Mikel Garcia de Andoin, Alberto Bottarelli, Sebastian Schmitt, Philipp Hauke, Mikel Sanz,
" Formulation of the Electric Vehicle Charging and Routing Problem for a Hybrid Quantum-Classical Search Space Reduction Heuristic",
International Conference on Intelligent Transportation Systems, 2024.
Abstract
Combinatorial optimization problems have attracted much interest in the quantum computing community in the recent years as a potential testbed to showcase quantum advantage. In this paper, we show how to exploit multilevel carriers of quantum information -- qudits -- for the construction of algorithms for constrained quantum optimization. These systems have been recently introduced in the context of quantum optimization and they allow us to treat...
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Ahmed Sadik, Sebastian Brulin, Markus Olhofer,
"CODING BY DESIGN: GPT-4 EMPOWERS AGILE MODEL DRIVEN DEVELOPMENT",
MODELSWARD 2024 - The 12th International Conference on Model-Based Software and Systems Engineering, 2024.
Abstract
Generating code from a natural language using Large Language Models (LLMs) such as ChatGPT, seems groundbreaking. Yet, with more extensive use, it's evident that this approach has its own limitations. The inherent ambiguity of natural language proposes challenges to auto-generate synergistically structured artifacts that can be deployed. Model Driven Development (MDD) is therefore being highlighted in this research as a proper approach to overcom...
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"CoPal: Planning Robot Actions using Large Language Models",
Github website, 2024.
Abstract
Recent advances in the field of pretrained Large Language Models (LLM) made commonsense knowledge available "out of the box" for a vast range of scenarios including content generation, customer service, and voice assistants. The release of GPT-3.5 (known as ChatGPT) opened prospectives for building highly contextualizable conversational agents, capable to hold a dialog and reflect about various situations as well as on behalf of different social ...
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Linda Spaa, van der,
"LEARNING HUMAN PREFERENCES FOR PHYSICAL HUMAN-ROBOT COOPERATION",
TU Delft, 2024.
Abstract
PHYSICAL human-robot cooperation (pHRC) has the potential to combine human and
robot strengths in a team that can achieve more than a human and a robot working
on the task separately. However, how much of the potential can be realized depends on
the quality of cooperation, in which awareness of the partner’s intention and preferences
plays an important role. Preferences tend to be highly personal, and additionally de-
pend on the cooperati...
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Hifza Javed, Nina Moorman, Thomas Weisswange, Nawid Jamali,
"Dyadic Interactions and Interpersonal Perception: An Exploration of Behavioral Cues for Technology-Assisted Mediation",
15th International Conference on Applied Human Factors and Ergonomics (AHFE 2024), 2024.
Abstract
Mediators aim to shape group dynamics in various ways, such as improving trust and cohesion, balancing participation, and promoting constructive conflict resolution. Technological systems used to mediate human-human interactions must be able to continuously assess the state of the interaction and generate appropriate actions. To this end, an understanding of the collective affective state of the group is needed in order to produce meaningful acti...
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Zhenpeng Shi, Nikolay Matyunin, Kalman Graffi, David Starobinski,
"Uncovering CWE-CVE-CPE Relations with Threat Knowledge Graphs",
ACM Transactions on Privacy and Security (TOPS), 2024.
Abstract
Security assessment relies on public information on products, vulnerabilities and weaknesses. So far, databases in these categories have rarely been analyzed in combination. Yet, doing so could help predict unreported vulnerabilities and identify common threat patterns. In this paper, we propose a methodology for producing and optimizing a knowledge graph that aggregates knowledge from common threat databases (CPE, CVE, and CWE). We apply the thr...
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Jihong Zhu, Michael Gienger, Giovanni Franzese, Jens Kober,
"Do You Need a Hand? – An Interactive Robotic
Dressing Assistance Scheme",
IEEE Transactions on Robotics, 2024.
Abstract
Developing physically assistive robots capable of
dressing assistance has the potential to significantly improve
the lives of the elderly and disabled population. However, most
robotics dressing strategies used a single robot only, which greatly
limited the performance of the dressing assistance. In fact, both
arms are usually required when healthcare professionals perform
the task. Inspired by them, we propose a bimanual cooperative
schem...
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Michael Gienger,
"Explainable human-robot interaction & LLM-based robot planning",
TU Delft, 2024.
Abstract
This invited lab talk covers research conducted in the Smile project related to the AR-supported learning and interaction framework, as well as of the recent LLM-based planning concepts....
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Chao Wang,
"Large Language Models for Multi-Modal Human-Robot Interaction",
LMU Winterschool , 2024.
Abstract
I will report our latest achievement based on the CHI LBW paper we submitted: https://arxiv.org/abs/2401.15174
A paper website is also created for better spreading (please see the "Supplementary Material").
Besides, I will show a real time demo of our system with camera, microphone and object with marker. The robot's behavior will be shown in RCS simulator and "inner thought" GUI.
Student can also send me system prompt, then we can tune the r...
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Felix Ocker and Julian Eggert,
"Accessing Knowledge using Retrieval Augmented Generation",
Honda Technical Forum 2023, 2023.
Abstract
Language Models (LMs) provide an intuitive interface for humans via Natural Language. However, they hallucinate very convincingly and do not have access to proprietary data. This presentation gives insights into Retrieval Augmented Generation (RAG) as a technology for realizing the LM experience for large amounts of proprietary data. We present the underlying architecture, results achieved with an HRI-EU internal prototype for the TikiWiki, the "...
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