11 accepted papers
Fine-tolerance peg-in-hole manipulation demands high precision under contact-rich, nonsmooth dynamics, where irregular geometries, inclinations, and tight-clearance interference often cause model-free reinforcement learning (RL) to fail. We propose the Curriculum-Guided Temporal Haptic World Model (…
Concept erasure aims to remove harmful, inappropriate, or copyrighted content from text-to-image diffusion models while preserving non-target semantics. However, existing methods either rely on costly fine-tuning or apply coarse semantic separation, often degrading unrelated concepts and lacking ada
Learning visuomotor policies with imitation learning from 3D observations is a primary research direction in robotic manipulation, as 3D data inherently captures spatial features critical for action. While many existing methods rely on multiview point cloud fusion, recent studies like 3D Diffusion P
Model-based robot control requires an accurate dynamics model and a machine learning-based method can extract robot dynamics from collected motion data by simulation and experiment. A Gaussian process (GP) has been used as one of the learning methods to obtain robot dynamics. To avoid large training
The exceptional generative capability of text-to-image models has raised substantial safety concerns regarding the generation of Not-Safe-For-Work (NSFW) content and potential copyright infringement. To address these concerns, previous methods safeguard the models by eliminating inappropriate concep…
External and internal convertible (EIC) form-based motion control (i.e., EIC-based control) is one of the effective approaches for underactuated balance robots. By sequentially controller design, trajectory tracking of the actuated subsystem and balance of the unactuated subsystem can be achieved si…
Large Language Models (LLMs) have exhibited impressive capabilities in various tasks, yet their vast parameter sizes restrict their applicability in resource-constrained settings. Knowledge distillation (KD) offers a viable solution by transferring expertise from large teacher models to compact stud…
Existing popular video captioning benchmarks and models often produce generic captions for videos that lack specific identification of individuals, locations, or organizations (named entities). However, in the case of news videos, the setting is more demanding, requiring the inclusion of such named…
Tracking control of underactuated balance robots needs to estimate balance profiles, that is, balance equilibrium manifold (BEM) of the unactuated subsystems. We present a learning-based approach to obtain the balance manifold for underactuated balance robots. We first establish the relationship bet…
Self-supervised pre-training recently demonstrates success on large-scale multimodal data, and state-of-the-art contrastive learning methods often enforce the feature consistency from cross-modality inputs, such as video/audio or video/text pairs. Despite its convenience to formulate and leverage in…
We present a Gaussian process (GP)-based tracking control of underactuated balance robots in which an actuated subsystem is required to follow a desired trajectory, while an unactuated, unstable subsystem needs to be kept balanced. The GP models are used to capture the coupling effects between the a