by jsendak | Apr 25, 2025 | Computer Science
arXiv:2504.16405v1 Announce Type: new
Abstract: The furnishing of multi-modal large language models (MLLMs) has led to the emergence of numerous benchmark studies, particularly those evaluating their perception and understanding capabilities.
Among these, understanding image-evoked emotions aims to enhance MLLMs’ empathy, with significant applications such as human-machine interaction and advertising recommendations. However, current evaluations of this MLLM capability remain coarse-grained, and a systematic and comprehensive assessment is still lacking.
To this end, we introduce EEmo-Bench, a novel benchmark dedicated to the analysis of the evoked emotions in images across diverse content categories.
Our core contributions include:
1) Regarding the diversity of the evoked emotions, we adopt an emotion ranking strategy and employ the Valence-Arousal-Dominance (VAD) as emotional attributes for emotional assessment. In line with this methodology, 1,960 images are collected and manually annotated.
2) We design four tasks to evaluate MLLMs’ ability to capture the evoked emotions by single images and their associated attributes: Perception, Ranking, Description, and Assessment. Additionally, image-pairwise analysis is introduced to investigate the model’s proficiency in performing joint and comparative analysis.
In total, we collect 6,773 question-answer pairs and perform a thorough assessment on 19 commonly-used MLLMs.
The results indicate that while some proprietary and large-scale open-source MLLMs achieve promising overall performance, the analytical capabilities in certain evaluation dimensions remain suboptimal.
Our EEmo-Bench paves the path for further research aimed at enhancing the comprehensive perceiving and understanding capabilities of MLLMs concerning image-evoked emotions, which is crucial for machine-centric emotion perception and understanding.
Enhancing Multi-Modal Large Language Models (MLLMs) with Image-Evoked Emotions
This article introduces the concept of image-evoked emotions and its relevance in enhancing the empathy of multi-modal large language models (MLLMs). MLLMs have gained significant attention in various domains, including human-machine interaction and advertising recommendations. However, the evaluation of MLLMs’ understanding of image-evoked emotions is currently limited and lacks a systematic and comprehensive assessment.
The Importance of Emotion in MLLMs
Emotion plays a crucial role in human communication and understanding, and the ability to perceive and understand emotions is highly desirable in MLLMs. By incorporating image-evoked emotions into MLLMs, these models can better empathize with users and provide more tailored responses and recommendations.
The EEmo-Bench Benchmark
To address the limitations in evaluating MLLMs’ understanding of image-evoked emotions, the authors introduce EEmo-Bench, a novel benchmark specifically designed for this purpose. EEmo-Bench focuses on the analysis of the evoked emotions in images across diverse content categories.
The benchmark includes the following core contributions:
- Diversity of evoked emotions: To assess emotional attributes, the authors adopt an emotion ranking strategy and utilize the Valence-Arousal-Dominance (VAD) model. A dataset of 1,960 images is collected and manually annotated for emotional assessment.
- Four evaluation tasks: Four tasks are designed to evaluate MLLMs’ ability to capture evoked emotions and their associated attributes: Perception, Ranking, Description, and Assessment. Additionally, image-pairwise analysis is introduced for joint and comparative analysis.
- Thorough assessment of MLLMs: A comprehensive evaluation is conducted on 19 commonly-used MLLMs, with a collection of 6,773 question-answer pairs. The results highlight the performance of different models in various evaluation dimensions.
Insights and Future Directions
The results of the EEmo-Bench benchmark reveal that while some proprietary and large-scale open-source MLLMs show promising overall performance, there are still areas in which these models’ analytical capabilities can be improved. This highlights the need for further research and innovation to enhance MLLMs’ comprehension and perception of image-evoked emotions.
The concepts discussed in this article are highly relevant to the wider field of multimedia information systems, as they bridge the gap between textual data and visual content analysis. Incorporating image-evoked emotions into MLLMs opens up new avenues for research in areas such as virtual reality, augmented reality, and artificial reality.
The multi-disciplinary nature of the concepts presented here underscores the importance of collaboration between researchers from fields such as computer vision, natural language processing, and psychology. By combining expertise from these diverse domains, we can develop more sophisticated MLLMs that truly understand and respond to the emotions evoked by visual stimuli.
In conclusion, the EEmo-Bench benchmark serves as a stepping stone for future research in enhancing the comprehension and perception capabilities of MLLMs in the context of image-evoked emotions. This research has significant implications for machine-centric emotion perception and understanding, with applications ranging from personalized user experiences to improved advertising recommendations.
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by jsendak | Apr 25, 2025 | AI
arXiv:2504.16115v1 Announce Type: new
Abstract: Fields offer a versatile approach for describing complex systems composed of interacting and dynamic components. In particular, some of these dynamical and stochastic systems may exhibit goal-directed behaviors aimed at achieving specific objectives, which we refer to as $textit{intelligent fields}$. However, due to their inherent complexity, it remains challenging to develop a formal theoretical description of such systems and to effectively translate these descriptions into practical applications. In this paper, we propose three fundamental principles — complete configuration, locality, and purposefulness — to establish a theoretical framework for understanding intelligent fields. Moreover, we explore methodologies for designing such fields from the perspective of artificial intelligence applications. This initial investigation aims to lay the groundwork for future theoretical developments and practical advances in understanding and harnessing the potential of such objective-driven dynamical stochastic fields.
Understanding Intelligent Fields: A Multi-disciplinary Approach
In the study of complex systems, fields provide a versatile framework for describing dynamic interactions. In this context, certain systems exhibit goal-directed behaviors with a specific objective in mind. These systems, known as intelligent fields, pose a challenge when it comes to developing a formal theoretical description and translating it into practical applications. This paper explores three fundamental principles – complete configuration, locality, and purposefulness – to establish a theoretical framework for understanding intelligent fields, while also investigating methodologies for designing and applying such fields.
The Complexity of Intelligent Fields
Intelligent fields are inherently complex due to the numerous components and interactions involved. Describing their behavior and understanding their dynamics requires a multi-disciplinary approach. The study of intelligent fields incorporates concepts from fields such as systems theory, statistical physics, artificial intelligence, and even cognitive science.
Systems theory provides a foundation for analyzing the interplay between the individual components within an intelligent field and how they collectively contribute to the system’s behavior. Understanding the larger-scale emergent properties of the field requires concepts from statistical physics, which help model the stochastic nature of the system.
Artificial intelligence plays a critical role in designing and harnessing intelligent fields. Techniques from machine learning and optimization algorithms enable the field to adapt and learn from its environment, making it more efficient in achieving its objectives. Additionally, cognitive science offers insights into the underlying principles and processes that drive intelligent behavior, helping in the development of more accurate and realistic models of intelligent fields.
Fundamental Principles for Intelligent Fields
To establish a theoretical framework, this paper puts forth three fundamental principles for understanding intelligent fields: complete configuration, locality, and purposefulness.
Complete Configuration: Intelligent fields require a comprehensive definition of the system’s components, interactions, and environmental factors. Without a complete configuration, it becomes difficult to accurately model and analyze the behavior of the field.
Locality: The principle of locality emphasizes that intelligent fields operate based on local interactions and information. This means that each component of the field only has access to limited knowledge about its immediate surroundings. By focusing on local interactions, the complexity of the system can be reduced, enabling more efficient analysis and design.
Purposefulness: Intelligent fields are goal-directed systems, working towards achieving specific objectives. Understanding and incorporating the purposefulness of the field is crucial for its design and optimization. Techniques from artificial intelligence, such as reinforcement learning, can be employed to train the field to adapt and modify its behavior to achieve its objectives more effectively.
Designing Intelligent Fields
The methodologies for designing intelligent fields discussed in this paper revolve around the integration of artificial intelligence techniques. Machine learning algorithms can be employed to train the field based on collected data, enabling it to adapt its behavior over time. Optimization algorithms, on the other hand, help in fine-tuning the field’s parameters and configuration for optimal performance.
By combining insights from various disciplines, designing intelligent fields becomes a multi-disciplinary endeavor. Techniques from artificial intelligence, statistical physics, and systems theory can be utilized to create effective and efficient intelligent fields that exhibit goal-directed behaviors.
Future Directions
This initial investigation into intelligent fields establishes a theoretical foundation and highlights the multi-disciplinary nature of the field. Moving forward, further theoretical developments can build upon these principles and explore more advanced models of intelligent fields, incorporating insights from cognitive science and other related domains.
Practical advancements in understanding and harnessing the potential of intelligent fields also hold promise. Developing real-world applications that leverage intelligent fields can lead to significant improvements in areas such as autonomous systems, predictive modeling, and optimization.
Conclusion
The study of intelligent fields is an intersection of various disciplines, requiring a multi-disciplinary approach to comprehend their complexity. By establishing fundamental principles and exploring methodologies for designing and applying intelligent fields, this paper lays the groundwork for future theoretical developments and practical advancements. With further research, intelligent fields have the potential to revolutionize numerous domains, making them more efficient, adaptive, and capable of achieving specific objectives.
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by jsendak | Apr 25, 2025 | Art
On April 24, Remai Modern presents a powerful exhibition that shines a light on the rich and complex heritage of the Caribbean. Entitled “Voices from the Caribbean,” this exhibition is a testament to the deep connection between artists and the land that has shaped their identities.
Exploring Caribbean Identities
As we step into this exhibition, we embark on a journey that traverses the vibrant traditions, histories, and stories that have shaped the Caribbean. The voices of eight talented artists, each with familial and lived ties to the region, take center stage.
Through their works, these artists invite us to question our preconceptions and dig deeper into the cultural fabric of the Caribbean. We are faced with interconnected themes of identity, diaspora, colonialism, and resilience. The artists challenge us to reconsider our understanding of Caribbean identities and the complexities that come with it.
A Historical Perspective
The Caribbean, known for its breathtaking landscapes and cultural diversity, also bears the scars of a complex history. From the violent legacy of colonization, when countless indigenous communities were displaced and enslaved Africans were brought to the region, to the present-day influences of globalization, the Caribbean has undergone immense transformation.
The influences of these historical events on the artists’ works cannot be ignored. Their pieces are imbued with the struggles, triumphs, and ongoing negotiations of the Caribbean experience. Colonial narratives are disrupted, and new frameworks for understanding emerge, highlighting the resilience and agency of the Caribbean people.
A Contemporary Dialogue
While deeply rooted in history, “Voices from the Caribbean” also invites us to engage with the contemporary realities of the region. The artists confront issues such as environmental degradation, political unrest, and the impact of tourism on local cultures.
Through their artistic expressions, these artists act as contemporary griots, preserving and honoring the rich tapestry of Caribbean culture. Their works inspire dialogue, reflection, and a deeper appreciation for the vibrancy and diversity that define the Caribbean today.
Discover the Power of the Caribbean
Join us at Remai Modern as we celebrate the creativity and resilience of Caribbean artists. Through this exhibition, “Voices from the Caribbean,” we invite you to immerse yourself in the stories, histories, and identities that have shaped this dynamic and captivating region.
Prepare to be moved, challenged, and inspired by the nuanced expressions of these talented artists. Let their voices resonate within you, inviting you to explore the richness and complexity of the Caribbean.
On April 24, Remai Modern presents a new exhibition that gives primacy to the voices of eight artists who think deeply about the Caribbean and have familial and lived ties to the region.
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by jsendak | Apr 25, 2025 | Art
Thematic Preface:
Welcome to The Cynics Republic—Plac Defilad, a groundbreaking exhibition that brings together dematerialized artworks from the prestigious collections of the Museum of Modern Art in Warsaw and Kontakt Collection in Vienna. This unique showcase delves into the realm of intangible artistic expressions, including performances, protocols, films, and sound pieces, offering visitors a captivating experience that transcends physical boundaries.
Contextualizing Historical Significance:
Throughout history, the art world has taken varied forms, constantly evolving and challenging traditional understandings of artistic creation. Groundbreaking artistic movements such as Fluxus and Conceptual Art have paved the way for the exploration of immaterial and ephemeral artistic expressions. This exhibition embraces the legacy of these movements and showcases the significance of dematerialized artworks in contemporary art discourse.
Looking back, the revolutionary ideas of Fluxus artists such as Yoko Ono and Joseph Beuys challenged conventional notions of materiality and permanence in art. Their emphasis on concepts, actions, and experiences pushed the boundaries of artistic expression, echoing the spirit of this exhibition. Similarly, Conceptual Art of the 1960s and 1970s, with artists like Sol LeWitt and Joseph Kosuth, emphasized the primacy of ideas above material objects, laying the foundation for the dematerialized artworks we encounter today.
Exploring Contemporary Relevance:
In the digital age, where virtual reality and online experiences are increasingly embedded in our daily lives, the notion of dematerialization in art takes on heightened significance. Artists are embodying the intangible and delving into the immaterial realm, challenging traditional expectations of art as a tangible medium.
This exhibition not only reflects this contemporary exploration but also prompts us to question the very concept of materiality in an era where digital media and technology dominate our existence. By showcasing dematerialized artworks, The Cynics Republic—Plac Defilad raises thought-provoking questions about the transience of art, the role of the viewer, and the evolving nature of artistic expression.
Appreciating the Contributions:
It is with great pride and anticipation that the Museum of Modern Art in Warsaw and Kontakt Collection in Vienna present The Cynics Republic—Plac Defilad. This collaboration aims to curate an immersive exhibition that invites visitors to engage with unconventional art forms, challenge preconceived notions, and explore the boundless possibilities of artistic expression.
We invite you to embark on this journey into the world of dematerialized artworks, where ideas take center stage, and the intangible becomes tangible.
The Cynics Republic—Plac Defilad is an exhibition featuring dematerialized artworks (performances, protocols, films, sound pieces) from the collections of the Museum of Modern Art in Warsaw and Kontakt Collection in Vienna.
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by jsendak | Apr 25, 2025 | GR & QC Articles
arXiv:2504.16156v1 Announce Type: new
Abstract: We study a point scalar charge in circular orbit around a topological star, a regular, horizonless soliton emerging from dimensional compactification of Einstein-Maxwell theory in five dimensions, which could describe qualitative properties of microstate geometries for astrophysical black holes. This is the first step towards studying extreme mass-ratio inspirals around these objects. We show that when the particle probes the spacetime close to the object, the scalar-wave flux deviates significantly from the corresponding black hole case. Furthermore, as the topological star approaches the black-hole limit, the inspiral can resonantly excite its long-lived modes, resulting in sharp features in the emitted flux. Although such resonances are too narrow to produce detectable dephasing, we estimate that a year-long inspiral down to the innermost stable circular orbit could accumulate a significant dephasing for most configurations relative to the black hole case. While a full parameter-estimation analysis is needed, the generically large deviations are likely to be within the sensitivity reach of future space-based gravitational-wave detectors.
Future Roadmap: Challenges and Opportunities
Introduction
In this article, we examine the conclusions of a study that investigates a point scalar charge in circular orbit around a topological star. This star is a regular, horizonless soliton that emerges from the dimensional compactification of Einstein-Maxwell theory in five dimensions. The findings of this study have implications for understanding astrophysical black holes and the possibility of extreme mass-ratio inspirals (EMRIs) around them. In this roadmap, we outline potential challenges and opportunities that lie ahead in this field of research.
Challenges
- Resonant Excitations: One significant challenge identified in the study is the resonant excitation of long-lived modes in the topological star as it approaches the black hole limit. This resonance leads to sharp features in the emitted flux, which deviates significantly from the flux in a black hole case. Understanding the dynamics and behavior of these resonances will require further investigation.
- Dephasing Analysis: To fully quantify the impact of the resonances on the emitted flux, a comprehensive parameter-estimation analysis is needed. This analysis will help determine the extent of dephasing that occurs during an inspiral down to the innermost stable circular orbit. Conducting such an analysis is a challenging task that requires a detailed understanding of the underlying physics and computational techniques.
Opportunities
- Detectability: Despite the challenges, the study suggests that the deviations caused by the resonant excitation and dephasing are likely to be within the sensitivity reach of future space-based gravitational-wave detectors. This presents an exciting opportunity to observe and analyze these effects, potentially providing insights into the nature of microstate geometries for astrophysical black holes.
- Parameter Variation: Extending the study to explore a wide range of parameter configurations is an opportunity for future research. By varying different parameters, such as the mass and charge of the scalar particle, and the properties of the topological star, a more comprehensive understanding of the system’s behavior can be gained.
Conclusion
In conclusion, the study of a point scalar charge in circular orbit around a topological star has highlighted both challenges and opportunities for future research in the field of extreme mass-ratio inspirals around astrophysical black holes. Overcoming challenges such as understanding resonant excitations and conducting dephasing analysis will pave the way for further investigation. The potential to detect and analyze these effects using future space-based gravitational-wave detectors provides an exciting opportunity to deepen our understanding of black hole microstate geometries. Exploring a broader parameter space will also contribute to a more comprehensive understanding of the system’s behavior. The road ahead holds great potential for uncovering new insights into the nature of black holes in our universe.
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