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Collections including paper arxiv:2404.08634

Data-efficient LLMs

dataset pruning for advancing the capabilities of LLMs

Effective pruning of web-scale datasets based on complexity of concept clusters

Paper • 2401.04578 • Published Jan 9
How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15 • 38
A Survey on Data Selection for LLM Instruction Tuning

Paper • 2402.05123 • Published Feb 4 • 3
LESS: Selecting Influential Data for Targeted Instruction Tuning

Paper • 2402.04333 • Published Feb 6 • 3

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Paper • 2402.19427 • Published Feb 29 • 52
Simple linear attention language models balance the recall-throughput tradeoff

Paper • 2402.18668 • Published Feb 28 • 18
ChunkAttention: Efficient Self-Attention with Prefix-Aware KV Cache and Two-Phase Partition

Paper • 2402.15220 • Published Feb 23 • 19
Linear Transformers are Versatile In-Context Learners

Paper • 2402.14180 • Published Feb 21 • 6

Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads

Paper • 2401.10774 • Published Jan 19 • 53
APAR: LLMs Can Do Auto-Parallel Auto-Regressive Decoding

Paper • 2401.06761 • Published Jan 12 • 1
Infinite-LLM: Efficient LLM Service for Long Context with DistAttention and Distributed KVCache

Paper • 2401.02669 • Published Jan 5 • 14
MambaByte: Token-free Selective State Space Model

Paper • 2401.13660 • Published Jan 24 • 50

Papers I have / will read in 2024

This collection contains all the papers (on ArXiv) that either I've read or I will read in 2024, including a short summary / conclusion

Improving Text Embeddings with Large Language Models

Paper • 2401.00368 • Published Dec 31, 2023 • 79
Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study

Paper • 2404.10719 • Published Apr 16 • 4
Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length

Paper • 2404.08801 • Published Apr 12 • 63
Pre-training Small Base LMs with Fewer Tokens

Paper • 2404.08634 • Published Apr 12 • 34

YAYI 2: Multilingual Open-Source Large Language Models

Paper • 2312.14862 • Published Dec 22, 2023 • 13
SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling

Paper • 2312.15166 • Published Dec 23, 2023 • 56
TrustLLM: Trustworthiness in Large Language Models

Paper • 2401.05561 • Published Jan 10 • 64
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Paper • 2401.06066 • Published Jan 11 • 42

ChatAnything: Facetime Chat with LLM-Enhanced Personas

Paper • 2311.06772 • Published Nov 12, 2023 • 34
Fine-tuning Language Models for Factuality

Paper • 2311.08401 • Published Nov 14, 2023 • 28
A Survey on Language Models for Code

Paper • 2311.07989 • Published Nov 14, 2023 • 21
Instruction-Following Evaluation for Large Language Models

Paper • 2311.07911 • Published Nov 14, 2023 • 19

The Generative AI Paradox: "What It Can Create, It May Not Understand"

Paper • 2311.00059 • Published Oct 31, 2023 • 18
Teaching Large Language Models to Reason with Reinforcement Learning

Paper • 2403.04642 • Published Mar 7 • 46
Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM

Paper • 2403.07816 • Published Mar 12 • 39
PERL: Parameter Efficient Reinforcement Learning from Human Feedback

Paper • 2403.10704 • Published Mar 15 • 57

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