Artifact removal routinely precedes the classification of electrodermal activity (EDA), on the assumption that a cleaner signal supports a better decision. We tested this assumption in a virtual-reality (VR) balance-disturbance task. A residual gating network was trained on a benchmark with expert-corrected EDA, frozen...
Haochen Chai, Qixu Zhu, Siyao Li et al.· 0 citations
This demo paper presents the conceptual foundations and the first steps towards implementation of a novel no-code solution for movement data analytics based on the open-source Python library MovingPandas and the open-source geographic information system QGIS. The resulting Trajectools plugin is available open-source at...
Egocentric bimanual hand pose estimation is important for virtual interaction, wearable control, and rehabilitation, but visual observations are often degraded by self-occlusion, hand-hand contact, and object manipulation. We propose EVFormer, a multimodal framework that combines the current RGB frame with the precedin...
JiaCheng Ge, SiYu Zhang, ShengJie Li et al.· 0 citations
Interdisciplinary student teams must negotiate differences in terminology, priorities, and practices, yet these differences are difficult to surface in text-based communication. We introduce Spritz, a Discord-based LLM technology probe designed to create a situated experience of AI-mediated collaboration for reflection...
Ching-Jung Cheng, Yu-Chan Chung, Bing-Chen Chiu et al.· 0 citations
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The growing use of large language models (LLMs) by young adults seeking sensitive health information has raised important questions in Human-AI Interaction about how these systems can support understanding and navigation of reproductive well-being. In response to Feminist HCI principles, we introduce OpenBloom, a web a...
Yang Hong, Ashley Hua, Adya Daruka et al.· 0 citations
In 2024, Saudi Arabia's Personal Data Protection Law (PDPL) came into force. However, little work has been done to assess its implementation. In this paper, we analyzed 100 e-commerce websites operating in Saudi Arabia against the PDPL, examining the presence of a privacy policy and, if present, the policy's declaratio...
Heterogeneous multi-robot path planning is a well-studied problem in which agents with disparate kinematic and dynamic models must coordinate to achieve shared objectives. These formulations, however, treat all agents as robotic-their cost models are mechanical and their traversability is sensor-derived. In human-robot...
Kristian Dalland, Prithvi Poddar, Souma Chowdhury et al.· 0 citations
Robot delivery studies can overstate transport capacity when travel to pickups and human support fall outside the modeled schedule. We formulate a location aware dispatch model that couples robot admission to transporter support and shared elevators, charging, and cleaning. The model replays 33,079 observed hospital re...
Krzysztof Siwek, Aleksandra \'Swietlicka· 0 citations
Autonomous social navigation requires balancing efficiency, physical safety, and social compliance. Reinforcement Learning (RL) methods provide a viable and effective solution but often rely on unrealistic assumptions, such as the knowledge of humans' position and velocity. In this paper, we introduce JESSI (JAX-based...
Tommaso Van Der Meer Andrea Garulli, Antonio Giannitrapani, Renato Quartullo et al.· 0 citations
Aspiring international students across Asian countries increasingly depend on commercial education agents to navigate scholarships, documentation, and visas. Alongside this commercial infrastructure, volunteer-run Facebook groups have emerged. Unpaid admins and moderators, often under their real identities, vet informa...
Umme Jannat Taposhi, Md. Tawhid Anwar, Alvi Islam Ratul et al.· 0 citations
We propose a force-based model for social navigation of a tour-guide robot. Social forces due to various factors like obstacles, user position and heading, have been accounted for in the model. We claim that each one of these forces makes the robot more sociable to the user and we design an experimental setup for evalu...
Roadside traffic reasoning requires every free-form textual claim to be backed by visual evidence. Existing grounded multimodal large language models (MLLMs) frequently exhibit say-point mismatch, in which the textual answer contradicts the bounding boxes the model localizes. Evaluation metrics that score answers and b...
Runwei Guan, Rongsheng Hu, Shangshu Chen et al.· 0 citations
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduSep 30, 2026
Able to defeat top-ranked human players and more efficient than other models, the new system could help decision-makers in military maneuvers or business negotiations.
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
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