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Found 10 papers, 1 papers with code
Empowering Language Models with Active Inquiry for Deeper Understanding
The rise of large language models (LLMs) has revolutionized the way that we interact with artificial intelligence systems through natural language.
GS-Pose: Category-Level Object Pose Estimation via Geometric and Semantic Correspondence
This requires significantly less data to train than prior methods since the semantic features are robust to object texture and appearance.
CCD-3DR: Consistent Conditioning in Diffusion for Single-Image 3D Reconstruction
However, such strategies fail to consistently align the denoised point cloud with the given image, leading to unstable conditioning and inferior performance.
Language Model Self-improvement by Reinforcement Learning Contemplation
We demonstrate that SIRLC can be applied to various NLP tasks, such as reasoning problems, text generation, and machine translation.
HouseCat6D -- A Large-Scale Multi-Modal Category Level 6D Object Perception Dataset with Household Objects in Realistic Scenarios
Estimating 6D object poses is a major challenge in 3D computer vision.
PhoCaL: A Multi-Modal Dataset for Category-Level Object Pose Estimation with Photometrically Challenging Objects
Object pose estimation is crucial for robotic applications and augmented reality.
DemoGrasp: Few-Shot Learning for Robotic Grasping with Human Demonstration
We first present a small sequence of RGB-D images displaying a human-object interaction.
Sparse Tensor Additive Regression
Tensors are becoming prevalent in modern applications such as medical imaging and digital marketing.
Distributed Flexible Nonlinear Tensor Factorization
Tensor factorization is a powerful tool to analyse multi-way data.
