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Collections including paper arxiv:2302.04761

A collection of arXiv papers from Chip Huyen's AI Engineering organized by chapter and ordered by when each appears in the book.

Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning

Paper • 2211.04325 • Published Oct 26, 2022
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Paper • 1810.04805 • Published Oct 11, 2018 • 17
On the Opportunities and Risks of Foundation Models

Paper • 2108.07258 • Published Aug 16, 2021
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks

Paper • 2204.07705 • Published Apr 16, 2022 • 1

ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs

Paper • 2307.16789 • Published Jul 31, 2023 • 100
Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

Paper • 2308.00675 • Published Aug 1, 2023 • 36
Toolformer: Language Models Can Teach Themselves to Use Tools

Paper • 2302.04761 • Published Feb 9, 2023 • 11
GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction

Paper • 2305.18752 • Published May 30, 2023 • 4

RL Fine-tuning Tool Usage

Collection of papers that utilize reinforcement learning to enhance tool usage and function calling.

Toolformer: Language Models Can Teach Themselves to Use Tools

Paper • 2302.04761 • Published Feb 9, 2023 • 11
On the Tool Manipulation Capability of Open-source Large Language Models

Paper • 2305.16504 • Published May 25, 2023 • 2
WebRL: Training LLM Web Agents via Self-Evolving Online Curriculum Reinforcement Learning

Paper • 2411.02337 • Published Nov 4, 2024 • 35

Toolformer: Language Models Can Teach Themselves to Use Tools

Paper • 2302.04761 • Published Feb 9, 2023 • 11

PET-SQL: A Prompt-enhanced Two-stage Text-to-SQL Framework with Cross-consistency

Paper • 2403.09732 • Published Mar 13, 2024 • 1
Toolformer: Language Models Can Teach Themselves to Use Tools

Paper • 2302.04761 • Published Feb 9, 2023 • 11

Papers - Fine-tuning - Prompts

Toolformer: Language Models Can Teach Themselves to Use Tools

Paper • 2302.04761 • Published Feb 9, 2023 • 11
OpenBezoar: Small, Cost-Effective and Open Models Trained on Mixes of Instruction Data

Paper • 2404.12195 • Published Apr 18, 2024 • 12

Papers - Training Research - Exemplary Prompts

Toolformer: Language Models Can Teach Themselves to Use Tools

Paper • 2302.04761 • Published Feb 9, 2023 • 11

Papers - Training - Fitness Score

Toolformer: Language Models Can Teach Themselves to Use Tools

Paper • 2302.04761 • Published Feb 9, 2023 • 11

Papers - Fine-tuning

Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning

Paper • 2310.20587 • Published Oct 31, 2023 • 18
SELF: Language-Driven Self-Evolution for Large Language Model

Paper • 2310.00533 • Published Oct 1, 2023 • 2
QLoRA: Efficient Finetuning of Quantized LLMs

Paper • 2305.14314 • Published May 23, 2023 • 50
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 44

Toolformer: Language Models Can Teach Themselves to Use Tools

Paper • 2302.04761 • Published Feb 9, 2023 • 11

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