Xingkai Yu
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View article: DeepSeek-R1 incentivizes reasoning in LLMs through reinforcement learning
DeepSeek-R1 incentivizes reasoning in LLMs through reinforcement learning Open
General reasoning represents a long-standing and formidable challenge in artificial intelligence (AI). Recent breakthroughs, exemplified by large language models (LLMs) 1,2 and chain-of-thought (CoT) prompting 3 , have achieved considerabl…
View article: DHGRPO: Domain-Induced, Hierarchical Group Relative Policy Optimization
DHGRPO: Domain-Induced, Hierarchical Group Relative Policy Optimization Open
DHGRPO (Domain-Induced Hierarchical Group Relative Policy Optimization) is a mathematically grounded extension of Group Relative Policy Optimization (GRPO) that mitigates group-level failure modes in preference-based fine-tuning of large l…
View article: Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling
Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling Open
In this work, we introduce Janus-Pro, an advanced version of the previous work Janus. Specifically, Janus-Pro incorporates (1) an optimized training strategy, (2) expanded training data, and (3) scaling to larger model size. With these imp…
View article: DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced\n Multimodal Understanding
DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced\n Multimodal Understanding Open
We present DeepSeek-VL2, an advanced series of large Mixture-of-Experts (MoE)\nVision-Language Models that significantly improves upon its predecessor,\nDeepSeek-VL, through two key major upgrades. For the vision component, we\nincorporate…
View article: Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation
Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation Open
In this paper, we introduce Janus, an autoregressive framework that unifies multimodal understanding and generation. Prior research often relies on a single visual encoder for both tasks, such as Chameleon. However, due to the differing le…
View article: A Dual Adaptive Unscented Kalman Filter Algorithm for SINS-Based Integrated Navigation System
A Dual Adaptive Unscented Kalman Filter Algorithm for SINS-Based Integrated Navigation System Open
In this study, the problem of measuring noise pollution distribution by the intertial-based integrated navigation system is effectively suppressed. Based on nonlinear inertial navigation error modeling, a nested dual Kalman filter framewor…
View article: DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models Open
In the era of large language models, Mixture-of-Experts (MoE) is a promising architecture for managing computational costs when scaling up model parameters. However, conventional MoE architectures like GShard, which activate the top-$K$ ou…
View article: DeepSeek LLM: Scaling Open-Source Language Models with Longtermism
DeepSeek LLM: Scaling Open-Source Language Models with Longtermism Open
The rapid development of open-source large language models (LLMs) has been truly remarkable. However, the scaling law described in previous literature presents varying conclusions, which casts a dark cloud over scaling LLMs. We delve into …
View article: Robust Kalman filters with unknown covariance of multiplicative noise
Robust Kalman filters with unknown covariance of multiplicative noise Open
In this paper, state and noise covariance estimation problems for linear system with unknown multiplicative noise are considered. The measurement likelihood is modelled as a mixture of two Gaussian distributions and a Student's t distribut…
View article: Adaptive Kalman Filter for Linear Systems with Additive and Multiplicative Noises
Adaptive Kalman Filter for Linear Systems with Additive and Multiplicative Noises Open
This manuscript investigates adaptive Kalman filter problem of of linear systems with multiplicative and additive noises. The main contributions are stated in two aspects. Firstly, compared with the estimation problem of linear systems wit…
View article: Adaptive Kalman Filter for Linear Systems with Additive and Multiplicative Noises
Adaptive Kalman Filter for Linear Systems with Additive and Multiplicative Noises Open
This manuscript investigates adaptive Kalman filter problem of of linear systems with multiplicative and additive noises. The main contributions are stated in two aspects. Firstly, compared with the estimation problem of linear systems wit…