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1,682 papers
Current multi-view gaze estimation remains limited by existing datasets, insufficient exploitation of complementary cross-view information, and evaluation focused primarily on average gaze error. We address these limitations through a more systematic study of multi-view gaze estimation. First, we introduce PrismGaze, a...
This paper instantiates the predictive interaction-dynamics framework of the base pHRI formulation on a SEA knee joint by implementing Bounded Assist-as-Needed scheduling, a corrective-channel energy tank, constrained OSQP stress cases, direct MuJoCo execution, and a posture-clamped MyoSuite knee slice.
The proposed system establishes a new operating point in the accuracy-latency-compute trade-off for latency- and resource-constrained gaze tracking, and highlights the potential of task-driven optical sensing for ultra-low-latency, computationally efficient human-computer interaction systems.
MILE, a teleoperation-based data-collection system comprising the wearable MILE exoskeleton and the mechanically corresponding MILE-Tac robotic hand, and trained paired ACT and DP policies with and without tactile input on MILE-collected demonstrations for downstream imitation learning.
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We introduce CoinFT, a capacitive 6-axis force/torque (F/T) sensor that is compact, light, low-cost, and robust with an average root-mean-squared error of 0.16 N for force and 1.08 mN m for moment when the input ranges from 0-14 N and 0-5 N in normal and shear directions, respectively. CoinFT is a stack of two rigid PC...
The results show that affective perception depends not only on the observed behavior, but also on how evidence is acquired, and by making observation acquisition experimentally controllable, AffectSim provides a foundation for studying embodied affective perception in interactive 3D environments.
The findings indicate that AI integration generally enhances diagnostic performance, but also introduced a 7% automation bias rate, quantified as the number of accepted negative consultations, where a previously correct independent assessment gets overturned by inaccurate AI guidance.
It is argued that making interpretation available at visitors' chosen moments improves the timing of explanation in outdoor MR and shifts more work to visitors: deciding when to stop, what to ask, how deeply to engage, and when to move on.
A psychology-oriented perspective is adopted to examine how university students form trust in AI-based learning assistants and proposes a conceptual framework that organizes psychological predictors of trust into four groups: cognitive appraisal, affective reactions, social-relational factors, and contextual moderators...
This paper proposes PnPSelect, a plug-and-play IoT device selection solution utilizing Ultra-Wideband (UWB) technology on commercial devices, and introduces a pointing direction estimation method that utilizes UWB readings from a single anchor to infer the user’s pointing direction.
HAGI++ is presented, a multi-modal diffusion-based imputation method that, for the first time, leverages integrated head-orientation sensors to exploit the natural correlation between head and eye movements and enables more complete, accurate eye-gaze recordings in real-world contexts, enhancing gaze-based analysis and...
The channel-gated model is the most accurate of the authors' learned fusion arms on clean data and its gates suppress the natively biased foot-orientation channels on clean real data without test-time supervision and flag dropout bursts at 0.92-0.999 AUROC.
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.
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.
A Blog post by H company on Hugging Face
The PKG Center for Social Impact expands Code.Tulsa experiential learning program.
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
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