasia Kochetkova, Uliana St Petersbourg State Univ St Petersbourg Russia

ISBN: (纸本)9783031779602;9783031779619

This study aims to investigate the perception of speech rate in Russian. The goal is to examine the impact of pauses duration, articulation rate, as well as speaker's and listener's gender on speech rate perception. The relevance of this study lies in its potential to improve speech synthesis systems by understanding how speech rate perception varies, particularly between genders. The novelty of the research is in its comprehensive analysis of the impact of gender, articulation speed, and pauses on speech rate perception based on Russian language material. The material of the current study consists of recordings of 2 texts read by 55 native Russian speakers. The series of auditory perceptual experiments contained both natural and modified stimuli. The results of the experiments revealed the impact of speaker's gender on speech rate perception, but no impact of listener's gender. We also found the effect of pauses duration on overall speech rate perception. The results of the study showed that we can describe the speech rate perception through its intrinsic characteristics, such as pausing and articulation rate. We also proposed a model of speech rate perception in Russian language. Although this study did not focused on the effect that speech style and other factors may produce, the data obtained allow identifying important patterns in listener's behavior, that can be applied in natural language processing, as well as in artificial intelligence systems.

关键词： Speech rate Articulation rate Perception Gender

来源：评论

学校读者我要写书评

暂无评论

ConFit: Contrastive Fine-Tuning of Text-to-Text Transformer for Relation Classification 13th

ConFit: Contrastive Fine-Tuning of Text-to-Text Transformer ...

引用

13th International Conference on Natural Language Processing and Chinese Computing

作者： Duan, Jiaxin Lu, Fengyu Liu, Junfei Peking Univ Beijing Peoples R China

ISBN: (纸本)9789819794331;9789819794348

Relation classification (RC) is commonly the second step in a relation extraction pipeline, which asserts the relation of two identified entities based on their context. The latest trend for dealing with the task resorts to pre-trained language models (PLMs). It transforms the discriminative RC into a linguistics problem and fully induces the language knowledge PLMs derived from pre-training. Despite the visible progress, existing approaches handle only one relation between each entity pair while workless in real cases where multiple relations may be valid, i.e., entity pair overlap (EPO), leading to their limited applications. In this paper, we introduce ConFit, a novel contrastive learning based approach that fine-tunes text-to-text PLM for relation classification. ConFit reformulates RC as a restoration problem of textualized relations, and it learns to bind sequential words of a candidate relation with a probability mass above or below a threshold, corresponding to whether the relation truly holds. As a result, the learned model adaptively phrases diverse relations through a decoding, scoring, and selection workflow to fit EPO scenarios. Extensive experiments on four widely used datasets evidence that T5-large fine-tuned with ConFit significantly outperforms previous methods, whether single or multiple relations exist.

关键词： Relation classification Fine-tuning Contrastive learning

来源：评论

学校读者我要写书评

暂无评论

Overview of the NLPCC 2024 Shared Task: Chinese Essay Discourse Logic Evaluation and Integration 13th

Overview of the NLPCC 2024 Shared Task: Chinese Essay Discou...

引用

13th International Conference on Natural Language Processing and Chinese Computing

作者： Zhou, Yuhao Wu, Hongyi Shen, Xinshu Lan, Man Wu, Yuanbin Bai, Xiaopeng Mao, Shaoguang Ge, Tao Xia, Yan East China Normal Univ Sch Comp Sci & Technol Shanghai Peoples R China East China Normal Univ Shanghai Inst AI Educ Shanghai Peoples R China East China Normal Univ Dept Chinese Language & Literature Shanghai Peoples R China Microsoft Res Asia Beijing Peoples R China

ISBN: (纸本)9789819794423;9789819794430

This paper presents an overview of the second Chinese Essay Discourse Logic Evaluation and Integration (CEDLEI) competition, which is organized as NLPCC 2024 Shared Task 4. As the second edition of the competition, this task expands and improves upon the success of the first edition. Based on the foundation of inter-sentence and inter-paragraph logical relation identification in the first edition, this year's competition introduces the addition of discourse coherence feedback generation. These improvements aim to reduce the burden of essay marking on teachers while providing students with more consistent and objective assessments. Through these tracks, participants will explore and apply the latest natural language processing techniques to enhance the accuracy and efficiency of Chinese composition assessment. Task information is available at https://***/cubenlp/NLPCC-2024-Shared-Task4.

关键词： Discourse Logic Relation Discourse Coherence Feedback Generation

来源：评论

学校读者我要写书评

暂无评论

Sentiment Analysis for Egyptian Arabic-English Code-Switched Data Using Traditional Neural Models and Advanced Language Models 26th

Sentiment Analysis for Egyptian Arabic-English Code-Switched...

引用

26th International Conference on Speech and Computer

作者： Sherif, Ahmed Sabty, Caroline German Int Univ Reg Ring Rd Cairo Egypt

ISBN: (纸本)9783031780134;9783031780141

As code-switching on social media becomes more common, the amount of bilingual users and code-switched data is rapidly increasing. This presents unique challenges for sentiment analysis, which has traditionally focused on monolingual text. Sentiment analysis involves categorizing sentiments from comments, reviews, or tweets into positive, negative, or neutral. To address the scarcity of research in code-switched sentiment analysis, this paper contributes the first code-switched corpus for Egyptian Arabic-English sentiment analysis (EESA), featuring 4,100 annotated YouTube comments. Another contribution is the implementation of various sentiment analysis models, including traditional neural models (BiLSTM-Attention and Hybrid-Transformer) and the utilization of advanced language models (Gemini and GPT). Traditional models, using non-contextual, contextual, and character embeddings with additional word features, achieved an ensemble test F1-score of 92.54%. Advanced models, evaluated in zero-shot and fine-tuned configurations, showed significant potential. Gemini-1.5 and GPT-4o performed well as zero-shot models, and the fine-tuned GPT-3.5 model achieved the highest test F1-score of 92.67%. This work compares traditional and advanced models, highlighting advancements in code-switched sentiment analysis.

关键词： NLP Code-switching Sentiment analysis Deep learning Arabic language

来源：评论

学校读者我要写书评

暂无评论

Local or Global Optimization for Dialogue Discourse Parsing 13th

Local or Global Optimization for Dialogue Discourse Parsing

引用

13th International Conference on Natural Language Processing and Chinese Computing

作者： Wang, Chengrui Ji, Shaoming Kong, Fang Soochow Univ Lab Nat Language Proc Suzhou Peoples R China Soochow Univ Sch Comp Sci & Technol Suzhou Peoples R China

ISBN: (纸本)9789819794300;9789819794317

Dialogue Discourse Parsing aims to identify the discourse links and relations between utterances, which has attracted more interest in recent years. Previous studies either adopt local optimization to independently select one parent for each utterance or use global optimization to directly get the tree representing the dialogue structure. However, the influence of these two optimization methods remains less explored. In this paper, we aim to systematically inspect their performance. Specifically, for local optimization, we use local loss during the training stage and a greedy strategy during the inference stage. For global optimization, We implement optimization of unlabeled and labeled trees by structured losses including Max-Margin and TreeCRF, and exploit Chu-Liu-Edmonds algorithm during the inference stage. Experiments shows that the performance of these two optimization methods is closely related to the characteristics of the dataset, and global optimization can reduce the burden of identifying long-range dependency relations.

关键词： Dialogue discourse parsing Local optimization Global optimization

来源：评论

学校读者我要写书评

暂无评论

Editing Personality For Large Language Models 13th

Editing Personality For Large Language Models

引用

13th International Conference on Natural Language Processing and Chinese Computing

作者： Mao, Shengyu Wang, Xiaohan Wang, Mengru Jiang, Yong Xie, Pengjun Huang, Fei Zhang, Ningyu Zhejiang Univ Hangzhou Peoples R China Alibaba Grp Hangzhou Peoples R China

ISBN: (纸本)9789819794331;9789819794348

This paper introduces an innovative task focused on editing the personality traits of Large Language Models (LLMs). This task seeks to adjust the models' responses to opinion-related questions on specified topics since an individual's personality often manifests in the form of their expressed opinions, thereby showcasing different personality traits. Specifically, we construct PersonalityEdit, a new benchmark dataset to address this task. Drawing on the theory in Social Psychology [10], we isolate three representative traits, namely Neuroticism, Extraversion, and Agreeableness, as the foundation for our benchmark. We then gather data using GPT-4, generating responses that align with a specified topic and embody the targeted personality trait. We conduct comprehensive experiments involving various baselines and discuss the representation of personality behavior in LLMs. Our findings uncover potential challenges of the proposed task, illustrating several remaining issues. We anticipate that our work can stimulate further annotation in model editing and personality-related research.

关键词： Personality Trait Large Language Model Model Editing

来源：评论

学校读者我要写书评

暂无评论

Humor Recognition Based on Dual Graph Attention Network with Incongruity and Ambiguity Feature Extraction 13th

Humor Recognition Based on Dual Graph Attention Network with...

引用

13th International Conference on Natural Language Processing and Chinese Computing

作者： Ping, Zhichao Liu, Zhi Wang, Mengyi Lin, Hongfei Zhang, Yijia Dalian Maritime Univ Sch Informat Sci & Technol Dalian 116024 Liaoning Peoples R China Dalian Univ Technol Sch Comp Sci & Technol Dalian 116026 Liaoning Peoples R China

ISBN: (纸本)9789819794393;9789819794409

Humor, a fundamental aspect of human communication, poses a formidable challenge for computational systems. Drawing inspiration from the theory of incongruity, we introduce a novel Dual Graph Attention Network-based Feature Extraction Model (DGFEM) tailored specifically for humor recognition. This model constructs a comprehensive relational graph among linguistic tokens, thereby capturing the essence of incongruity that often underlies humorous content. Furthermore, it integrates WordNet for leveraging synonym relationships, enhancing the model's capacity to identify ambiguity, a key characteristic of humor. Through rigorous experimentation conducted on two benchmark datasets, our DGFEM model has demonstrated remarkable effectiveness in humor recognition, underscoring its potential to advance the state-of-the-art in this domain.

关键词： Humor recognition Graph attention network Incongruity feature Ambiguity feature

来源：评论

学校读者我要写书评

暂无评论

A Simple and Effective Span Interaction Modeling Method for Enhancing Multiple Span Question Answering 13th

A Simple and Effective Span Interaction Modeling Method for ...

引用

13th International Conference on Natural Language Processing and Chinese Computing

作者： Zhang, Yingying Luo, Zhiyi Ding, Zuohua Zhejiang Sci Tech Univ Hangzhou Peoples R China

ISBN: (纸本)9789819794300;9789819794317

Although multi-span question-answering tasks align more closely with the complex demands of the real world, existing models often struggle to effectively model the dependencies and overall semantic structure between multiple answer spans. Therefore, we propose a concise and effective method for modeling span interactions, which primarily includes: 1) a Span Representation Module that utilizes SpanBERT to enhance span information within tokens;and 2) a Span Interaction Module that leverages two contrastive learning tasks to reinforce answer spans' interaction within token representation. On one hand, we use the [CLS] token as an intermediary variable to carry information of span interaction, and on the other hand, we employ prompt-based tasks to further strengthen the multi-span question-answering reasoning capabilities of encoder and the span aggregation ability of the CLS token. Experiments demonstrate that baselines, on MultiSpanQA, incorporating our strategy achieved an improvement in EM F1 ranging from 2.88 to 11.27, achieving state-of-the-art (SOTA) results at equivalent model scales.

关键词： Reading Comprehension Multi-Span Question Answering Span Modeling Contrastive Learning

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 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：