activity
20242026
collaborators

7 papers

cs.DC2026

DeepSeek Elastic Compute (DSec): A Sandbox Infrastructure for Effective Agentic Training at Scale

Jialiang Huang, Hongxuan Tang, Jingchang Chen +128

Large-scale agentic training and evaluation with large language models (LLMs) rely on isolated, stateful execution environments in which models inspect repositories, invoke tools,…

cs.CL2026

DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression

DeepSeek-AI, :, Anyi Xu +585

The widespread adoption of long-horizon agents has made model workloads increasingly input-heavy. Although prior work has substantially reduced the cost of long-context computation…

cs.CV2025

From Detection to Association: Learning Discriminative Object Embeddings for Multi-Object Tracking

Yuqing Shao, Yuchen Yang, Rui Yu +5

End-to-end multi-object tracking (MOT) methods have recently achieved remarkable progress by unifying detection and association within a single framework. Despite their strong dete…

cs.RO2025

DistillDrive: End-to-End Multi-Mode Autonomous Driving Distillation by Isomorphic Hetero-Source Planning Model

Rui Yu, Xianghang Zhang, Runkai Zhao +2

End-to-end autonomous driving has been recently seen rapid development, exerting a profound influence on both industry and academia. However, the existing work places excessive foc…

cs.LG2025

Unimodal-driven Distillation in Multimodal Emotion Recognition with Dynamic Fusion

Jiagen Li, Rui Yu, Huihao Huang +1

Multimodal Emotion Recognition in Conversations (MERC) identifies emotional states across text, audio and video, which is essential for intelligent dialogue systems and opinion ana…

cs.CV2024

Future Does Matter: Boosting 3D Object Detection with Temporal Motion Estimation in Point Cloud Sequences

Rui Yu, Runkai Zhao, Cong Nie +3

Accurate and robust LiDAR 3D object detection is essential for comprehensive scene understanding in autonomous driving. Despite its importance, LiDAR detection performance is limit…

cs.CV2024

Unleashing the Potential of Mamba: Boosting a LiDAR 3D Sparse Detector by Using Cross-Model Knowledge Distillation

Rui Yu, Runkai Zhao, Jiagen Li +3

The LiDAR 3D object detector that balances accuracy and speed is crucial for achieving real-time perception in autonomous driving. However, many existing LiDAR detection models rel…