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Found 10 papers, 2 papers with code
PillarMamba: Learning Local-Global Context for Roadside Point Cloud via Hybrid State Space Model
In this work, we introduce Mamba to pillar-based roadside point cloud perception and propose a framework based on Cross-stage State-space Group (CSG), called PillarMamba.
HeightFormer: Learning Height Prediction in Voxel Features for Roadside Vision Centric 3D Object Detection via Transformer
BEV features and voxel features present the real distribution of objects in 3D world compared to the image features.
MPO: An Efficient Post-Processing Framework for Mixing Diverse Preference Alignment
Reinforcement Learning from Human Feedback (RLHF) has shown promise in aligning large language models (LLMs).
RoseRAG: Robust Retrieval-augmented Generation with Small-scale LLMs via Margin-aware Preference Optimization
Large language models (LLMs) have achieved impressive performance but face high computational costs and latency, limiting their deployment in resource-constrained settings.
Unified Approaches in Self-Supervised Event Stream Modeling: Progress and Prospects
The proliferation of digital interactions across diverse domains, such as healthcare, e-commerce, gaming, and finance, has resulted in the generation of vast volumes of event stream (ES) data.
Expressivity of Representation Learning on Continuous-Time Dynamic Graphs: An Information-Flow Centric Review
Graphs are ubiquitous in real-world applications, ranging from social networks to biological systems, and have inspired the development of Graph Neural Networks (GNNs) for learning expressive representations.
Understanding Players as if They Are Talking to the Game in a Customized Language: A Pilot Study
This pilot study explores the application of language models (LMs) to model game event sequences, treating them as a customized natural language.
MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models
Artificial Intelligence (AI) has demonstrated significant potential in healthcare, particularly in disease diagnosis and treatment planning.
player2vec: A Language Modeling Approach to Understand Player Behavior in Games
Methods for learning latent user representations from historical behavior logs have gained traction for recommendation tasks in e-commerce, content streaming, and other settings.
Accelerate Model Parallel Training by Using Efficient Graph Traversal Order in Device Placement
In particular, we empirically study how different graph traversal order leads to different device placement, which in turn affects the training execution time.
