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Large Language Model Unlearning via Embedding-Corrupted Prompts
Paper • 2406.07933 • Published • 6 -
Block Transformer: Global-to-Local Language Modeling for Fast Inference
Paper • 2406.02657 • Published • 36 -
Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning
Paper • 2406.12050 • Published • 10 -
How Do Large Language Models Acquire Factual Knowledge During Pretraining?
Paper • 2406.11813 • Published • 29
Collections
Discover the best community collections!
Collections including paper arxiv:2406.02657
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Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation
Paper • 2406.06525 • Published • 64 -
Husky: A Unified, Open-Source Language Agent for Multi-Step Reasoning
Paper • 2406.06469 • Published • 23 -
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models
Paper • 2406.04271 • Published • 27 -
Block Transformer: Global-to-Local Language Modeling for Fast Inference
Paper • 2406.02657 • Published • 36
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Kaleido Diffusion: Improving Conditional Diffusion Models with Autoregressive Latent Modeling
Paper • 2405.21048 • Published • 12 -
Block Transformer: Global-to-Local Language Modeling for Fast Inference
Paper • 2406.02657 • Published • 36 -
Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation
Paper • 2406.06525 • Published • 64
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MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training
Paper • 2311.17049 • Published -
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
Paper • 2405.04434 • Published • 14 -
A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision
Paper • 2303.17376 • Published -
Sigmoid Loss for Language Image Pre-Training
Paper • 2303.15343 • Published • 4
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Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length
Paper • 2404.08801 • Published • 62 -
TransformerFAM: Feedback attention is working memory
Paper • 2404.09173 • Published • 43 -
Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention
Paper • 2404.07143 • Published • 103 -
Block Transformer: Global-to-Local Language Modeling for Fast Inference
Paper • 2406.02657 • Published • 36
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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 • 26 -
MoDE: CLIP Data Experts via Clustering
Paper • 2404.16030 • Published • 12 -
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning
Paper • 2405.12130 • Published • 45 -
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention
Paper • 2405.12981 • Published • 27
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PRDP: Proximal Reward Difference Prediction for Large-Scale Reward Finetuning of Diffusion Models
Paper • 2402.08714 • Published • 10 -
Data Engineering for Scaling Language Models to 128K Context
Paper • 2402.10171 • Published • 21 -
RLVF: Learning from Verbal Feedback without Overgeneralization
Paper • 2402.10893 • Published • 10 -
Coercing LLMs to do and reveal (almost) anything
Paper • 2402.14020 • Published • 12
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Blending Is All You Need: Cheaper, Better Alternative to Trillion-Parameters LLM
Paper • 2401.02994 • Published • 47 -
MambaByte: Token-free Selective State Space Model
Paper • 2401.13660 • Published • 48 -
Repeat After Me: Transformers are Better than State Space Models at Copying
Paper • 2402.01032 • Published • 22 -
BlackMamba: Mixture of Experts for State-Space Models
Paper • 2402.01771 • Published • 22