258,720+ open-access research outputs.
Human-robot collaboration has been studied primarily in dyadic or sequential settings. However, real homes require multiadic collaboration, where multiple humans and robots share a workspace, acting c…
We show that Fr\'echet Distance (FD), long considered impractical as a training objective, can in fact be effectively optimized in the representation space. Our idea is simple: decouple the population…
Recent visual generation models have made major progress in photorealism, typography, instruction following, and interactive editing, yet they still struggle with spatial reasoning, persistent state, …
Electroencephalogram (EEG) signals are vital for automated seizure detection, but their inherent noise makes robust representation learning challenging. Existing graph construction methods, whether co…
The robotic manipulation of Deformable Linear Objects (DLOs) is a fundamental challenge due to the high-dimensional, non-linear dynamics of flexible structures and the complexity of maintaining topolo…
Existing research infrastructure is fundamentally document-centric, providing citation links between papers but lacking explicit representations of methodological evolution. In particular, it does not…
We present FlexiTac, a low-cost, open-source, and scalable piezoresistive tactile sensing solution designed for robotic end-effectors. FlexiTac is a practical "plug-in" module consisting of (i) thin, …
We introduce a refined immersed boundary (IB) methodology that is better-than-first-order accurate in practice, while preserving key properties of "continuous-forcing" IB approaches that retain a sing…
This work presents ThermoMesh, a passive thin-film thermoelectric mesh sensor designed to detect and characterize spatio-temporally sparse heat sources through conduction-based thermal imaging. The de…
Strong-coupling experiments based on magnons enable the exploration into on-chip demonstrations involving numerous long-lived excitations. Yttrium iron garnet (YIG) has been considered for decades as …
Efficient exploration is a central problem in reinforcement learning and is often formalized as maximizing the entropy of the state-action occupancy measure. While unconstrained maximum-entropy explor…
Finding the host galaxies of stellar-mass compact binary mergers will open a new window for studying their formation histories and measuring key cosmological parameters, such as the Hubble constant. T…
Multi-turn prompt injection follows a known attack path -- trust-building, pivoting, escalation but text-level defenses miss covert attacks where individual turns appear benign. We show this attack pa…
The standard post-training recipe for large multimodal models (LMMs) applies supervised fine-tuning (SFT) on curated demonstrations followed by reinforcement learning with verifiable rewards (RLVR). H…
Existing learning-based occupancy prediction methods rely on large-scale 3D annotations and generalize poorly across environments. We present FreeOcc, a training-free framework for open-vocabulary occ…
Accurate state estimation of nonlinear dynamical systems is fundamental to modern aerospace operations across air, sea, and space domains. Online tracking of adversarial unmanned aerial vehicles (UAVs…
The realization of bulk metallic altermagnetism has remained elusive despite the growing number of candidate materials. Here, we present evidence that moderate cobalt substitution ($\sim$15%) drives t…
Altermagnets host spin-split band structures while exhibiting vanishing equilibrium spin magnetization, making field-induced responses a direct probe of their quantum geometry. A central question, in …
Despite rapid advances in photorealistic video generation, real-world applications such as filmmaking require video aesthetics, e.g., harmonious colors and cinematic lighting, beyond visual fidelity. …
Range anxiety and long recharging times remain critical barriers to electric vehicle adoption. Dynamic Inductive Charging (DIC) offers a compelling solution by enabling wireless power transfer while d…
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