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Collections including paper arxiv:2405.14860

Fundational - Deep Learning

Just How Flexible are Neural Networks in Practice?

Paper • 2406.11463 • Published Jun 17 • 7
Not All Language Model Features Are Linear

Paper • 2405.14860 • Published May 23 • 39
KAN: Kolmogorov-Arnold Networks

Paper • 2404.19756 • Published Apr 30 • 108
An Interactive Agent Foundation Model

Paper • 2402.05929 • Published Feb 8 • 27

Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Paper • 2406.06525 • Published Jun 10 • 64
Husky: A Unified, Open-Source Language Agent for Multi-Step Reasoning

Paper • 2406.06469 • Published Jun 10 • 23
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models

Paper • 2406.04271 • Published Jun 6 • 27
Block Transformer: Global-to-Local Language Modeling for Fast Inference

Paper • 2406.02657 • Published Jun 4 • 36

Not All Language Model Features Are Linear

Paper • 2405.14860 • Published May 23 • 39
LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations

Paper • 2410.02707 • Published Oct 3 • 47

Phased Consistency Model

Paper • 2405.18407 • Published May 28 • 46
AutoCoder: Enhancing Code Large Language Model with AIEV-Instruct

Paper • 2405.14906 • Published May 23 • 23
Not All Language Model Features Are Linear

Paper • 2405.14860 • Published May 23 • 39

Not All Language Model Features Are Linear

Paper • 2405.14860 • Published May 23 • 39
TimeGPT-1

Paper • 2310.03589 • Published Oct 5, 2023 • 5
A Careful Examination of Large Language Model Performance on Grade School Arithmetic

Paper • 2405.00332 • Published May 1 • 30
EasyAnimate: A High-Performance Long Video Generation Method based on Transformer Architecture

Paper • 2405.18991 • Published May 29 • 12

Not All Language Model Features Are Linear

Paper • 2405.14860 • Published May 23 • 39
Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

Paper • 2405.21060 • Published May 31 • 63

Models and Linearity

Your Transformer is Secretly Linear

Paper • 2405.12250 • Published May 19 • 150
Not All Language Model Features Are Linear

Paper • 2405.14860 • Published May 23 • 39

Interesting things.

AtP*: An efficient and scalable method for localizing LLM behaviour to components

Paper • 2403.00745 • Published Mar 1 • 11
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27 • 602
MobiLlama: Towards Accurate and Lightweight Fully Transparent GPT

Paper • 2402.16840 • Published Feb 26 • 23
LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens

Paper • 2402.13753 • Published Feb 21 • 111

Relative representations enable zero-shot latent space communication

Paper • 2209.15430 • Published Sep 30, 2022 • 1
Not All Language Model Features Are Linear

Paper • 2405.14860 • Published May 23 • 39
The Geometry of Categorical and Hierarchical Concepts in Large Language Models

Paper • 2406.01506 • Published Jun 3 • 3

efficient inference

Hydragen: High-Throughput LLM Inference with Shared Prefixes

Paper • 2402.05099 • Published Feb 7 • 18
Ouroboros: Speculative Decoding with Large Model Enhanced Drafting

Paper • 2402.13720 • Published Feb 21 • 5
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention

Paper • 2405.12981 • Published May 21 • 28
Your Transformer is Secretly Linear

Paper • 2405.12250 • Published May 19 • 150

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