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Continuous Latent Diffusion Language Model
Paper • 2605.06548 • Published • 88 -
Scaling Latent Reasoning via Looped Language Models
Paper • 2510.25741 • Published • 234 -
Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach
Paper • 2502.05171 • Published • 161 -
Pretraining Language Models to Ponder in Continuous Space
Paper • 2505.20674 • Published • 3
Collections
Discover the best community collections!
Collections including paper arxiv:2501.06425
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CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data
Paper • 2404.15653 • Published • 29 -
MoDE: CLIP Data Experts via Clustering
Paper • 2404.16030 • Published • 14 -
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning
Paper • 2405.12130 • Published • 50 -
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention
Paper • 2405.12981 • Published • 33
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Adapters: A Unified Library for Parameter-Efficient and Modular Transfer Learning
Paper • 2311.11077 • Published • 29 -
Tensor Product Attention Is All You Need
Paper • 2501.06425 • Published • 91 -
LoRA: Low-Rank Adaptation of Large Language Models
Paper • 2106.09685 • Published • 65 -
ShortGPT: Layers in Large Language Models are More Redundant Than You Expect
Paper • 2403.03853 • Published • 66
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Evolving Deeper LLM Thinking
Paper • 2501.09891 • Published • 116 -
ProcessBench: Identifying Process Errors in Mathematical Reasoning
Paper • 2412.06559 • Published • 87 -
AceMath: Advancing Frontier Math Reasoning with Post-Training and Reward Modeling
Paper • 2412.15084 • Published • 13 -
The Lessons of Developing Process Reward Models in Mathematical Reasoning
Paper • 2501.07301 • Published • 100
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LLM Pruning and Distillation in Practice: The Minitron Approach
Paper • 2408.11796 • Published • 61 -
TableBench: A Comprehensive and Complex Benchmark for Table Question Answering
Paper • 2408.09174 • Published • 53 -
To Code, or Not To Code? Exploring Impact of Code in Pre-training
Paper • 2408.10914 • Published • 45 -
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Paper • 2408.11878 • Published • 64
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Nuclear Norm Regularization for Deep Learning
Paper • 2405.14544 • Published • 1 -
Token embeddings violate the manifold hypothesis
Paper • 2504.01002 • Published • 1 -
Approximate Nullspace Augmented Finetuning for Robust Vision Transformers
Paper • 2403.10476 • Published • 1 -
ElaLoRA: Elastic & Learnable Low-Rank Adaptation for Efficient Model Fine-Tuning
Paper • 2504.00254 • Published • 1
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Tensor Product Attention Is All You Need
Paper • 2501.06425 • Published • 91 -
Demons in the Detail: On Implementing Load Balancing Loss for Training Specialized Mixture-of-Expert Models
Paper • 2501.11873 • Published • 69 -
Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention
Paper • 2502.11089 • Published • 170 -
MoBA: Mixture of Block Attention for Long-Context LLMs
Paper • 2502.13189 • Published • 20
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FAST: Efficient Action Tokenization for Vision-Language-Action Models
Paper • 2501.09747 • Published • 28 -
Tensor Product Attention Is All You Need
Paper • 2501.06425 • Published • 91 -
SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM Training
Paper • 2501.06842 • Published • 16 -
LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token
Paper • 2501.03895 • Published • 51
-
Continuous Latent Diffusion Language Model
Paper • 2605.06548 • Published • 88 -
Scaling Latent Reasoning via Looped Language Models
Paper • 2510.25741 • Published • 234 -
Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach
Paper • 2502.05171 • Published • 161 -
Pretraining Language Models to Ponder in Continuous Space
Paper • 2505.20674 • Published • 3
-
LLM Pruning and Distillation in Practice: The Minitron Approach
Paper • 2408.11796 • Published • 61 -
TableBench: A Comprehensive and Complex Benchmark for Table Question Answering
Paper • 2408.09174 • Published • 53 -
To Code, or Not To Code? Exploring Impact of Code in Pre-training
Paper • 2408.10914 • Published • 45 -
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Paper • 2408.11878 • Published • 64
-
CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data
Paper • 2404.15653 • Published • 29 -
MoDE: CLIP Data Experts via Clustering
Paper • 2404.16030 • Published • 14 -
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning
Paper • 2405.12130 • Published • 50 -
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention
Paper • 2405.12981 • Published • 33
-
Nuclear Norm Regularization for Deep Learning
Paper • 2405.14544 • Published • 1 -
Token embeddings violate the manifold hypothesis
Paper • 2504.01002 • Published • 1 -
Approximate Nullspace Augmented Finetuning for Robust Vision Transformers
Paper • 2403.10476 • Published • 1 -
ElaLoRA: Elastic & Learnable Low-Rank Adaptation for Efficient Model Fine-Tuning
Paper • 2504.00254 • Published • 1
-
Adapters: A Unified Library for Parameter-Efficient and Modular Transfer Learning
Paper • 2311.11077 • Published • 29 -
Tensor Product Attention Is All You Need
Paper • 2501.06425 • Published • 91 -
LoRA: Low-Rank Adaptation of Large Language Models
Paper • 2106.09685 • Published • 65 -
ShortGPT: Layers in Large Language Models are More Redundant Than You Expect
Paper • 2403.03853 • Published • 66
-
Tensor Product Attention Is All You Need
Paper • 2501.06425 • Published • 91 -
Demons in the Detail: On Implementing Load Balancing Loss for Training Specialized Mixture-of-Expert Models
Paper • 2501.11873 • Published • 69 -
Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention
Paper • 2502.11089 • Published • 170 -
MoBA: Mixture of Block Attention for Long-Context LLMs
Paper • 2502.13189 • Published • 20
-
Evolving Deeper LLM Thinking
Paper • 2501.09891 • Published • 116 -
ProcessBench: Identifying Process Errors in Mathematical Reasoning
Paper • 2412.06559 • Published • 87 -
AceMath: Advancing Frontier Math Reasoning with Post-Training and Reward Modeling
Paper • 2412.15084 • Published • 13 -
The Lessons of Developing Process Reward Models in Mathematical Reasoning
Paper • 2501.07301 • Published • 100
-
FAST: Efficient Action Tokenization for Vision-Language-Action Models
Paper • 2501.09747 • Published • 28 -
Tensor Product Attention Is All You Need
Paper • 2501.06425 • Published • 91 -
SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM Training
Paper • 2501.06842 • Published • 16 -
LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token
Paper • 2501.03895 • Published • 51