109 citations
- Carnegie Mellon UniversityUS4 papers
- École Polytechnique Fédérale de LausanneCH2 papers
- ETH ZurichCH2 papers
- Tufts UniversityUS2 papers
- CEA Paris-SaclayFR1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- Centro Regional de Derechos Humanos y Justicia de Género, Corporación HumanasCL1 paper
- Changsha UniversityCN1 paper
- Château GombertFR1 paper
- Chemnitz University of TechnologyDE1 paper
- Colorado School of MinesUS1 paper
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR1 paper
6 papers · 1 filter
Effects of Auditory Information for People With Visual Impairments in Highly Automated Vehicles
Mark Colley, Tobias Aescht, Omid Rajabi +3
Automated vehicles promise to improve accessibility and access to personal mobility for everyone. However, their design and current research trends in visualizing relevant informat…
Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning
Bang Giang Le, Viet Cuong Ta
Cooperative multi-agent reinforcement learning assumes each agent shares the same reward function and can be trained effectively using the Trust Region framework of single-agent. I…
Meituan Merchant Business Diagnosis via Policy-Guided Dual-Process User Simulation
Ziyang Chen, Renbing Chen, Daowei Li +4
Simulating group-level user behavior enables scalable counterfactual evaluation of merchant strategies without costly online experiments. However, building a trustworthy simulator…
Let Me Introduce You: Stimulating Taste-Broadening Serendipity Through Song Introductions
Brett Binst, Ulysse Maes, Martijn C. Willemsen +1
Research on how people experience music emphasizes the importance of exploration and diversity in listening. However, music recommender systems struggle with facilitating explorati…
Towards Fluent Interaction with Cyber-Physical Architecture
Jesse T. Gonzalez, Neeta Khanuja, Michael Li +6
What happens when your walls begin to move? This paper explores the design of human-robot interaction for architectural-scale, shape-changing environments. We present findings from…
Safe Learning for Contact-Rich Robot Tasks: A Survey from Classical Learning-Based Methods to Safe Foundation Models
Heng Zhang, Rui Dai, Gokhan Solak +4
Contact-rich tasks pose significant challenges for robotic systems due to inherent uncertainty, complex dynamics, and the high risk of damage during interaction. Recent advances in…