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Collections including paper arxiv:2404.02258

AI Paper of the Day

A collection of papers that I think are interesting, one added each day

about 18 hours ago

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 22
OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1, 2024 • 82
Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 145
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity

Paper • 2401.17072 • Published Jan 30, 2024 • 25

The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27, 2024 • 605
BitNet: Scaling 1-bit Transformers for Large Language Models

Paper • 2310.11453 • Published Oct 17, 2023 • 96
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Paper • 2404.02258 • Published Apr 2, 2024 • 104
TransformerFAM: Feedback attention is working memory

Paper • 2404.09173 • Published Apr 14, 2024 • 43

Foundation AI Papers

Curated List of Must-Reads on LLM reasoning at Temus AI team

Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models

Paper • 2310.04406 • Published Oct 6, 2023 • 8
Chain-of-Thought Reasoning Without Prompting

Paper • 2402.10200 • Published Feb 15, 2024 • 104
ICDPO: Effectively Borrowing Alignment Capability of Others via In-context Direct Preference Optimization

Paper • 2402.09320 • Published Feb 14, 2024 • 6
Self-Discover: Large Language Models Self-Compose Reasoning Structures

Paper • 2402.03620 • Published Feb 6, 2024 • 114

mixture-of-experts

Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Paper • 2404.02258 • Published Apr 2, 2024 • 104

Efficient Training

Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Paper • 2404.02258 • Published Apr 2, 2024 • 104

Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Paper • 2404.02258 • Published Apr 2, 2024 • 104
Jamba: A Hybrid Transformer-Mamba Language Model

Paper • 2403.19887 • Published Mar 28, 2024 • 104
EfficientVMamba: Atrous Selective Scan for Light Weight Visual Mamba

Paper • 2403.09977 • Published Mar 15, 2024 • 9
SiMBA: Simplified Mamba-Based Architecture for Vision and Multivariate Time series

Paper • 2403.15360 • Published Mar 22, 2024 • 11

RecurrentGemma: Moving Past Transformers for Efficient Open Language Models

Paper • 2404.07839 • Published Apr 11, 2024 • 43
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Paper • 2404.02258 • Published Apr 2, 2024 • 104

JetMoE: Reaching Llama2 Performance with 0.1M Dollars

Paper • 2404.07413 • Published Apr 11, 2024 • 36
Rho-1: Not All Tokens Are What You Need

Paper • 2404.07965 • Published Apr 11, 2024 • 88
Jamba: A Hybrid Transformer-Mamba Language Model

Paper • 2403.19887 • Published Mar 28, 2024 • 104
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Paper • 2404.02258 • Published Apr 2, 2024 • 104

Twist and turn LLms

Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Paper • 2404.02258 • Published Apr 2, 2024 • 104

Jamba: A Hybrid Transformer-Mamba Language Model

Paper • 2403.19887 • Published Mar 28, 2024 • 104
Aurora-M: The First Open Source Multilingual Language Model Red-teamed according to the U.S. Executive Order

Paper • 2404.00399 • Published Mar 30, 2024 • 41
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Paper • 2404.02258 • Published Apr 2, 2024 • 104
Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length

Paper • 2404.08801 • Published Apr 12, 2024 • 64

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