P5: Plug-and-Play Persona Prompting for Personalized Response Selection

The use of persona-grounded retrieval-based chatbots is crucial for personalized conversations, but there are several challenges that need to be addressed. 1) In general, collecting persona-grounded corpus is very expensive. 2) The chatbot system does not always respond in consideration of persona at real applications. To address these challenges, we propose a plug-and-play persona prompting method. Our system can function as a standard open-domain chatbot if persona information is not available. We demonstrate that this approach performs well in the zero-shot setting, which reduces the dependence on persona-ground training data. This makes it easier to expand the system to other languages without the need to build a persona-grounded corpus. Additionally, our model can be fine-tuned for even better performance. In our experiments, the zero-shot model improved the standard model by 7.71 and 1.04 points in the original persona and revised persona, respectively. The fine-tuned model improved the previous state-of-the-art system by 1.95 and 3.39 points in the original persona and revised persona, respectively. To the best of our knowledge, this is the first attempt to solve the problem of personalized response selection using prompt sequences. Our code is available on github~\footnote{https://github.com/rungjoo/plug-and-play-prompt-persona}.Comment: EMNLP 2023 main conferenc

PK-ICR: Persona-Knowledge Interactive Context Retrieval for Grounded Dialogue

Identifying relevant Persona or Knowledge for conversational systems is a critical component of grounded dialogue response generation. However, each grounding has been studied in isolation with more practical multi-context tasks only recently introduced. We define Persona and Knowledge Dual Context Identification as the task to identify Persona and Knowledge jointly for a given dialogue, which could be of elevated importance in complex multi-context Dialogue settings. We develop a novel grounding retrieval method that utilizes all contexts of dialogue simultaneously while also requiring limited training via zero-shot inference due to compatibility with neural Q \& A retrieval models. We further analyze the hard-negative behavior of combining Persona and Dialogue via our novel null-positive rank test

Unsupervised 3D Reconstruction Networks

In this paper, we propose 3D unsupervised reconstruction networks (3D-URN), which reconstruct the 3D structures of instances in a given object category from their 2D feature points under an orthographic camera model. 3D-URN consists of a 3D shape reconstructor and a rotation estimator, which are trained in a fully-unsupervised manner incorporating the proposed unsupervised loss functions. The role of the 3D shape reconstructor is to reconstruct the 3D shape of an instance from its 2D feature points, and the rotation estimator infers the camera pose. After training, 3D-URN can infer the 3D structure of an unseen instance in the same category, which is not possible in the conventional schemes of non-rigid structure from motion and structure from category. The experimental result shows the state-of-the-art performance, which demonstrates the effectiveness of the proposed method.N

Negative Capacitance from the Inhomogenous Stray Field in a Ferroelectric–Dielectric Structure

© 2022 Wiley-VCH GmbHThe phenomenological Landau–Ginzburg–Devonshire model provides a fundamental background for an understanding of the peculiar charge–voltage behavior of ferroelectric (FE) materials. However, the model cannot explain the polarization behavior of multidomain FE materials. The experimentally observed negative capacitance (NC) effect, which is interpreted as an emergence of the Landau barrier effect, involves particular conceptual difficulty. This work provides a new conceptual framework to explain the quasi-static NC effect based on the energy formula for a stacked dielectric/ferroelectric (DE/FE) layer structure with the multidomain configuration with arbitrary shape. The presence of such domain configuration causes the energy–displacement curve of the inhomogenous Helmholtz energy term to have negative curvature. This is caused by the stray field between the neighboring domains. The model can be further extended to the DE/FE system with polycrystalline FE grains using the advanced phase-field analysis. It is determined that the NC effect from the stray field is a universal phenomenon. These models provide quantitative explanations for the previously reported short-pulse measurement results for various DE/FE material systems, which have lacked accurate interpretations.N

Generalized mean for feature extraction in one-class classification problems

Biased discriminant analysis (BDA), which extracts discriminative features for one-class classification problems, is sensitive to outliers in negative samples. This study focuses on the drawback of BDA attributed to the objective function based on the arithmetic mean in one-class classification problems, and proposes an objective function based on a generalized mean. A novel method is also presented to effectively maximize the objective function. The experimental results show that the proposed method provides better discriminative features than the BDA and its variants. (C) 2013 Elsevier Ltd. All rights reserved.OAIID:oai:osos.snu.ac.kr:snu2013-01/102/0000014178/1SEQ:1PERF_CD:SNU2013-01EVAL_ITEM_CD:102USER_ID:0000014178ADJUST_YN:YEMP_ID:A079380DEPT_CD:495CITE_RATE:2.632DEPT_NM:융합과학부SCOPUS_YN:YCONFIRM:

IDEA: Integrating Divisive and Ensemble-Agglomerate hierarchical clustering framework for arbitrary shape data

© 2021 IEEE.Hierarchical clustering, a traditional clustering method, has been getting attention again. Among several reasons, a credit goes to a recent paper by Dasgupta in 2016 that proposed a cost function that quantitatively evaluates hierarchical clustering trees. An important question is how to combine this recent advance with existing successful clustering methods. In this paper, we propose a hierarchical clustering method to minimize the cost function of clustering tree by incorporating existing clustering techniques. First, we developed an ensemble tree-search method that finds an integrated tree with reduced cost by integrating multiple existing hierarchical clustering methods. Second, to operate on large and arbitrary shape data, we designed an efficient hierarchical clustering framework, called integrating divisive and ensemble-agglomerate (IDEA) by combining it with advanced clustering techniques such as nearest neighbor graph construction, divisive-agglomerate hybridization, and dynamic cut tree. The IDEA clustering method showed better performance in minimizing Dasgupta's cost and improving accuracy (adjusted rand index) over existing cost-minimization-based, and density-based hierarchical clustering methods in experiments using arbitrary shape datasets and complex biology-domain datasets.N

Surface Modification of Sulfur-Assisted Reduced Graphene Oxide with Poly(phenylene sulfide) for Multifunctional Nanocomposites

The sulfur on the sulfur-assisted reduced graphene oxide (SrGO) surface provides the origin of poly(phenylene sulfide) PPS-grafting via SNAr mechanism. In-situ polymerization from sulfur on SrGO afforded surface modification of SrGO, resulting in enhanced dispersibility in PPS. The tensile strength, electrical and thermal conductivities, and flame retardancy of PPS-coated SrGO were efficiently enhanced using highly concentrated SrGO and masterbatch (MB) for industrial purposes. Three-dimensional X-ray microtomography scanning revealed that diluting MB in the PPS resin afforded finely distributed SrGO across the PPS resin, compared to the aggregated state of graphene oxide. For the samples after dilution, the thermal conductivity and flame retardancy of PPS/SrGO are preserved and typically enhanced by up to 20%. The proposed PPS/SrGO MB shows potential application as an additive for reinforced PPS due to the ease of addition during the extrusion process