https://github.com/Sha-Lab/babywalk
공식 코드BabyWalk: Going Farther in Vision-and-Language Navigation by Taking Baby Steps
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BabyWalk: Going Farther in Vision-and-Language Navigation by Taking Baby Steps
Open-RAG: Enhanced Retrieval-Augmented Reasoning with Open-Source Large Language Models
Learning to Navigate Intersections with Unsupervised Driver Trait Inference
Alice: Proactive Learning with Teacher's Demonstrations for Weak-to-Strong Generalization
Open-Set 3D Semantic Instance Maps for Vision Language Navigation -- O3D-SIM
Safe LLM-Controlled Robots with Formal Guarantees via Reachability Analysis
Adaptive Rectification Sampling for Test-Time Compute Scaling
Decentralized Motion Planning for Multi-Robot Navigation using Deep Reinforcement Learning
How Should Agents Ask Questions For Situated Learning? An Annotated Dialogue Corpus
Marathon Environments: Multi-Agent Continuous Control Benchmarks in a Modern Video Game Engine
Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks
Large Language Models are Better Reasoners with Self-Verification
Logic-Driven Context Extension and Data Augmentation for Logical Reasoning of Text
Explainable Graph Pyramid Autoformer for Long-Term Traffic Forecasting
Depicting Beyond Scores: Advancing Image Quality Assessment through Multi-modal Language Models
Language and Visual Entity Relationship Graph for Agent Navigation
Learning Efficient and Effective Trajectories for Differential Equation-based Image Restoration
From Cognition to Precognition: A Future-Aware Framework for Social Navigation
Deciphering Raw Data in Neuro-Symbolic Learning with Provable Guarantees
Demystifying AI Platform Design for Distributed Inference of Next-Generation LLM models
Share Secrets for Privacy: Confidential Forecasting with Vertical Federated Learning
Sequence Compression Speeds Up Credit Assignment in Reinforcement Learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.