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Can LLMs Clarify? Investigation and Enhancement of Large Language Models on Argument Claim Optimization 31

Can LLMs Clarify? Investigation and Enhancement of Large Lan...

引用

31st International Conference on Computational Linguistics, COLING 2025

作者： Wang, Yiran He, Ben Chen, Xuanang Sun, Le School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Chinese Information Processing Laboratory Institute of Software Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798891761964

In argumentation, the claim is the foundational proposition that underpins the argument, serving as the central pillar upon which the argument is constructed. It guides the subsequent presentation of evidence, reasoning, and analysis, thereby facilitating the audience's understanding of the core issue. Therefore, ensuring that the claim is precise and unambiguous is crucial for constructing a coherent and persuasive argument. While Large Language Models (LLMs) have demonstrated proficiency in text rewriting tasks such as style transfer and query rewriting, their application to claim optimization remains unexplored. Unlike other rewriting tasks, claim clarification requires the model to rewrite ambiguous or unclear segments of the claim, enhance the content by adding omitted key details, and eliminate redundant or verbose elements. Addressing this gap, this paper evaluates the performance of LLMs on the claim clarification task across various settings. While popular rewriting evaluation methods such as BLEU and ROUGE rely on exact word matching, this paper introduces a novel semantic evaluation approach based on a sliding window mechanism. Three distinct LLMs, including LLama2, Mistral, and Qwen2, are assessed for their ability to clarify arguments through zero-shot or few-shot prompting, and supervised fine-tuning (SFT). Additionally, we propose a reinforcement learning-based clarification approach that optimally balances content preservation with claim clarity, thereby augmenting the performance of LLMs on the claim clarification task. © 2025 Association for Computational Linguistics.

关键词： Semantics

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A Concept Drift Tolerant Abnormal Detection Method for Network Traffic 15

A Concept Drift Tolerant Abnormal Detection Method for Netwo...

引用

15th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2023

作者： Wang, Xu Han, Li Sun, Shimin Xu, Guowei Tianjin University of Technology National Engineering Laboratory for Computer Virus Prevention and Control Technology School of Computer Science and Engineering Tianjin China Tiangong University School of Software Tianjin China

ISBN: (纸本)9798350308693

we propose a cutting-edge solution that leverages passive adaptive methods based on ensemble learning to effectively detect anomalous traffic in data streams. Our approach tackles the issue of concept drift by integrating various deep learning models, each offering a unique perspective to learn data features. By doing so, our solution can accurately capture the distribution of data concepts and propose weight layers to make the model adaptable to changes caused by concept drift. In a series of experiments conducted on public datasets, our model demonstrated remarkable effectiveness in detecting anomalies, achieving accuracy rates of over 97% after adapting to concept drift. © 2023 IEEE.

关键词： Learning systems

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On the Fine-Grained Query Complexity of Symmetric Functions 34

On the Fine-Grained Query Complexity of Symmetric Functions

引用

34th International Symposium on Algorithms and Computation, ISAAC 2023

作者： Podder, Supartha Yao, Penghui Ye, Zekun Department of Computer Science Stony Brook University New YorkNY United States State Key Laboratory for Novel Software Technology Nanjing University China Hefei National Laboratory China State Key Laboratory for Novel Software Technology Nanjing University China

ISBN: (纸本)9783959772891

Watrous conjectured that the randomized and quantum query complexities of symmetric functions are polynomially equivalent, which was resolved by Ambainis and Aaronson [1], and was later improved in [15, 12]. This paper explores a fine-grained version of the Watrous conjecture, including the randomized and quantum algorithms with success probabilities arbitrarily close to 1/2. Our contributions include the following: 1. An analysis of the optimal success probability of quantum and randomized query algorithms of two fundamental partial symmetric Boolean functions given a fixed number of queries. We prove that for any quantum algorithm computing these two functions using T queries, there exist randomized algorithms using poly(T) queries that achieve the same success probability as the quantum algorithm, even if the success probability is arbitrarily close to 1/2. These two classes of functions are instrumental in analyzing general symmetric functions. 2. We establish that for any total symmetric Boolean function f, if a quantum algorithm uses T queries to compute f with success probability 1/2 + β, then there exists a randomized algorithm using O(T2) queries to compute f with success probability 1/2 + Ω (δβ2) on a 1 − δ fraction of inputs, where β, δ can be arbitrarily small positive values. As a corollary, we prove a randomized version of Aaronson-Ambainis Conjecture [1] for total symmetric Boolean functions in the regime where the success probability of algorithms can be arbitrarily close to 1/2. 3. We present polynomial equivalences for several fundamental complexity measures of partial symmetric Boolean functions. Specifically, we first prove that for certain partial symmetric Boolean functions, quantum query complexity is at most quadratic in approximate degree for any error arbitrarily close to 1/2. Next, we show exact quantum query complexity is at most quadratic in degree. Additionally, we give the tight bounds of several complexity measures, indicating their p

关键词： Quantum theory

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Quantum Pseudorandom Scramblers 22nd

Quantum Pseudorandom Scramblers

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22nd Theory of Cryptography Conference, TCC 2024

作者： Lu, Chuhan Qin, Minglong Song, Fang Yao, Penghui Zhao, Mingnan Computer Science Department Portland State University Portland United States State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China Hefei National Laboratory Hefei230088 China

ISBN: (纸本)9783031780165

Quantum pseudorandom state generators (PRSGs) have stimulated exciting developments in recent years. A PRSG, on a fixed initial (e.g., all-zero) state, produces an output state that is computationally indistinguishable from a Haar random state. However, pseudorandomness of the output state is not guaranteed on other initial states. In fact, known PRSG constructions provably fail on some initial states. In this work, we propose and construct quantum Pseudorandom State Scramblers (PRSSs), which can produce a pseudorandom state on an arbitrary initial state. In the information-theoretical setting, we obtain a scrambler which maps an arbitrary initial state to a distribution of quantum states that is close to Haar random in total variation distance. As a result, our scrambler exhibits a dispersing property. Loosely, it can span an ϵ-net of the state space. This significantly strengthens what standard PRSGs can induce, as they may only concentrate on a small region of the state space provided that the average output state approximates a Haar random state. Our PRSS construction develops a parallel extension of the famous Kac’s walk, and we show that it mixes exponentially faster than the standard Kac’s walk. This constitutes the core of our proof. We also describe a few applications of PRSSs. While our PRSS construction assumes a post-quantum one-way function, PRSSs are potentially a weaker primitive and can be separated from one-way functions in a relativized world similar to standard PRSGs. © International Association for Cryptologic Research 2025.

关键词： Distribution functions

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An Artificial Intelligence-Based Segmentation Auxiliary Diagnostic System for Focal Liver Lesions 2

An Artificial Intelligence-Based Segmentation Auxiliary Diag...

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2nd International Conference on Mechatronics, IoT and Industrial Informatics, ICMIII 2024

作者： Gu, Jingjun Yu, Zhi Zhang, Wei Hu, Haoyu Zhejiang University Zhejiang Provincial Key Laboratory of Service Robot College of Computer Science Hangzhou China Zhejiang University School of Software Technology Hangzhou China

ISBN: (纸本)9798350386639

In this paper, we introduce an artificial intelligence-based system designed for the segmentation and auxiliary diagnosis of focal liver lesions. This system can effectively segment lesions in both singlephase non-contrast CT images and multiphase contrast-enhanced CT images. Additionally, it has the capability to synchronize CT data from Picture Archiving and Communication Systems (PACS) and to visualize the segmentation results. Our AI system aims to meet the demand for rapid screening of liver lesions in primary hospitals and physical examination institutions, while also fulfilling the more precise segmentation needs of provincial and municipal hospitals. © 2024 IEEE.

关键词： Picture archiving and communication systems

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Multisource transfer learning based on multiconcept and multispace for text classification 3

Multisource transfer learning based on multiconcept and mult...

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3rd International Symposium on computer Applications and Information Systems, ISCAIS 2024

作者： Qu, Qiaoli Zhu, Yi Pan, Jianhan School of Computer Science and Technology Jiangsu Normal University Xuzhou China The Key Laboratory of the Software Development and Verification Technology The Ministry of Industry and Information Technology Nanjing University of Aeronautics and Astronautics Nanjing210016 China

ISBN: (纸本)9781510681316

Many multi-source transfer learning methods use the latent attributes between source domains to mitigate interference. However, these strategies have some shortcomings. Strategies that only use commonality may lose valuable latent information specific to a single source domain when extracting knowledge. Strategies that focus on specificity are limited by the differences between source domains, so they cannot effectively integrate different knowledge. For strategies that include both attributes, they only explore the knowledge scattered in the original source domains, and do not attempt to explore additional knowledge, which can fill the learning gap and promote knowledge fusion. Based on the above problems, this paper proposes a multi-source transfer learning method that can deeply mine the commonality and characteristics of multiple source domains and fully integrate all the latent information by reconstructing the multi-source latent feature space and combining high-level concept learning. Finally, we conduct a large number of experiments to verify the effectiveness and superiority of the algorithm. © 2024 SPIE.

关键词： Learning systems

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SSAST-Adapter: A Parameter-efficient Incremental Learning Algorithm for Underwater Acoustic Target Recognition

SSAST-Adapter: A Parameter-efficient Incremental Learning Al...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Zhu, Qian Xu, Qisheng Zhu, Boqing Gao, Zijian Zeng, Lingbin Xu, Kele College of Computer Science and Technology National University of Defense Technology Changsha China State Key Laboratory of Complex & Critical Software Environment Changsha China College of Meteorology and Oceanography National University of Defense Technology Changsha China

ISBN: (纸本)9798350368741

Underwater acoustic target recognition involves identifying and classifying targets in underwater environments using acoustic signals. In recent years, deep learning has made significant progress in this field. However, the models require the entire dataset to be available upfront, and classification categories must be predefined. In practical scenarios, new objects or species may appear in underwater environments over time, making it impractical to retrain a model from scratch each time new data is introduced. At the same time, training on new data inevitably leads to catastrophic forgetting of past data. To address these challenges, we propose a large-scale pre-training strategy combined with adapters to enable incremental learning without the need for complete retraining. To minimize the number of parameters during model fine-tuning, we employ a adapter structure at various network layers, reducing the number of trainable parameters to less than 2%. Experimental results demonstrate that our proposed method effectively reduces the need for full retraining by allowing the model to update in a resource-efficient manner using only new data, and the model has achieved high recognition accuracy in underwater acoustic target recognition tasks. © 2025 IEEE.

关键词： Adapter Audio Spectrum Transformer Incremental Learning Underwater Acoustics Target Recognition

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A concise and visual computational interpretation of emotional expression in hand-drawn lines 3

A concise and visual computational interpretation of emotion...

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3rd International Conference on Machine Vision, Automatic Identification, and Detection, MVAID 2024

作者： Li, Jiayi Li, Yize Lin, Yunhui Lyu, Ruimin School of Artificial Intelligence and Computer Science Jiangnan University Wuxi214000 China Jiangsu Key Laboratory of Media Design and Software Technology Wuxi214000 China

ISBN: (纸本)9781510681880

In the realms of visual arts and psychology, it's acknowledged that lines and their properties significantly impact human emotional responses. Historically, various characteristics of lines have been proposed for emotional expression research, yet, the pivotal technique in computer vision, Scale-Invariant Feature Transform (SIFT), has frequently been disregarded. computing SIFT key points and their orientations on lines unveils the morphological traits of lines and deciphers their connection with specific emotional states. This method is not only concise in computation but also offers intuitive visualizations and explanations. Our investigation delves into the crucial role of SIFT features in conveying emotions from a computational vision standpoint. By scrutinizing SIFT features extracted from hand-drawn line images, we examined the trends in the quantity and orientation of feature points, and vividly illustrated how these points influence line morphology. Logistic regression analysis has further exposed the linkage between feature points and emotional dimensions such as pleasure and arousal. The results underscore the significance of SIFT features in emotional expression, facilitating the advancement of affective computing applications, as well as emotion recognition and analysis grounded in line features. © 2024 SPIE.

关键词： Regression analysis

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Enhancing the capabilities of Llama2 in biomedical applications 3

Enhancing the capabilities of Llama2 in biomedical applicati...

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3rd International Symposium on computer Applications and Information Systems, ISCAIS 2024

作者： Ren, Yuankai Xie, Zhenping School of Artificial Intelligence and Computer Science Jiangnan University Wuxi China Jiangsu Key University Laboratory of Software and Media Technology under Human-Computer Cooperation Jiangnan University Jiangsu Wuxi China

ISBN: (纸本)9781510681316

This study is dedicated to the development and evaluation of a large language model specifically optimized for the biomedical domain, using the sophisticated Llama2 architecture as its foundation. By delving into the vast corpus of biomedical literature, which includes medical research papers, news reports, drug labels, and case studies, we have curated a comprehensive training dataset comprising 10 billion tokens aimed at addressing the deficiencies of existing language models in specialized medical knowledge. During the model training phase, we initially conducted pre-training using data from the biomedical domain, followed by supervised training of a biomedical question-answering model utilizing LoRA technology. In the evaluation phase, the model's performance underwent rigorous testing with challenging datasets, including the Chinese National Medical Licensing Examination, the United States Pharmacist Licensing Examination, and the PubMedQA question-answering dataset. These tests served as a robust indicator of the model's practical applicability in real-world medical professional scenarios. Experimental results suggest that our model performs exceptionally well in various specific biomedical tasks and surpasses the well-known ChatGPT-3.5 model in key performance metrics, affirming the effectiveness of domain-optimized large language models. Despite the exemplary performance, the model still lags behind the latest ChatGPT-4, which indicates potential for improvement in understanding depth, reasoning capabilities, and knowledge updating. Overall, this research provides a potent tool for natural language processing tasks in the biomedical field and lays the groundwork for the future development of more specialized and precise large language models. © 2024 SPIE.

关键词： Statistical tests

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Handover Scheme in LEO Satellite Networks Based on QoE for Streaming Services 24

Handover Scheme in LEO Satellite Networks Based on QoE for S...

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24th IEEE International Conference on Communication technology, ICCT 2024

作者： Feng, Huazhi Zhu, Lidong Zhou, Jianhong University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu China Xihua University School of Computer and Software Engineering Chengdu China

ISBN: (纸本)9798350363760

The development of satellite communications has received considerable attention in recent years. Early satellite communications were dominated by voice and low-speed data services, but now they must support high-speed multimedia services. Low Earth orbit (LEO) satellites are an important part of the future realization of high-bandwidth and low-latency multimedia services. However, LEO satellites face many challenges in accessing and handover due to their fast-moving speed. For example, few studies have been conducted on the performance of multimedia services (including streaming services) in satellite communication environments at the Quality of Experience (QoE) level, and there are no relevant simulation systems to evaluate and examine them. Therefore, this paper builds a simulation system for streaming media services in LEO satellite communication scenarios in order to simulate the initial buffering, rebuffering, and idle state of the users during service. Then, an access and handover scheme for the QoE level of streaming media service is proposed. Finally, our proposed scheme is evaluated based on this simulation system. From the simulation results, the simulation system proposed in this paper can successfully realize the various functions of users in on- demand streaming media services. And the streaming QoE-based access and handover scheme can perform well in satellite, a resource-constrained scenario. © 2024 IEEE.

关键词： Satellite communication systems

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