RA-DIT: Retrieval-Augmented Dual Instruction Tuning
Paper
• 2310.01352 • Published
• 7
Papers
Key papers
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Self-Consistency Improves Chain of Thought Reasoning in Language Models
Paper • 2203.11171 • Published • 5 -
MemGPT: Towards LLMs as Operating Systems
Paper • 2310.08560 • Published • 9 -
Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models
Paper • 2310.06117 • Published • 2 -
Large Language Models Understand and Can be Enhanced by Emotional Stimuli
Paper • 2307.11760 • Published • 1 -
TopicGPT: A Prompt-based Topic Modeling Framework
Paper • 2311.01449 • Published • 1 -
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Paper • 2305.18290 • Published • 64 -
Query Rewriting for Retrieval-Augmented Large Language Models
Paper • 2305.14283 • Published -
FireAct: Toward Language Agent Fine-tuning
Paper • 2310.05915 • Published • 2 -
Large Language Models as Analogical Reasoners
Paper • 2310.01714 • Published • 16 -
Cognitive Architectures for Language Agents
Paper • 2309.02427 • Published • 8 -
Chain-of-Verification Reduces Hallucination in Large Language Models
Paper • 2309.11495 • Published • 40 -
From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting
Paper • 2309.04269 • Published • 34 -
Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback
Paper • 2305.10142 • Published • 1 -
MetaGPT: Meta Programming for Multi-Agent Collaborative Framework
Paper • 2308.00352 • Published • 2 -
PAL: Program-aided Language Models
Paper • 2211.10435 • Published • 4 -
Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Paper • 2305.10601 • Published • 15 -
Training language models to follow instructions with human feedback
Paper • 2203.02155 • Published • 24 -
Symbol tuning improves in-context learning in language models
Paper • 2305.08298 • Published • 3 -
Small Models are Valuable Plug-ins for Large Language Models
Paper • 2305.08848 • Published • 5 -
Role-Play with Large Language Models
Paper • 2305.16367 • Published • 4 -
Reframing Instructional Prompts to GPTk's Language
Paper • 2109.07830 • Published • 1 -
Prompting Is Programming: A Query Language for Large Language Models
Paper • 2212.06094 • Published • 1 -
Precise Zero-Shot Dense Retrieval without Relevance Labels
Paper • 2212.10496 • Published • 5 -
Language Models can Solve Computer Tasks
Paper • 2303.17491 • Published -
Language Models as Agent Models
Paper • 2212.01681 • Published -
Large Language Models are Zero-Shot Reasoners
Paper • 2205.11916 • Published • 3 -
Generative Agents: Interactive Simulacra of Human Behavior
Paper • 2304.03442 • Published • 14 -
Decomposed Prompting: A Modular Approach for Solving Complex Tasks
Paper • 2210.02406 • Published • 1 -
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Paper • 2201.11903 • Published • 15 -
Active Retrieval Augmented Generation
Paper • 2305.06983 • Published • 3 -
ReAct: Synergizing Reasoning and Acting in Language Models
Paper • 2210.03629 • Published • 33 -
Orca 2: Teaching Small Language Models How to Reason
Paper • 2311.11045 • Published • 77 -
Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine
Paper • 2311.16452 • Published • 2