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

DeepSeek-V3 Technical Report

SAM 2: Segment Anything in Images and Videos

The Llama 3 Herd of Models

Qwen2 Technical Report

DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training

Mixtral of Experts

Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision

Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Scaling deep learning for materials discovery

The Falcon Series of Open Language Models

CogVLM: Visual Expert for Pretrained Language Models

Towards Understanding Sycophancy in Language Models

Mistral 7B

SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

Accurate proteome-wide missense variant effect prediction with AlphaMissense

Efficient Memory Management for Large Language Model Serving with PagedAttention

Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

3D Gaussian Splatting for Real-Time Radiance Field Rendering

AgentBench: Evaluating LLMs as Agents

ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs

Universal and Transferable Adversarial Attacks on Aligned Language Models

Llama 2: Open Foundation and Fine-Tuned Chat Models

FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning

Jailbroken: How Does LLM Safety Training Fail?

SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Textbooks Are All You Need

Simple and Controllable Music Generation

AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration

Let's Verify Step by Step

Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Voyager: An Open-Ended Embodied Agent with Large Language Models

Gorilla: Large Language Model Connected with Massive APIs

QLoRA: Efficient Finetuning of Quantized LLMs

Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold

Tree of Thoughts: Deliberate Problem Solving with Large Language Models

InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning

ImageBind: One Embedding Space To Bind Them All

Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models

MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Visual Instruction Tuning

DINOv2: Learning Robust Visual Features without Supervision

Generative Agents: Interactive Simulacra of Human Behavior

Segment Anything

Self-Refine: Iterative Refinement with Self-Feedback

Sparks of Artificial General Intelligence: Early experiments with GPT-4

Zero-1-to-3: Zero-shot One Image to 3D Object

Reflexion: Language Agents with Verbal Reinforcement Learning

Evolutionary-scale prediction of atomic-level protein structure with a language model

GPT-4 Technical Report

Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

Consistency Models

LLaMA: Open and Efficient Foundation Language Models

Language Is Not All You Need: Aligning Perception with Language Models

Symbolic Discovery of Optimization Algorithms

Adding Conditional Control to Text-to-Image Diffusion Models

Toolformer: Language Models Can Teach Themselves to Use Tools

BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers

Muse: Text-To-Image Generation via Masked Generative Transformers

GraphCast: Learning skillful medium-range global weather forecasting

Constitutional AI: Harmlessness from AI Feedback

Robust Speech Recognition via Large-Scale Weak Supervision

Fast Inference from Transformers via Speculative Decoding

Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks

Magic3D: High-Resolution Text-to-3D Content Creation

SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models

PAL: Program-aided Language Models

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

ReAct: Synergizing Reasoning and Acting in Language Models

Flow Matching for Generative Modeling

Imagen Video: High Definition Video Generation with Diffusion Models

GLM-130B: An Open Bilingual Pre-trained Model

Discovering faster matrix multiplication algorithms with reinforcement learning

DreamFusion: Text-to-3D using 2D Diffusion

Make-A-Video: Text-to-Video Generation without Text-Video Data

Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

AudioLM: a Language Modeling Approach to Audio Generation

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

Classifier-Free Diffusion Guidance

Scaling Autoregressive Models for Content-Rich Text-to-Image Generation

Emergent Abilities of Large Language Models

FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness

Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding

Least-to-Most Prompting Enables Complex Reasoning in Large Language Models

A Generalist Agent

Simple Open-Vocabulary Object Detection with Vision Transformers

OPT: Open Pre-trained Transformer Language Models

Flamingo: a Visual Language Model for Few-Shot Learning

GPT-NeoX-20B: An Open-Source Autoregressive Language Model

Hierarchical Text-Conditional Image Generation with CLIP Latents

PaLM: Scaling Language Modeling with Pathways

Training Compute-Optimal Large Language Models

STaR: Bootstrapping Reasoning With Reasoning

Self-Consistency Improves Chain of Thought Reasoning in Language Models

Training language models to follow instructions with human feedback

Locating and Editing Factual Associations in GPT

Red Teaming Language Models with Language Models

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model

BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

Instant Neural Graphics Primitives with a Multiresolution Hash Encoding

A ConvNet for the 2020s

High-Resolution Image Synthesis with Latent Diffusion Models

WebGPT: Browser-assisted question-answering with human feedback

GLaM: Efficient Scaling of Language Models with Mixture-of-Experts

Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Show Your Work: Scratchpads for Intermediate Computation with Language Models

Masked Autoencoders Are Scalable Vision Learners

Highly accurate protein structure prediction with AlphaFold

Evaluating Large Language Models Trained on Code

ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation

LoRA: Low-Rank Adaptation of Large Language Models

BEiT: BERT Pre-Training of Image Transformers

HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units

Decision Transformer: Reinforcement Learning via Sequence Modeling

Emerging Properties in Self-Supervised Vision Transformers

PanGu-$α$: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation

RoFormer: Enhanced Transformer with Rotary Position Embedding

Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

GLM: General Language Model Pretraining with Autoregressive Blank Infilling

Learning Transferable Visual Models From Natural Language Supervision

Improved Denoising Diffusion Probabilistic Models

ZeRO-Offload: Democratizing Billion-Scale Model Training

Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity

Training data-efficient image transformers & distillation through attention

Score-Based Generative Modeling through Stochastic Differential Equations

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Denoising Diffusion Implicit Models

Rethinking Attention with Performers

Learning to summarize from human feedback

Big Bird: Transformers for Longer Sequences

GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding

wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations

Denoising Diffusion Probabilistic Models

Language Models are Few-Shot Learners

End-to-End Object Detection with Transformers

Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Dense Passage Retrieval for Open-Domain Question Answering

Longformer: The Long-Document Transformer

ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators

NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis

Scaling Laws for Neural Language Models

Reformer: The Efficient Transformer

Dream to Control: Learning Behaviors by Latent Imagination

Analyzing and Improving the Image Quality of StyleGAN

Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

ZeRO: Memory Optimizations Toward Training Trillion Parameter Models

ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism

RoBERTa: A Robustly Optimized BERT Pretraining Approach

SpanBERT: Improving Pre-training by Representing and Predicting Spans

XLNet: Generalized Autoregressive Pretraining for Language Understanding

Generating Diverse High-Fidelity Images with VQ-VAE-2

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

Unified Language Model Pre-training for Natural Language Understanding and Generation

Generating Long Sequences with Sparse Transformers

Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context

A Style-Based Generator Architecture for Generative Adversarial Networks

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Glow: Generative Flow with Invertible 1x1 Convolutions

Neural Ordinary Differential Equations

AI safety via debate

World Models

Group Normalization

IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures

Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

Decoupled Weight Decay Regularization

Neural Discrete Representation Learning

Graph Attention Networks

Rainbow: Combining Improvements in Deep Reinforcement Learning

Proximal Policy Optimization Algorithms

Attention Is All You Need

Inductive Representation Learning on Large Graphs

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

Mask R-CNN

Wasserstein GAN

Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Image-to-Image Translation with Conditional Adversarial Networks

WaveNet: A Generative Model for Raw Audio

Semi-Supervised Classification with Graph Convolutional Networks

Densely Connected Convolutional Networks

Layer Normalization

Concrete Problems in AI Safety

Density estimation using Real NVP

Communication-Efficient Learning of Deep Networks from Decentralized Data

Asynchronous Methods for Deep Reinforcement Learning

Mastering the game of Go with deep neural networks and tree search

Deep Residual Learning for Image Recognition

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

Neural Machine Translation of Rare Words with Subword Units

You Only Look Once: Unified, Real-Time Object Detection

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Deep learning

U-Net: Convolutional Networks for Biomedical Image Segmentation

Trust Region Policy Optimization

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Adam: A Method for Stochastic Optimization

Fully Convolutional Networks for Semantic Segmentation

Going Deeper with Convolutions

Sequence to Sequence Learning with Neural Networks

Very Deep Convolutional Networks for Large-Scale Image Recognition

Neural Machine Translation by Jointly Learning to Align and Translate

Generative Adversarial Networks

Auto-Encoding Variational Bayes

Playing Atari with Deep Reinforcement Learning

Efficient Estimation of Word Representations in Vector Space

ImageNet Classification with Deep Convolutional Neural Networks

Improving neural networks by preventing co-adaptation of feature detectors