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Collections including paper arxiv:2310.13961

Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Paper • 2401.16380 • Published Jan 29 • 46
Best Practices and Lessons Learned on Synthetic Data for Language Models

Paper • 2404.07503 • Published Apr 11 • 29
WizardLM: Empowering Large Language Models to Follow Complex Instructions

Paper • 2304.12244 • Published Apr 24, 2023 • 13
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Paper • 2402.13064 • Published Feb 20 • 46

Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 4

💫 Glossary https://osanseviero.github.io/hackerllama/blog/posts/hitchhiker_guide/

Understanding LLMs: A Comprehensive Overview from Training to Inference

Paper • 2401.02038 • Published Jan 4 • 61
Learning To Teach Large Language Models Logical Reasoning

Paper • 2310.09158 • Published Oct 13, 2023 • 1
ChipNeMo: Domain-Adapted LLMs for Chip Design

Paper • 2311.00176 • Published Oct 31, 2023 • 8
WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct

Paper • 2308.09583 • Published Aug 18, 2023 • 7

Papers: Instruct

Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 4
Tuna: Instruction Tuning using Feedback from Large Language Models

Paper • 2310.13385 • Published Oct 20, 2023 • 10
Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models

Paper • 2310.13127 • Published Oct 19, 2023 • 11
From Language Modeling to Instruction Following: Understanding the Behavior Shift in LLMs after Instruction Tuning

Paper • 2310.00492 • Published Sep 30, 2023 • 1

Papers: MoE/Ensemble

Papers related to Mixture of Experts topics.

QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models

Paper • 2310.16795 • Published Oct 25, 2023 • 26
Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 4
The Consensus Game: Language Model Generation via Equilibrium Search

Paper • 2310.09139 • Published Oct 13, 2023 • 12
Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning

Paper • 2310.03094 • Published Oct 4, 2023 • 12

Instruction Dataset

Monolingual or Multilingual Instruction Tuning: Which Makes a Better Alpaca

Paper • 2309.08958 • Published Sep 16, 2023 • 2
Generative Data Augmentation using LLMs improves Distributional Robustness in Question Answering

Paper • 2309.06358 • Published Sep 3, 2023 • 1
Tuna: Instruction Tuning using Feedback from Large Language Models

Paper • 2310.13385 • Published Oct 20, 2023 • 10
Retrieval-Generation Synergy Augmented Large Language Models

Paper • 2310.05149 • Published Oct 8, 2023 • 1

Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 4
Diversity of Thought Improves Reasoning Abilities of Large Language Models

Paper • 2310.07088 • Published Oct 11, 2023 • 5
AutoMix: Automatically Mixing Language Models

Paper • 2310.12963 • Published Oct 19, 2023 • 14
SAI: Solving AI Tasks with Systematic Artificial Intelligence in Communication Network

Paper • 2310.09049 • Published Oct 13, 2023 • 1

Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 4
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs

Paper • 2309.09582 • Published Sep 18, 2023 • 4
Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models

Paper • 2310.13127 • Published Oct 19, 2023 • 11
Evaluating the Robustness to Instructions of Large Language Models

Paper • 2308.14306 • Published Aug 28, 2023 • 1

Dataset generation

Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 4
ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Paper • 2202.07922 • Published Feb 16, 2022 • 1
Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small Models

Paper • 2310.13671 • Published Oct 20, 2023 • 18
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs

Paper • 2309.09582 • Published Sep 18, 2023 • 4

Research Papers

Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models

Paper • 2310.13127 • Published Oct 19, 2023 • 11
Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 4
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs

Paper • 2309.09582 • Published Sep 18, 2023 • 4
Unitxt: Flexible, Shareable and Reusable Data Preparation and Evaluation for Generative AI

Paper • 2401.14019 • Published Jan 25 • 19

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