Models
Datasets
Spaces
Docs
Enterprise
Pricing
Log In
Sign Up

Collections

Discover the best community collections!

Collections including paper arxiv:2503.18878

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 29
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 14
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 44
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 23

RL+reason model

RL + Transformer = A General-Purpose Problem Solver

Paper • 2501.14176 • Published Jan 24 • 28
Towards General-Purpose Model-Free Reinforcement Learning

Paper • 2501.16142 • Published Jan 27 • 30
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Paper • 2501.17161 • Published Jan 28 • 123
MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization

Paper • 2412.12098 • Published Dec 16, 2024 • 4

Interesting new techniques

Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models

Paper • 2401.01335 • Published Jan 2, 2024 • 68
Lumiere: A Space-Time Diffusion Model for Video Generation

Paper • 2401.12945 • Published Jan 23, 2024 • 86
Adding NVMe SSDs to Enable and Accelerate 100B Model Fine-tuning on a Single GPU

Paper • 2403.06504 • Published Mar 11, 2024 • 56
Transformer-Lite: High-efficiency Deployment of Large Language Models on Mobile Phone GPUs

Paper • 2403.20041 • Published Mar 29, 2024 • 34

To Read collection

interesting papers to read

Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model

Paper • 2503.24290 • Published Mar 31 • 62
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders

Paper • 2503.18878 • Published Mar 24 • 119
START: Self-taught Reasoner with Tools

Paper • 2503.04625 • Published Mar 6 • 113
DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Paper • 2503.14476 • Published Mar 18 • 141

Interpretability

I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders

Paper • 2503.18878 • Published Mar 24 • 119
Truth Neurons

Paper • 2505.12182 • Published May 18 • 8
Resa: Transparent Reasoning Models via SAEs

Paper • 2506.09967 • Published Jun 11 • 21
Why Can't Transformers Learn Multiplication? Reverse-Engineering Reveals Long-Range Dependency Pitfalls

Paper • 2510.00184 • Published Sep 30 • 16

Papers I have written about on my blog.

MARS: A Multi-Agent Framework Incorporating Socratic Guidance for Automated Prompt Optimization

Paper • 2503.16874 • Published Mar 21 • 44
System Prompt Optimization with Meta-Learning

Paper • 2505.09666 • Published May 14 • 71
UniRL: Self-Improving Unified Multimodal Models via Supervised and Reinforcement Learning

Paper • 2505.23380 • Published May 29 • 22
DeepTheorem: Advancing LLM Reasoning for Theorem Proving Through Natural Language and Reinforcement Learning

Paper • 2505.23754 • Published May 29 • 15

Perception and abstraction. Each modality is tokenized and embedded into vectors for model to comprehend.

VILA^2: VILA Augmented VILA

Paper • 2407.17453 • Published Jul 24, 2024 • 41
Octopus v4: Graph of language models

Paper • 2404.19296 • Published Apr 30, 2024 • 118
Octo-planner: On-device Language Model for Planner-Action Agents

Paper • 2406.18082 • Published Jun 26, 2024 • 48
Dolphin: Long Context as a New Modality for Energy-Efficient On-Device Language Models

Paper • 2408.15518 • Published Aug 28, 2024 • 42

Resa: Transparent Reasoning Models via SAEs

Paper • 2506.09967 • Published Jun 11 • 21
Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2

Paper • 2408.05147 • Published Aug 9, 2024 • 40
Train Sparse Autoencoders Efficiently by Utilizing Features Correlation

Paper • 2505.22255 • Published May 28 • 24
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders

Paper • 2503.18878 • Published Mar 24 • 119

LLM Internal Mechanism

I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders

Paper • 2503.18878 • Published Mar 24 • 119
Landscape of Thoughts: Visualizing the Reasoning Process of Large Language Models

Paper • 2503.22165 • Published Mar 28 • 28

Models and datasets used in the paper "Interpreting Reasoning Features in Large Language Models via Sparse Autoenoder": https://arxiv.org/abs/2503.188

andreuka18/DeepSeek-R1-Distill-Llama-8B-lmsys-openthoughts-tokenized

Viewer • Updated Mar 31 • 781k • 109
andreuka18/deepseek-r1-distill-llama-8b-lmsys-openthoughts

Text Generation • Updated Mar 31
andreuka18/OpenThoughts-10k-DeepSeek-R1

Viewer • Updated Mar 31 • 10k • 16
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders

Paper • 2503.18878 • Published Mar 24 • 119

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 29
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 14
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 44
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 23

Papers I have written about on my blog.

MARS: A Multi-Agent Framework Incorporating Socratic Guidance for Automated Prompt Optimization

Paper • 2503.16874 • Published Mar 21 • 44
System Prompt Optimization with Meta-Learning

Paper • 2505.09666 • Published May 14 • 71
UniRL: Self-Improving Unified Multimodal Models via Supervised and Reinforcement Learning

Paper • 2505.23380 • Published May 29 • 22
DeepTheorem: Advancing LLM Reasoning for Theorem Proving Through Natural Language and Reinforcement Learning

Paper • 2505.23754 • Published May 29 • 15

RL+reason model

RL + Transformer = A General-Purpose Problem Solver

Paper • 2501.14176 • Published Jan 24 • 28
Towards General-Purpose Model-Free Reinforcement Learning

Paper • 2501.16142 • Published Jan 27 • 30
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Paper • 2501.17161 • Published Jan 28 • 123
MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization

Paper • 2412.12098 • Published Dec 16, 2024 • 4

Perception and abstraction. Each modality is tokenized and embedded into vectors for model to comprehend.

VILA^2: VILA Augmented VILA

Paper • 2407.17453 • Published Jul 24, 2024 • 41
Octopus v4: Graph of language models

Paper • 2404.19296 • Published Apr 30, 2024 • 118
Octo-planner: On-device Language Model for Planner-Action Agents

Paper • 2406.18082 • Published Jun 26, 2024 • 48
Dolphin: Long Context as a New Modality for Energy-Efficient On-Device Language Models

Paper • 2408.15518 • Published Aug 28, 2024 • 42

Interesting new techniques

Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models

Paper • 2401.01335 • Published Jan 2, 2024 • 68
Lumiere: A Space-Time Diffusion Model for Video Generation

Paper • 2401.12945 • Published Jan 23, 2024 • 86
Adding NVMe SSDs to Enable and Accelerate 100B Model Fine-tuning on a Single GPU

Paper • 2403.06504 • Published Mar 11, 2024 • 56
Transformer-Lite: High-efficiency Deployment of Large Language Models on Mobile Phone GPUs

Paper • 2403.20041 • Published Mar 29, 2024 • 34

Resa: Transparent Reasoning Models via SAEs

Paper • 2506.09967 • Published Jun 11 • 21
Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2

Paper • 2408.05147 • Published Aug 9, 2024 • 40
Train Sparse Autoencoders Efficiently by Utilizing Features Correlation

Paper • 2505.22255 • Published May 28 • 24
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders

Paper • 2503.18878 • Published Mar 24 • 119

To Read collection

interesting papers to read

Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model

Paper • 2503.24290 • Published Mar 31 • 62
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders

Paper • 2503.18878 • Published Mar 24 • 119
START: Self-taught Reasoner with Tools

Paper • 2503.04625 • Published Mar 6 • 113
DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Paper • 2503.14476 • Published Mar 18 • 141

LLM Internal Mechanism

I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders

Paper • 2503.18878 • Published Mar 24 • 119
Landscape of Thoughts: Visualizing the Reasoning Process of Large Language Models

Paper • 2503.22165 • Published Mar 28 • 28

Interpretability

I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders

Paper • 2503.18878 • Published Mar 24 • 119
Truth Neurons

Paper • 2505.12182 • Published May 18 • 8
Resa: Transparent Reasoning Models via SAEs

Paper • 2506.09967 • Published Jun 11 • 21
Why Can't Transformers Learn Multiplication? Reverse-Engineering Reveals Long-Range Dependency Pitfalls

Paper • 2510.00184 • Published Sep 30 • 16

Models and datasets used in the paper "Interpreting Reasoning Features in Large Language Models via Sparse Autoenoder": https://arxiv.org/abs/2503.188

andreuka18/DeepSeek-R1-Distill-Llama-8B-lmsys-openthoughts-tokenized

Viewer • Updated Mar 31 • 781k • 109
andreuka18/deepseek-r1-distill-llama-8b-lmsys-openthoughts

Text Generation • Updated Mar 31
andreuka18/OpenThoughts-10k-DeepSeek-R1

Viewer • Updated Mar 31 • 10k • 16
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders

Paper • 2503.18878 • Published Mar 24 • 119

Previous
1
2
3
Next

Company

TOS Privacy About Jobs

Website

Models Datasets Spaces Pricing Docs