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Discover the best community collections!

Collections including paper arxiv:2401.17464

LLaMA: Open and Efficient Foundation Language Models

Paper • 2302.13971 • Published Feb 27, 2023 • 13
Efficient Tool Use with Chain-of-Abstraction Reasoning

Paper • 2401.17464 • Published Jan 30, 2024 • 17
MoMa: Efficient Early-Fusion Pre-training with Mixture of Modality-Aware Experts

Paper • 2407.21770 • Published Jul 31, 2024 • 22
Agent-as-a-Judge: Evaluate Agents with Agents

Paper • 2410.10934 • Published Oct 14, 2024 • 18

Attention Is All You Need

Paper • 1706.03762 • Published Jun 12, 2017 • 50
LLaMA: Open and Efficient Foundation Language Models

Paper • 2302.13971 • Published Feb 27, 2023 • 13
Efficient Tool Use with Chain-of-Abstraction Reasoning

Paper • 2401.17464 • Published Jan 30, 2024 • 17
MoMa: Efficient Early-Fusion Pre-training with Mixture of Modality-Aware Experts

Paper • 2407.21770 • Published Jul 31, 2024 • 22

Tool use papers

Papers on agent tool use, agency over agents, and multi-agent systems

Efficient Tool Use with Chain-of-Abstraction Reasoning

Paper • 2401.17464 • Published Jan 30, 2024 • 17
ReAct: Synergizing Reasoning and Acting in Language Models

Paper • 2210.03629 • Published Oct 6, 2022 • 15

Tool Usage (w/VLMs)

MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action

Paper • 2303.11381 • Published Mar 20, 2023 • 2
Efficient Tool Use with Chain-of-Abstraction Reasoning

Paper • 2401.17464 • Published Jan 30, 2024 • 17
Salesforce/xlam-function-calling-60k

Viewer • Updated Jul 19, 2024 • 60k • 1.81k • 403

Prompting papers

Important papers to read related to AI prompting research

Efficient Tool Use with Chain-of-Abstraction Reasoning

Paper • 2401.17464 • Published Jan 30, 2024 • 17
An automatically discovered chain-of-thought prompt generalizes to novel models and datasets

Paper • 2305.02897 • Published May 4, 2023

Chain-of-Thought Reasoning Without Prompting

Paper • 2402.10200 • Published Feb 15, 2024 • 104
How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15, 2024 • 40
BitDelta: Your Fine-Tune May Only Be Worth One Bit

Paper • 2402.10193 • Published Feb 15, 2024 • 19
A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts

Paper • 2402.09727 • Published Feb 15, 2024 • 36

Tool Use | Function Calling

Efficient Tool Use with Chain-of-Abstraction Reasoning

Paper • 2401.17464 • Published Jan 30, 2024 • 17

Efficient Tool Use with Chain-of-Abstraction Reasoning

Paper • 2401.17464 • Published Jan 30, 2024 • 17
Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation

Paper • 2401.15688 • Published Jan 28, 2024 • 11
SliceGPT: Compress Large Language Models by Deleting Rows and Columns

Paper • 2401.15024 • Published Jan 26, 2024 • 69
From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalities

Paper • 2401.15071 • Published Jan 26, 2024 • 35

Efficient Tool Use with Chain-of-Abstraction Reasoning

Paper • 2401.17464 • Published Jan 30, 2024 • 17

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 22
Efficient Tool Use with Chain-of-Abstraction Reasoning

Paper • 2401.17464 • Published Jan 30, 2024 • 17
ReFT: Reasoning with Reinforced Fine-Tuning

Paper • 2401.08967 • Published Jan 17, 2024 • 29
The Impact of Reasoning Step Length on Large Language Models

Paper • 2401.04925 • Published Jan 10, 2024 • 16

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