Garment Particles is a 5D point cloud representation jointly encoding 2D sewing patterns and 3D geometry, supporting rectified flow generation from high-level inputs and diffusion-based editing of patterns or shapes.
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BFMTrack presents Latent Sequence Optimization to extend Behavioral Foundation Models to precise time-varying motion tracking by optimizing latent sequences with simulation and policy gradients, tested on dense tracking, keyframing, and real-robot deployment.
CoastlineVLM-7B, a 7B VLM fine-tuned from LLaVA/GeoChat, jointly detects coastline presence, classifies proxies, and outputs polylines, reducing Hausdorff distance to 31.84 m and EMD to 17.32 m versus segmentation baselines on NZCCD.
LLMs generate 5P causal graphs from 46 psychotherapy intake transcripts that match human expert graphs in structure and meaning, with moderate clinical usefulness ratings.
Random feature selection outperforms many state-of-the-art unsupervised feature selection methods on standard performance and efficiency metrics.
Bayesian optimization with Gaussian processes unifies minimization, single-point saddle searches, and double-ended path searches on potential energy surfaces through a shared six-step surrogate loop using derivative observations and inverse-distance kernels.
citing papers explorer
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Garment Particles: A 2D--3D Symmetric Garment Representation for Generation and Editing
Garment Particles is a 5D point cloud representation jointly encoding 2D sewing patterns and 3D geometry, supporting rectified flow generation from high-level inputs and diffusion-based editing of patterns or shapes.
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BFMTrack: Latent Sequence Optimization for Physics-Based Motion Tracking with Behavioral Foundation Models
BFMTrack presents Latent Sequence Optimization to extend Behavioral Foundation Models to precise time-varying motion tracking by optimizing latent sequences with simulation and policy gradients, tested on dense tracking, keyframing, and real-robot deployment.
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Geometric Coastline Localization using Vision-Language Models
CoastlineVLM-7B, a 7B VLM fine-tuned from LLaVA/GeoChat, jointly detects coastline presence, classifies proxies, and outputs polylines, reducing Hausdorff distance to 31.84 m and EMD to 17.32 m versus segmentation baselines on NZCCD.
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InsightFlow: LLM-Driven Synthesis of Patient Narratives for Mental Health into Causal Models
LLMs generate 5P causal graphs from 46 psychotherapy intake transcripts that match human expert graphs in structure and meaning, with moderate clinical usefulness ratings.
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Worse than Random: The Importance of a Baseline for Unsupervised Feature Selection
Random feature selection outperforms many state-of-the-art unsupervised feature selection methods on standard performance and efficiency metrics.
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A Tutorial Review of Bayesian Optimization with Gaussian Processes to Accelerate Stationary Point Searches
Bayesian optimization with Gaussian processes unifies minimization, single-point saddle searches, and double-ended path searches on potential energy surfaces through a shared six-step surrogate loop using derivative observations and inverse-distance kernels.