collaborators

9 papers

cs.RO2026

UAV-MapFusion: RTK-Aligned Uncertainty-Aware Coarse-to-Fine Multi-Session UAV Mapping

Feng Pan, Chunran Zheng, Bing Xue +4

Large-scale point cloud maps are essential for robotics and spatial intelligence tasks. UAVs provide an efficient means for large-scale map acquisition; however, due to limited fli…

cs.CV2026

Neural Architecture Distributions: A New Paradigm for Stochastic Segmentation

Conghui Li, Junhao Huang, Chern Hong Lim +2

Stochastic segmentation seeks to represent multiple plausible masks for a single image, which is essential in safety- and quality-critical applications such as medical imaging or b…

cs.CL2026

DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence

DeepSeek-AI, Anyi Xu, Bangcai Lin +315

We present a preview version of DeepSeek-V4 series, including two strong Mixture-of-Experts (MoE) language models -- DeepSeek-V4-Pro with 1.6T parameters (49B activated) and DeepSe…

cs.CL2026

DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

DeepSeek-AI, Daya Guo, Dejian Yang +195

General reasoning represents a long-standing and formidable challenge in artificial intelligence. Recent breakthroughs, exemplified by large language models (LLMs) and chain-of-tho…

cs.CL2025

DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models

DeepSeek-AI, Aixin Liu, Aoxue Mei +260

We introduce DeepSeek-V3.2, a model that harmonizes high computational efficiency with superior reasoning and agent performance. The key technical breakthroughs of DeepSeek-V3.2 ar…

cs.CL2025

The Bias is in the Details: An Assessment of Cognitive Bias in LLMs

R. Alexander Knipper, Charles S. Knipper, Kaiqi Zhang +3

As Large Language Models (LLMs) are increasingly embedded in real-world decision-making processes, it becomes crucial to examine the extent to which they exhibit cognitive biases.…