ArXiv最新文献_第5页

Jack of All Trades, Master of Some, a Multi-Purpose Transformer Agent 多才多艺的变压器代理商

ArXiv Pub Date : 2024-02-15 DOI: 10.48550/arXiv.2402.09844

Quentin Gallou'edec, Edward Beeching, Cl'ement Romac, Emmanuel Dellandr'ea

引用次数: 0

Towards Reducing Diagnostic Errors with Interpretable Risk Prediction 通过可解释的风险预测减少诊断错误

ArXiv Pub Date : 2024-02-15 DOI: 10.48550/arXiv.2402.10109

Denis Jered McInerney, William Dickinson, Lucy Flynn, Andrea Young, Geoffrey Young, J.-W. van de Meent, Byron C. Wallace

{"title":"Towards Reducing Diagnostic Errors with Interpretable Risk Prediction","authors":"Denis Jered McInerney, William Dickinson, Lucy Flynn, Andrea Young, Geoffrey Young, J.-W. van de Meent, Byron C. Wallace","doi":"10.48550/arXiv.2402.10109","DOIUrl":"https://doi.org/10.48550/arXiv.2402.10109","url":null,"abstract":"Many diagnostic errors occur because clinicians cannot easily access relevant information in patient Electronic Health Records (EHRs). In this work we propose a method to use LLMs to identify pieces of evidence in patient EHR data that indicate increased or decreased risk of specific diagnoses; our ultimate aim is to increase access to evidence and reduce diagnostic errors. In particular, we propose a Neural Additive Model to make predictions backed by evidence with individualized risk estimates at time-points where clinicians are still uncertain, aiming to specifically mitigate delays in diagnosis and errors stemming from an incomplete differential. To train such a model, it is necessary to infer temporally fine-grained retrospective labels of eventual\"true\"diagnoses. We do so with LLMs, to ensure that the input text is from before a confident diagnosis can be made. We use an LLM to retrieve an initial pool of evidence, but then refine this set of evidence according to correlations learned by the model. We conduct an in-depth evaluation of the usefulness of our approach by simulating how it might be used by a clinician to decide between a pre-defined list of differential diagnoses.","PeriodicalId":8425,"journal":{"name":"ArXiv","volume":"9 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139962951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Classification Diffusion Models 分类扩散模型

ArXiv Pub Date : 2024-02-15 DOI: 10.48550/arXiv.2402.10095

Shahar Yadin, Noam Elata, T. Michaeli

{"title":"Classification Diffusion Models","authors":"Shahar Yadin, Noam Elata, T. Michaeli","doi":"10.48550/arXiv.2402.10095","DOIUrl":"https://doi.org/10.48550/arXiv.2402.10095","url":null,"abstract":"A prominent family of methods for learning data distributions relies on density ratio estimation (DRE), where a model is trained to $textit{classify}$ between data samples and samples from some reference distribution. These techniques are successful in simple low-dimensional settings but fail to achieve good results on complex high-dimensional data, like images. A different family of methods for learning distributions is that of denoising diffusion models (DDMs), in which a model is trained to $textit{denoise}$ data samples. These approaches achieve state-of-the-art results in image, video, and audio generation. In this work, we present $textit{Classification Diffusion Models}$ (CDMs), a generative technique that adopts the denoising-based formalism of DDMs while making use of a classifier that predicts the amount of noise added to a clean signal, similarly to DRE methods. Our approach is based on the observation that an MSE-optimal denoiser for white Gaussian noise can be expressed in terms of the gradient of a cross-entropy-optimal classifier for predicting the noise level. As we illustrate, CDM achieves better denoising results compared to DDM, and leads to at least comparable FID in image generation. CDM is also capable of highly efficient one-step exact likelihood estimation, achieving state-of-the-art results among methods that use a single step. Code is available on the project's webpage in https://shaharYadin.github.io/CDM/ .","PeriodicalId":8425,"journal":{"name":"ArXiv","volume":"9 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139962999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RS-DPO: A Hybrid Rejection Sampling and Direct Preference Optimization Method for Alignment of Large Language Models RS-DPO：用于大型语言模型对齐的混合拒绝采样和直接偏好优化方法

ArXiv Pub Date : 2024-02-15 DOI: 10.48550/arXiv.2402.10038

Saeed Khaki, JinJin Li, Lan Ma, Liu Yang, Prathap Ramachandra

{"title":"RS-DPO: A Hybrid Rejection Sampling and Direct Preference Optimization Method for Alignment of Large Language Models","authors":"Saeed Khaki, JinJin Li, Lan Ma, Liu Yang, Prathap Ramachandra","doi":"10.48550/arXiv.2402.10038","DOIUrl":"https://doi.org/10.48550/arXiv.2402.10038","url":null,"abstract":"Reinforcement learning from human feedback (RLHF) has been extensively employed to align large language models with user intent. However, proximal policy optimization (PPO) based RLHF is occasionally unstable requiring significant hyperparameter finetuning, and computationally expensive to maximize the estimated reward during alignment. Recently, direct preference optimization (DPO) is proposed to address those challenges. However, DPO relies on contrastive responses generated from human annotator and alternative LLM, instead of the policy model, limiting the effectiveness of the RLHF. In this paper, we addresses both challenges by systematically combining rejection sampling (RS) and DPO. Our proposed method, RS-DPO, initiates with the development of a supervised fine-tuned policy model (SFT). A varied set of k responses per prompt are sampled directly from the SFT model. RS-DPO identifies pairs of contrastive samples based on their reward distribution. Finally, we apply DPO with the contrastive samples to align the model to human preference. Our experiments indicate that our proposed method effectively fine-tunes LLMs with limited resource environments, leading to improved alignment with user intent. Furthermore, it outperforms existing methods, including RS, PPO, and DPO.","PeriodicalId":8425,"journal":{"name":"ArXiv","volume":"12 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139963040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling the Impact of Timeline Algorithms on Opinion Dynamics Using Low-rank Updates 利用低等级更新模拟时间轴算法对舆论动态的影响

ArXiv Pub Date : 2024-02-15 DOI: 10.48550/arXiv.2402.10053

Tianyi Zhou, Stefan Neumann, Kiran Garimella, A. Gionis

{"title":"Modeling the Impact of Timeline Algorithms on Opinion Dynamics Using Low-rank Updates","authors":"Tianyi Zhou, Stefan Neumann, Kiran Garimella, A. Gionis","doi":"10.48550/arXiv.2402.10053","DOIUrl":"https://doi.org/10.48550/arXiv.2402.10053","url":null,"abstract":"Timeline algorithms are key parts of online social networks, but during recent years they have been blamed for increasing polarization and disagreement in our society. Opinion-dynamics models have been used to study a variety of phenomena in online social networks, but an open question remains on how these models can be augmented to take into account the fine-grained impact of user-level timeline algorithms. We make progress on this question by providing a way to model the impact of timeline algorithms on opinion dynamics. Specifically, we show how the popular Friedkin--Johnsen opinion-formation model can be augmented based on aggregate information, extracted from timeline data. We use our model to study the problem of minimizing the polarization and disagreement; we assume that we are allowed to make small changes to the users' timeline compositions by strengthening some topics of discussion and penalizing some others. We present a gradient descent-based algorithm for this problem, and show that under realistic parameter settings, our algorithm computes a $(1+varepsilon)$-approximate solution in time $tilde{O}(msqrt{n} lg(1/varepsilon))$, where $m$ is the number of edges in the graph and $n$ is the number of vertices. We also present an algorithm that provably computes an $varepsilon$-approximation of our model in near-linear time. We evaluate our method on real-world data and show that it effectively reduces the polarization and disagreement in the network. Finally, we release an anonymized graph dataset with ground-truth opinions and more than 27,000 nodes (the previously largest publicly available dataset contains less than 550 nodes).","PeriodicalId":8425,"journal":{"name":"ArXiv","volume":"8 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139963072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

VisIRNet: Deep Image Alignment for UAV-taken Visible and Infrared Image Pairs VisIRNet：无人机拍摄的可见光和红外图像对的深度图像配准

ArXiv Pub Date : 2024-02-15 DOI: 10.48550/arXiv.2402.09635

Sedat Ozer, A. P. Ndigande

引用次数: 0

Inversion of limited-aperture Fresnel experimental data using orthogonality sampling method with single and multiple sources 使用正交采样法对有限孔径菲涅尔实验数据进行单源和多源反演

ArXiv Pub Date : 2024-02-15 DOI: 10.48550/arXiv.2402.09740

Won-Kwang Park

{"title":"Inversion of limited-aperture Fresnel experimental data using orthogonality sampling method with single and multiple sources","authors":"Won-Kwang Park","doi":"10.48550/arXiv.2402.09740","DOIUrl":"https://doi.org/10.48550/arXiv.2402.09740","url":null,"abstract":"In this study, we consider the application of orthogonality sampling method (OSM) with single and multiple sources for a fast identification of small objects in limited-aperture inverse scattering problem. We first apply the OSM with single source and show that the indicator function with single source can be expressed by the Bessel function of order zero of the first kind, infinite series of Bessel function of nonzero integer order of the first kind, range of signal receiver, and the location of emitter. Based on this result, we explain that the objects can be identified through the OSM with single source but the identification is significantly influenced by the location of source and applied frequency. For a successful improvement, we then consider the OSM with multiple sources. Based on the identified structure of the OSM with single source, we design an indicator function of the OSM with multiple sources and show that it can be expressed by the square of the Bessel function of order zero of the first kind an infinite series of the square of Bessel function of nonzero integer order of the first kind. Based on the theoretical results, we explain that the objects can be identified uniquely through the designed OSM. Several numerical experiments with experimental data provided by the Institute Fresnel demonstrate the pros and cons of the OSM with single source and how the designed OSM with multiple sources behave.","PeriodicalId":8425,"journal":{"name":"ArXiv","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139963293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reproducing, Extending, and Analyzing Naming Experiments 复制、扩展和分析命名实验

ArXiv Pub Date : 2024-02-15 DOI: 10.48550/arXiv.2402.10022

Rachel Alpern, Ido Lazer, Issar Tzachor, Hanit Hakim, Sapir Weissbuch, D. Feitelson

{"title":"Reproducing, Extending, and Analyzing Naming Experiments","authors":"Rachel Alpern, Ido Lazer, Issar Tzachor, Hanit Hakim, Sapir Weissbuch, D. Feitelson","doi":"10.48550/arXiv.2402.10022","DOIUrl":"https://doi.org/10.48550/arXiv.2402.10022","url":null,"abstract":"Naming is very important in software development, as names are often the only vehicle of meaning about what the code is intended to do. A recent study on how developers choose names collected the names given by different developers for the same objects. This enabled a study of these names' diversity and structure, and the construction of a model of how names are created. We reproduce different parts of this study in three independent experiments. Importantly, we employ methodological variations rather than striving of an exact replication. When the same results are obtained this then boosts our confidence in their validity by demonstrating that they do not depend on the methodology. Our results indeed corroborate those of the original study in terms of the diversity of names, the low probability of two developers choosing the same name, and the finding that experienced developers tend to use slightly longer names than inexperienced students. We explain name diversity by performing a new analysis of the names, classifying the concepts represented in them as universal (agreed upon), alternative (reflecting divergent views on a topic), or optional (reflecting divergent opinions on whether to include this concept at all). This classification enables new research directions concerning the considerations involved in naming decisions. We also show that explicitly using the model proposed in the original study to guide naming leads to the creation of better names, whereas the simpler approach of just asking participants to use longer and more detailed names does not.","PeriodicalId":8425,"journal":{"name":"ArXiv","volume":"23 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139963328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Characterizing Role Models in Software Practitioners' Career: An Interview Study 描述软件从业人员职业生涯中的榜样：访谈研究

ArXiv Pub Date : 2024-02-15 DOI: 10.1145/3641822.3641883

Mary S'anchez-Gord'on, Ricardo Colomo Palacios, Alex Sanchez Gordon

引用次数: 0

Orthogonal Time Frequency Space for Integrated Sensing and Communication: A Survey 用于综合传感与通信的正交时频空间：调查

ArXiv Pub Date : 2024-02-15 DOI: 10.48550/arXiv.2402.09637

Eyad Shtaiwi, Ahmed Abdelhadi, Husheng Li, Zhu Han, H. V. Poor

{"title":"Orthogonal Time Frequency Space for Integrated Sensing and Communication: A Survey","authors":"Eyad Shtaiwi, Ahmed Abdelhadi, Husheng Li, Zhu Han, H. V. Poor","doi":"10.48550/arXiv.2402.09637","DOIUrl":"https://doi.org/10.48550/arXiv.2402.09637","url":null,"abstract":"Sixth-generation (6G) wireless communication systems, as stated in the European 6G flagship project Hexa-X, are anticipated to feature the integration of intelligence, communication, sensing, positioning, and computation. An important aspect of this integration is integrated sensing and communication (ISAC), in which the same waveform is used for both systems both sensing and communication, to address the challenge of spectrum scarcity. Recently, the orthogonal time frequency space (OTFS) waveform has been proposed to address OFDM's limitations due to the high Doppler spread in some future wireless communication systems. In this paper, we review existing OTFS waveforms for ISAC systems and provide some insights into future research. Firstly, we introduce the basic principles and a system model of OTFS and provide a foundational understanding of this innovative technology's core concepts and architecture. Subsequently, we present an overview of OTFS-based ISAC system frameworks. We provide a comprehensive review of recent research developments and the current state of the art in the field of OTFS-assisted ISAC systems to gain a thorough understanding of the current landscape and advancements. Furthermore, we perform a thorough comparison between OTFS-enabled ISAC operations and traditional OFDM, highlighting the distinctive advantages of OTFS, especially in high Doppler spread scenarios. Subsequently, we address the primary challenges facing OTFS-based ISAC systems, identifying potential limitations and drawbacks. Then, finally, we suggest future research directions, aiming to inspire further innovation in the 6G wireless communication landscape.","PeriodicalId":8425,"journal":{"name":"ArXiv","volume":"18 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139963564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0