Agentic Intelligence Framework

Alternating Local Global Attention

Asynchronous Reinforcement Learning Infrastructure

Auxiliary Loss Free Load Balancing

Auxiliary Loss for Load Balance

Code Training Benefits Mathematical Reasoning

Collapsed Tree Retrieval

CommonCrawl Quality Filtering

Community Based Summarization

Community Detection For RAG

Computation Communication Overlap

Computational Efficiency in Large Language Models

Compute Optimal Scaling

Contextual Flexibility Retrieval

Cross File Code Completion

Cross File Dependency Analysis

Decoupled Rotary Position Embedding

DeepSeekMath Corpus

DeepSeekMoE

DeepSeekMoE Architecture

Dependency Aware Training

Dependency Aware Tree Traversal

Depth Over Width Scaling

Device Limited Routing

Direct Preference Optimization

Distillation of Reasoning Capability

Dynamic Expert Routing

Economical Training

Efficient Cross Node All to All Communication

Efficient Inference

Efficient Inference with Reduced Active Parameters

Efficient Long Context Attention Mechanism

Efficient Mixture of Experts Architecture

Efficient Model Training

Efficient Transformer Architecture

Entity Knowledge Graph Extraction

Expert Parallelism

Expert Selection Locality Analysis

FP8 Mixed Precision Training

Fill in the Middle Code Completion

Fine Grained Expert Segmentation

Gaussian Mixture Model Clustering

Ghost Attention

Global Context Understanding

Graph RAG

Group Relative Policy Optimization

Grouped Query Attention

Hierarchical Summarization

Instruction Fine Tuning with Direct Preference Optimization

Interleaving Local Global Attention

Iterative Reinforcement Learning

Knowledge Distillation for Small Language Models

Language Model Scaling Laws

Large Scale Agentic Data Synthesis

Large Scale Reinforcement Learning on Base Model

LeetCode Competition Benchmark

Leiden Algorithm For Text

Length Normalized Preference Optimization

Logit Soft Capping

Long Context Adaptation

Long Context Retrieval Optimization

Low Rank Key Value Joint Compression

Map Reduce Summarization

Memory Efficient Attention

Mixture of Experts Architecture

Mixture of Experts Sparsity Scaling Law

Model Merging through Weight Averaging

Modularity Based Retrieval

Multi Dimensional Scaling Laws

Multi Head Latent Attention

Multi Level Abstraction Retrieval

Multi Level Community Indexing

Multi Level Load Balancing

Multi Stage Post Training Recipe

Multi Stage Reinforcement Learning with Self Critique

Multi Step Learning Rate Scheduler

Multi Token Prediction

Multilingual Multimodal Understanding

Multilingual Performance Scaling

Multimodal Knowledge Distillation

MuonClip Optimizer

Node Limited Routing

Non Embedding FLOPs per Token

Open Foundation and Fine Tuned Chat Models

Open Language Model Evaluation System

Open and Efficient Foundation Language Models

Optimal Model Data Scaling Allocation

Pan & Scan Image Processing

Parameter Efficient Language Model Scaling

Performance Training Inference Tradeoff

Persona Driven Data Synthesis

Pre fill and Chunking

Project Level Code Understanding

Prompt Decontamination

Proximal Policy Optimization

Public Dataset Only Training

QK Clip Attention Stabilization

Quantization Aware Training

Query Focused Summarization

RMSNorm Pre Normalization

RMSNorm Stabilization

Reasoning Oriented Reinforcement Learning

Recursive Abstractive Processing

Recursive Summarization

Red Team Safety Testing

Reinforcement Learning with Cold Start

Reinforcement Learning with Human Feedback

Reinforcement Learning with Verifiable Rewards

Rejection Sampling Fine Tuning

Rejection Sampling and Supervised Fine Tuning

Repository Level Data Construction

Repository Level Deduplication

Responsible Open Model Development

RoPE Positional Embedding Extension

Rolling Buffer Cache

Rotary Positional Embeddings

Routing Network Token Selection

Safety Alignment

Safety Context Distillation

Scaling Laws for Large Language Models

Scaling Open Source Language Models with Longtermism

Self Reflection Content Moderation

Semantic Similarity Clustering

Shared Expert Isolation

Skill Specific Synthetic Data Generation

Skill Targeted Model Training

Sliding Window Attention

Sliding Window Attention Optimization

Sparse Mixture of Experts

Speculative Decoding

Supervised Fine Tuning

SwiGLU Activation Function

Synthetic Data Generation for Mathematics

Synthetic Data Rephrasing for Token Efficiency

System Message for Multi Turn Consistency

System Prompt Guardrails

Tile Wise Fine Grained Quantization

Token Dropping Strategy

Token Efficient Knowledge Compression

Tool Use Emergence

Topological Sorting For Code Learning

Tree Organized Retrieval

Two Expert Token Processing

Ultimate Expert Specialization

Unified Paradigm for Reinforcement Learning

Verifiable Rewards Reinforcement Learning

Vision Encoder Token Condensation