{"results":[{"id":"ss_c60a4fc7e01fbb4a60a358c503d6cf235e3f289f","title":"The Drama of the Commons","authors":[{"name":"E. Ostrom"},{"name":"Thomas Dietz"},{"name":"N. Dolšak"},{"name":"P. Stern"},{"name":"S. Stonich"},{"name":"E. Weber"}],"abstract":"he “tragedy of the commons” is a central concept in human ecology and the study of the environment. The prototypical scenario is simple. There is a resource—usually referred to as a common-pool resource—to which a large number of people have access. The resource might be an oceanic ecosystem from which fish are harvested, the global atmosphere into which greenhouse gases are released","source":"Semantic Scholar","year":2002,"language":"en","subjects":null,"doi":"10.17226/10287","url":"https://www.semanticscholar.org/paper/c60a4fc7e01fbb4a60a358c503d6cf235e3f289f","is_open_access":true,"citations":1512,"published_at":"","score":80},{"id":"ss_eb85c73e8bcfb66bcd5dde49e43c179e2c561ffe","title":"DRAMA: Joint Risk Localization and Captioning in Driving","authors":[{"name":"Srikanth Malla"},{"name":"Chiho Choi"},{"name":"Isht Dwivedi"},{"name":"Joonhyang Choi"},{"name":"Jiachen Li"}],"abstract":"Considering the functionality of situational awareness in safety-critical automation systems, the perception of risk in driving scenes and its explainability is of particular importance for autonomous and cooperative driving. Toward this goal, this paper proposes a new research direction of joint risk localization in driving scenes and its risk explanation as a natural language description. Due to the lack of standard benchmarks, we collected a large-scale dataset, DRAMA (Driving Risk Assessment Mechanism with A captioning module), which consists of 17,785 interactive driving scenarios collected in Tokyo, Japan. Our DRAMA dataset accommodates video- and object-level questions on driving risks with associated important objects to achieve the goal of visual captioning as a free-form language description utilizing closed and open-ended responses for multi-level questions, which can be used to evaluate a range of visual captioning capabilities in driving scenarios. We make this data available to the community for further re-search. Using DRAMA, we explore multiple facets of joint risk localization and captioning in interactive driving scenarios. In particular, we benchmark various multi-task pre-diction architectures and provide a detailed analysis of joint risk localization and risk captioning. The data set is available at https://usa.honda-ri.com/drama","source":"Semantic Scholar","year":2022,"language":"en","subjects":["Computer Science"],"doi":"10.1109/WACV56688.2023.00110","url":"https://www.semanticscholar.org/paper/eb85c73e8bcfb66bcd5dde49e43c179e2c561ffe","pdf_url":"https://arxiv.org/pdf/2209.10767","is_open_access":true,"citations":176,"published_at":"","score":71.28},{"id":"arxiv_2602.00588","title":"The French Drama Revolution: Political Economy and Literary Production, 1700-1900","authors":[{"name":"Thiago Dumont Oliveira"}],"abstract":"This paper investigates the changing nature of French drama between 1700-1900 using Latent Dirichlet Allocation and Jensen-Shannon Divergence. Results indicate that the topical distribution of French drama changed profoundly after the French Revolution, particularly between 1789 and 1850. Bourgeois themes emerged among the most prevalent topics since the late 18th century. To assess the coevolution of drama and economic growth, I plot the yearly prevalence of topics alongside French GDP between 1700-1900, and discuss these changes in light of the political and economic changes prompted by the French Revolution and the industrialization of the country.","source":"arXiv","year":2026,"language":"en","subjects":["cs.CL"],"url":"https://arxiv.org/abs/2602.00588","pdf_url":"https://arxiv.org/pdf/2602.00588","is_open_access":true,"published_at":"2026-01-31T08:10:01Z","score":70},{"id":"arxiv_2602.14960","title":"DRAMA: Domain Retrieval using Adaptive Module Allocation","authors":[{"name":"Pranav Kasela"},{"name":"Marco Braga"},{"name":"Ophir Frieder"},{"name":"Nazli Goharian"},{"name":"Gabriella Pasi"},{"name":"Raffaele Perego"}],"abstract":"Neural models are increasingly used in Web-scale Information Retrieval (IR). However, relying on these models introduces substantial computational and energy requirements, leading to increasing attention toward their environmental cost and the sustainability of large-scale deployments. While neural IR models deliver high retrieval effectiveness, their scalability is constrained in multi-domain scenarios, where training and maintaining domain-specific models is inefficient and achieving robust cross-domain generalisation within a unified model remains difficult. This paper introduces DRAMA (Domain Retrieval using Adaptive Module Allocation), an energy- and parameter-efficient framework designed to reduce the environmental footprint of neural retrieval. DRAMA integrates domain-specific adapter modules with a dynamic gating mechanism that selects the most relevant domain knowledge for each query. New domains can be added efficiently through lightweight adapter training, avoiding full model retraining. We evaluate DRAMA on multiple Web retrieval benchmarks covering different domains. Our extensive evaluation shows that DRAMA achieves comparable effectiveness to domain-specific models while using only a fraction of their parameters and computational resources. These findings show that energy-aware model design can significantly improve scalability and sustainability in neural IR.","source":"arXiv","year":2026,"language":"en","subjects":["cs.IR"],"url":"https://arxiv.org/abs/2602.14960","pdf_url":"https://arxiv.org/pdf/2602.14960","is_open_access":true,"published_at":"2026-02-16T17:38:24Z","score":70},{"id":"arxiv_2603.23816","title":"Aesthetics of Robot-Mediated Applied Drama: A Case Study on REMind","authors":[{"name":"Elaheh Sanoubari"},{"name":"Alicia Pan"},{"name":"Keith Rebello"},{"name":"Neil Fernandes"},{"name":"Andrew Houston"},{"name":"Kerstin Dautenhahn"}],"abstract":"Social robots are increasingly used in education, but most applications cast them as tutors offering explanation-based instruction. We explore an alternative: Robot-Mediated Applied Drama (RMAD), in which robots function as life-like puppets in interactive dramatic experiences designed to support reflection and social-emotional learning. This paper presents REMind, an anti-bullying robot role-play game that helps children rehearse bystander intervention and peer support. We focus on a central design challenge in RMAD: how to make robot drama emotionally and aesthetically engaging despite the limited expressive capacities of current robotic platforms. Through the development of REMind, we show how performing arts expertise informed this process, and argue that the aesthetics of robot drama arise from the coordinated design of the wider experience, not from robot expressivity alone.","source":"arXiv","year":2026,"language":"en","subjects":["cs.HC","cs.RO"],"url":"https://arxiv.org/abs/2603.23816","pdf_url":"https://arxiv.org/pdf/2603.23816","is_open_access":true,"published_at":"2026-03-25T00:58:01Z","score":70},{"id":"ss_68b2b0cc6ce32bac5454a7a5da59e6027978eadf","title":"DRAMA: An Efficient End-to-end Motion Planner for Autonomous Driving with Mamba","authors":[{"name":"Chengran Yuan"},{"name":"Zhanqi Zhang"},{"name":"Jiawei Sun"},{"name":"Shuo Sun"},{"name":"Zefan Huang"},{"name":"Christina Dao Wen Lee"},{"name":"Dongen Li"},{"name":"Yuhang Han"},{"name":"Anthony Wong"},{"name":"K. P. Tee"},{"name":"Marcelo H. Ang"}],"abstract":"Motion planning is a challenging task to generate safe and feasible trajectories in highly dynamic and complex environments, forming a core capability for autonomous vehicles. In this paper, we propose DRAMA, the first Mamba-based end-to-end motion planner for autonomous vehicles. DRAMA fuses camera, LiDAR Bird's Eye View images in the feature space, as well as ego status information, to generate a series of future ego trajectories. Unlike traditional transformer-based methods with quadratic attention complexity for sequence length, DRAMA is able to achieve a less computationally intensive attention complexity, demonstrating potential to deal with increasingly complex scenarios. Leveraging our Mamba fusion module, DRAMA efficiently and effectively fuses the features of the camera and LiDAR modalities. In addition, we introduce a Mamba-Transformer decoder that enhances the overall planning performance. This module is universally adaptable to any Transformer-based model, especially for tasks with long sequence inputs. We further introduce a novel feature state dropout which improves the planner's robustness without increasing training and inference times. Extensive experimental results show that DRAMA achieves higher accuracy on the NAVSIM dataset compared to the baseline Transfuser, with fewer parameters and lower computational costs.","source":"Semantic Scholar","year":2024,"language":"en","subjects":["Computer Science"],"doi":"10.48550/arXiv.2408.03601","url":"https://www.semanticscholar.org/paper/68b2b0cc6ce32bac5454a7a5da59e6027978eadf","is_open_access":true,"citations":59,"published_at":"","score":69.77000000000001},{"id":"ss_6deecd82876105225915342e5c80d5cd275139aa","title":"From Role-Play to Drama-Interaction: An LLM Solution","authors":[{"name":"Weiqi Wu"},{"name":"Hongqiu Wu"},{"name":"Lai Jiang"},{"name":"Xing-Chen Liu"},{"name":"Jiale Hong"},{"name":"Haizhen Zhao"},{"name":"Min Zhang"}],"abstract":"Drama is a form of storytelling inspired by human creativity, proceeding with a predefined storyline, carrying emotions and thoughts. This paper introduces \\emph{LLM-based interactive drama}, which endows traditional drama with an unprecedented immersion, where a person is allowed to walk into it and interact with the characters and scenes. We define this new artistic genre by 6 essential elements-plot, character, thought, diction, spectacle and interaction-and study the entire pipeline to forge a backbone \\emph{drama LLM} to drive the playing process, which is challenged by limited drama resources, uncontrollable narrative development, and complicated instruction following. We propose \\emph{Narrative Chain} to offer finer control over the narrative progression during interaction with players; \\emph{Auto-Drama} to synthesize drama scripts given arbitrary stories; \\emph{Sparse Instruction Tuning} to allow the model to follow sophisticated instructions. We manually craft 3 scripts, \\emph{Detective Conan}, \\emph{Harry Potter}, \\emph{Romeo and Juliet}, and design a 5-dimension principle to evaluate the drama LLM comprehensively.","source":"Semantic Scholar","year":2024,"language":"en","subjects":["Computer Science"],"doi":"10.48550/arXiv.2405.14231","url":"https://www.semanticscholar.org/paper/6deecd82876105225915342e5c80d5cd275139aa","is_open_access":true,"citations":52,"published_at":"","score":69.56},{"id":"ss_46739b53eb1422ecffe273c489174274800a5010","title":"The power of creative drama: integrating playful learning approaches in teacher education","authors":[{"name":"Tugce B. Arda Tuncdemir"}],"abstract":"ABSTRACT This research focuses on the use of creative drama as a tool to create an engaging and positive learning environment that improves social relationships and helps knowledge acquisition. The study explores preservice teachers’ comprehension, teaching methods, professional development experiences, and attitudes toward play and creative drama. Throughout 15 weeks, twelve preservice teachers participated in the Creative Drama Module. The data sources included interviews, weekly reflections on the drama module, teaching practices, the researcher's journal, and documents. The results indicate that the Module enhances preservice teachers’ confidence, abilities, and expertise in incorporating creative drama activities into their lessons.","source":"Semantic Scholar","year":2025,"language":"en","subjects":null,"doi":"10.1080/13569783.2025.2457745","url":"https://www.semanticscholar.org/paper/46739b53eb1422ecffe273c489174274800a5010","pdf_url":"https://doi.org/10.1080/13569783.2025.2457745","is_open_access":true,"citations":14,"published_at":"","score":69.42},{"id":"ss_d07485497d9e603817d1198bf559a42402821b0a","title":"IBSEN: Director-Actor Agent Collaboration for Controllable and Interactive Drama Script Generation","authors":[{"name":"Senyu Han"},{"name":"Lu Chen"},{"name":"Li-min Lin"},{"name":"Zhen Xu"},{"name":"Kai Yu"}],"abstract":"Large language models have demonstrated their capabilities in storyline creation and human-like character role-playing. Current language model agents mainly focus on reasonable behaviors from the level of individuals, and their behaviors might be hard to constraint on the level of the whole storyline. In this paper we introduce IBSEN, a director-actor coordinate agent framework that generates drama scripts and makes the plot played by agents more controllable. The director agent writes plot outlines that the user desires to see, instructs the actor agents to role-play their characters, and reschedules the plot when human players participate in the scenario to ensure the plot is progressing towards the objective. To evaluate the framework, we create a novel drama plot that involves several actor agents and check the interactions between them under the instruction of the director agent. Evaluation results show that our framework could generate complete, diverse drama scripts from only a rough outline of plot objectives, meanwhile maintaining the characteristics of characters in the drama. Our codes and prompts are available at https://github.com/OpenDFM/ibsen.","source":"Semantic Scholar","year":2024,"language":"en","subjects":["Computer Science"],"doi":"10.48550/arXiv.2407.01093","url":"https://www.semanticscholar.org/paper/d07485497d9e603817d1198bf559a42402821b0a","is_open_access":true,"citations":36,"published_at":"","score":69.08},{"id":"arxiv_2506.17590","title":"DRAMA-X: A Fine-grained Intent Prediction and Risk Reasoning Benchmark For Driving","authors":[{"name":"Mihir Godbole"},{"name":"Xiangbo Gao"},{"name":"Zhengzhong Tu"}],"abstract":"Understanding the short-term motion of vulnerable road users (VRUs) like pedestrians and cyclists is critical for safe autonomous driving, especially in urban scenarios with ambiguous or high-risk behaviors. While vision-language models (VLMs) have enabled open-vocabulary perception, their utility for fine-grained intent reasoning remains underexplored. Notably, no existing benchmark evaluates multi-class intent prediction in safety-critical situations, To address this gap, we introduce DRAMA-X, a fine-grained benchmark constructed from the DRAMA dataset via an automated annotation pipeline. DRAMA-X contains 5,686 accident-prone frames labeled with object bounding boxes, a nine-class directional intent taxonomy, binary risk scores, expert-generated action suggestions for the ego vehicle, and descriptive motion summaries. These annotations enable a structured evaluation of four interrelated tasks central to autonomous decision-making: object detection, intent prediction, risk assessment, and action suggestion. As a reference baseline, we propose SGG-Intent, a lightweight, training-free framework that mirrors the ego vehicle's reasoning pipeline. It sequentially generates a scene graph from visual input using VLM-backed detectors, infers intent, assesses risk, and recommends an action using a compositional reasoning stage powered by a large language model. We evaluate a range of recent VLMs, comparing performance across all four DRAMA-X tasks. Our experiments demonstrate that scene-graph-based reasoning enhances intent prediction and risk assessment, especially when contextual cues are explicitly modeled.","source":"arXiv","year":2025,"language":"en","subjects":["cs.CV","cs.AI","cs.RO"],"url":"https://arxiv.org/abs/2506.17590","pdf_url":"https://arxiv.org/pdf/2506.17590","is_open_access":true,"published_at":"2025-06-21T05:01:42Z","score":69},{"id":"arxiv_2504.20630","title":"ISDrama: Immersive Spatial Drama Generation through Multimodal Prompting","authors":[{"name":"Yu Zhang"},{"name":"Wenxiang Guo"},{"name":"Changhao Pan"},{"name":"Zhiyuan Zhu"},{"name":"Tao Jin"},{"name":"Zhou Zhao"}],"abstract":"Multimodal immersive spatial drama generation focuses on creating continuous multi-speaker binaural speech with dramatic prosody based on multimodal prompts, with potential applications in AR, VR, and others. This task requires simultaneous modeling of spatial information and dramatic prosody based on multimodal inputs, with high data collection costs. To the best of our knowledge, our work is the first attempt to address these challenges. We construct MRSDrama, the first multimodal recorded spatial drama dataset, containing binaural drama audios, scripts, videos, geometric poses, and textual prompts. Then, we propose ISDrama, the first immersive spatial drama generation model through multimodal prompting. ISDrama comprises these primary components: 1) Multimodal Pose Encoder, based on contrastive learning, considering the Doppler effect caused by moving speakers to extract unified pose information from multimodal prompts. 2) Immersive Drama Transformer, a flow-based mamba-transformer model that generates high-quality drama, incorporating Drama-MOE to select proper experts for enhanced prosody and pose control. We also design a context-consistent classifier-free guidance strategy to coherently generate complete drama. Experimental results show that ISDrama outperforms baseline models on objective and subjective metrics. The demos are available at https://aaronz345.github.io/ISDramaDemo. We provide the dataset and the evaluation code at https://huggingface.co/datasets/AaronZ345/MRSDrama and https://github.com/AaronZ345/ISDrama.","source":"arXiv","year":2025,"language":"en","subjects":["eess.AS","cs.MM","cs.SD"],"doi":"10.1145/3746027.3755014","url":"https://arxiv.org/abs/2504.20630","pdf_url":"https://arxiv.org/pdf/2504.20630","is_open_access":true,"published_at":"2025-04-29T10:56:44Z","score":69},{"id":"arxiv_2510.27238","title":"DRAMA: Unifying Data Retrieval and Analysis for Open-Domain Analytic Queries","authors":[{"name":"Chuxuan Hu"},{"name":"Maxwell Yang"},{"name":"James Weiland"},{"name":"Yeji Lim"},{"name":"Suhas Palawala"},{"name":"Daniel Kang"}],"abstract":"Manually conducting real-world data analyses is labor-intensive and inefficient. Despite numerous attempts to automate data science workflows, none of the existing paradigms or systems fully demonstrate all three key capabilities required to support them effectively: (1) open-domain data collection, (2) structured data transformation, and (3) analytic reasoning.   To overcome these limitations, we propose DRAMA, an end-to-end paradigm that answers users' analytic queries in natural language on large-scale open-domain data. DRAMA unifies data collection, transformation, and analysis as a single pipeline. To quantitatively evaluate system performance on tasks representative of DRAMA, we construct a benchmark, DRAMA-Bench, consisting of two categories of tasks: claim verification and question answering, each comprising 100 instances. These tasks are derived from real-world applications that have gained significant public attention and require the retrieval and analysis of open-domain data. We develop DRAMA-Bot, a multi-agent system designed following DRAMA. It comprises a data retriever that collects and transforms data by coordinating the execution of sub-agents, and a data analyzer that performs structured reasoning over the retrieved data. We evaluate DRAMA-Bot on DRAMA-Bench together with five state-of-the-art baseline agents. DRAMA-Bot achieves 86.5% task accuracy at a cost of $0.05, outperforming all baselines with up to 6.9 times the accuracy and less than 1/6 of the cost. DRAMA is publicly available at https://github.com/uiuc-kang-lab/drama.","source":"arXiv","year":2025,"language":"en","subjects":["cs.DB","cs.AI","cs.CL","cs.IR"],"doi":"10.1145/3769781","url":"https://arxiv.org/abs/2510.27238","pdf_url":"https://arxiv.org/pdf/2510.27238","is_open_access":true,"published_at":"2025-10-31T07:00:21Z","score":69},{"id":"arxiv_2509.16713","title":"OPEN-THEATRE: An Open-Source Toolkit for LLM-based Interactive Drama","authors":[{"name":"Tianyang Xu"},{"name":"Hongqiu Wu"},{"name":"Weiqi Wu"},{"name":"Hai Zhao"}],"abstract":"LLM-based Interactive Drama introduces a novel dialogue scenario in which the player immerses into a character and engages in a dramatic story by interacting with LLM agents. Despite the fact that this emerging area holds significant promise, it remains largely underexplored due to the lack of a well-designed playground to develop a complete drama. This makes a significant barrier for researchers to replicate, extend, and study such systems. Hence, we present Open-Theatre, the first open-source toolkit for experiencing and customizing LLM-based interactive drama. It refines prior work with an efficient multi-agent architecture and a hierarchical retrieval-based memory system, designed to enhance narrative coherence and realistic long-term behavior in complex interactions. In addition, we provide a highly configurable pipeline, making it easy for researchers to develop and optimize new approaches.","source":"arXiv","year":2025,"language":"en","subjects":["cs.CL"],"url":"https://arxiv.org/abs/2509.16713","pdf_url":"https://arxiv.org/pdf/2509.16713","is_open_access":true,"published_at":"2025-09-20T14:53:14Z","score":69},{"id":"arxiv_2502.17878","title":"Towards Enhanced Immersion and Agency for LLM-based Interactive Drama","authors":[{"name":"Hongqiu Wu"},{"name":"Weiqi Wu"},{"name":"Tianyang Xu"},{"name":"Jiameng Zhang"},{"name":"Hai Zhao"}],"abstract":"LLM-based Interactive Drama is a novel AI-based dialogue scenario, where the user (i.e. the player) plays the role of a character in the story, has conversations with characters played by LLM agents, and experiences an unfolding story. This paper begins with understanding interactive drama from two aspects: Immersion, the player's feeling of being present in the story, and Agency, the player's ability to influence the story world. Both are crucial to creating an enjoyable interactive experience, while they have been underexplored in previous work. To enhance these two aspects, we first propose Playwriting-guided Generation, a novel method that helps LLMs craft dramatic stories with substantially improved structures and narrative quality. Additionally, we introduce Plot-based Reflection for LLM agents to refine their reactions to align with the player's intentions. Our evaluation relies on human judgment to assess the gains of our methods in terms of immersion and agency.","source":"arXiv","year":2025,"language":"en","subjects":["cs.CL"],"url":"https://arxiv.org/abs/2502.17878","pdf_url":"https://arxiv.org/pdf/2502.17878","is_open_access":true,"published_at":"2025-02-25T06:06:16Z","score":69},{"id":"doaj_10.3366/film.2025.0321","title":"Finding Sunbeams in the Darkness: Michel Serres's Analogical Thinking and the Ethics of Listening in The Zone of Interest","authors":[{"name":"Kevin Hunt"}],"abstract":"This article addresses the fundamental concept underpinning Jonathan Glazer's The Zone of Interest, which recognizes selective empathy and extraordinary empathy dissonance within our contemporary cultures as a continuum, not a moment. The article uses Michel Serres's philosophical process to provide an ontological and epistemological framework within which The Zone of Interest can be understood analogously as a warning about darkness enveloping the world. Glazer has emphasized the axiom of his film is focusing upon the present. The Zone of Interest asks questions about humanity's contemporary cultural sensibilities, which determine how societies engage with diversity, difference, and the multiplicities of perspective that are an inescapable part of the global geopolitical landscape. Serres's process is inherently analogical, recognizing patterns of knowing and being that recur isomorphically across space and time. This article brings together the immersive sensibility mediated through the screen – situating The Zone of Interest as a cinematic experience that elevates sound over vision – with Serres's assimilation of Lucretian atomism, which links materialism and ethics; the importance of noise as a source of knowledge within Serresian thought; and a topological approach to time and space, which shapes the analogical, qualitatively relational, processes characteristic of Serres's philosophy.","source":"DOAJ","year":2025,"language":"","subjects":["Motion pictures","Philosophy (General)"],"doi":"10.3366/film.2025.0321","url":"https://www.euppublishing.com/doi/10.3366/film.2025.0321","is_open_access":true,"published_at":"","score":69},{"id":"doaj_10.56620/2587-9731-2025-2-134-150","title":"Traditional Regional Features in Xiangtong Xi Musical Drama","authors":[{"name":"Jianfu Li"}],"abstract":"\n    This article presents a discussion about Xiangtong Xi (香童戏), a traditional musical theatrical form associated with the Baoshan area of China’s Yunnan province. Xiangtong Xi drama originated from the folk religious and mystical rites of the southwestern regions of China. It organically combines elements such as singing, recitation, acting and martial arts techniques that are characteristic of the musical culture of the region. This genre has its own cult music and traditional performance style. At the same time, supporting and preserving the traditions of their art, Xiangtong Xi artists throughout the history of its existence have developed and continue to develop Xiangtong Xi music by studying the singing melodies and musical styles of other cultures, musical genres and movements and introducing their elements into their performances. The basis for such borrowings is primarily local folk music and songs, as well as other traditional musical genres of the region.\nKeywords: Xiangtong Xi, musical drama, ritual music, religious music, Prince’s Chant, Even Chant, Universal Chant, Chant of the Black God, plague god’s chant, percussion instruments\nFor citation: Li Jianfu (2025). Traditional Regional Features in Xiangtong Xi Musical Drama. Contemporary Musicology, 9(2), 134–150. https://doi.org/10.56620/2587-9731-2025-2-134-150","source":"DOAJ","year":2025,"language":"","subjects":["Music"],"doi":"10.56620/2587-9731-2025-2-134-150","url":"https://gnesinsjournal.ru/index.php/CM/article/view/197","is_open_access":true,"published_at":"","score":69},{"id":"doaj_10.33178/scenario.19.2.7","title":"A Note on (Dis)Appearances","authors":[{"name":"Silja Weber"}],"abstract":"\nThis is not a study, but a research note on academic writing practices in our field, whose purpose it is to serve as a foundation for discussion. It provides a brief introduction into researcher reflexivity, my own positioning towards the topic, and a numerical thematic overview of authorial presence (pronouns, third-person terms, and their semantic functions) in data-based research articles published in the Scenario journal over the last ten years. I do not draw conclusions, but from the angle of researcher reflexivity, I submit questions with respect to clarity of premises and ethics, for possible consideration by future authors in our field.  \n","source":"DOAJ","year":2025,"language":"","subjects":["Special aspects of education","Drama"],"doi":"10.33178/scenario.19.2.7","url":"https://aigne.ucc.ie/index.php/scenario/article/view/4328","is_open_access":true,"published_at":"","score":69},{"id":"doaj_10.14746/i.2025.39.48.9","title":"Dysonans ludonarracyjny w światocentrycznych grach wideo","authors":[{"name":"Michał Mróz"}],"abstract":"\nThe author explores the issue of “ludonarrative dissonance”, a term developed by the game designer C. Hocking in his critique of the game BioShock. The author explains Hocking’s arguments and then expands on the term, disagreeing with Hocking. In the case of BioShock, the author interprets the dissonance not as a design flaw but as a deliberate narrative strategy that momentarily distances the player from the game’s fiction to emphasize its metanarrative dimension. The author argues that ludonarrative dissonance is itself part of videogame poetics, thus echoing the works of F. Seraphine and P. Grabarczyk \u0026 B.W. Kampmann. The author then examines how ludonarrative dissonance may appear in vast, nonlinear open-world cRPGs. An analysis of examples from The Elder Scrolls: Skyrim, Fallout 3, and Fallout 4 reveals various instances of unintended dissonance. Finally, the author compares these games to Fallout: New Vegas, presenting it as an example of harmonizing the narrative – the main motifs and story – with the narrativity of gameplay, including rules, mechanics, and vast player agency.\n","source":"DOAJ","year":2025,"language":"","subjects":["Photography","Dramatic representation. The theater"],"doi":"10.14746/i.2025.39.48.9","url":"https://pressto.amu.edu.pl/index.php/i/article/view/51255","is_open_access":true,"published_at":"","score":69},{"id":"arxiv_2405.14231","title":"From Role-Play to Drama-Interaction: An LLM Solution","authors":[{"name":"Weiqi Wu"},{"name":"Hongqiu Wu"},{"name":"Lai Jiang"},{"name":"Xingyuan Liu"},{"name":"Jiale Hong"},{"name":"Hai Zhao"},{"name":"Min Zhang"}],"abstract":"Drama is a form of storytelling inspired by human creativity, proceeding with a predefined storyline, carrying emotions and thoughts. This paper introduces \\emph{LLM-based interactive drama}, which endows traditional drama with an unprecedented immersion, where a person is allowed to walk into it and interact with the characters and scenes. We define this new artistic genre by 6 essential elements-plot, character, thought, diction, spectacle and interaction-and study the entire pipeline to forge a backbone \\emph{drama LLM} to drive the playing process, which is challenged by limited drama resources, uncontrollable narrative development, and complicated instruction following. We propose \\emph{Narrative Chain} to offer finer control over the narrative progression during interaction with players; \\emph{Auto-Drama} to synthesize drama scripts given arbitrary stories; \\emph{Sparse Instruction Tuning} to allow the model to follow sophisticated instructions. We manually craft 3 scripts, \\emph{Detective Conan}, \\emph{Harry Potter}, \\emph{Romeo and Juliet}, and design a 5-dimension principle to evaluate the drama LLM comprehensively.","source":"arXiv","year":2024,"language":"en","subjects":["cs.CL"],"url":"https://arxiv.org/abs/2405.14231","pdf_url":"https://arxiv.org/pdf/2405.14231","is_open_access":true,"published_at":"2024-05-23T07:03:56Z","score":68},{"id":"arxiv_2408.03601","title":"DRAMA: An Efficient End-to-end Motion Planner for Autonomous Driving with Mamba","authors":[{"name":"Chengran Yuan"},{"name":"Zhanqi Zhang"},{"name":"Jiawei Sun"},{"name":"Shuo Sun"},{"name":"Zefan Huang"},{"name":"Christina Dao Wen Lee"},{"name":"Dongen Li"},{"name":"Yuhang Han"},{"name":"Anthony Wong"},{"name":"Keng Peng Tee"},{"name":"Marcelo H. Ang"}],"abstract":"Motion planning is a challenging task to generate safe and feasible trajectories in highly dynamic and complex environments, forming a core capability for autonomous vehicles. In this paper, we propose DRAMA, the first Mamba-based end-to-end motion planner for autonomous vehicles. DRAMA fuses camera, LiDAR Bird's Eye View images in the feature space, as well as ego status information, to generate a series of future ego trajectories. Unlike traditional transformer-based methods with quadratic attention complexity for sequence length, DRAMA is able to achieve a less computationally intensive attention complexity, demonstrating potential to deal with increasingly complex scenarios. Leveraging our Mamba fusion module, DRAMA efficiently and effectively fuses the features of the camera and LiDAR modalities. In addition, we introduce a Mamba-Transformer decoder that enhances the overall planning performance. This module is universally adaptable to any Transformer-based model, especially for tasks with long sequence inputs. We further introduce a novel feature state dropout which improves the planner's robustness without increasing training and inference times. Extensive experimental results show that DRAMA achieves higher accuracy on the NAVSIM dataset compared to the baseline Transfuser, with fewer parameters and lower computational costs.","source":"arXiv","year":2024,"language":"en","subjects":["cs.RO"],"url":"https://arxiv.org/abs/2408.03601","pdf_url":"https://arxiv.org/pdf/2408.03601","is_open_access":true,"published_at":"2024-08-07T07:41:01Z","score":68}],"total":256990,"page":1,"page_size":20,"sources":["CrossRef","arXiv","DOAJ","Semantic Scholar"],"query":"Drama"}