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DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines
Paper • 2310.03714 • Published • 30 -
ReST meets ReAct: Self-Improvement for Multi-Step Reasoning LLM Agent
Paper • 2312.10003 • Published • 34 -
AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework
Paper • 2308.08155 • Published • 3 -
GAIA: a benchmark for General AI Assistants
Paper • 2311.12983 • Published • 182
Collections
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Collections including paper arxiv:2310.03714
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DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines
Paper • 2312.13382 • Published • 3 -
DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines
Paper • 2310.03714 • Published • 30 -
TextGrad: Automatic "Differentiation" via Text
Paper • 2406.07496 • Published • 26
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Instruction Pre-Training: Language Models are Supervised Multitask Learners
Paper • 2406.14491 • Published • 85 -
Better & Faster Large Language Models via Multi-token Prediction
Paper • 2404.19737 • Published • 73 -
RAFT: Adapting Language Model to Domain Specific RAG
Paper • 2403.10131 • Published • 66 -
The Prompt Report: A Systematic Survey of Prompting Techniques
Paper • 2406.06608 • Published • 52
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AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework
Paper • 2308.08155 • Published • 3 -
GAIA: a benchmark for General AI Assistants
Paper • 2311.12983 • Published • 182 -
HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in HuggingFace
Paper • 2303.17580 • Published • 9 -
More Agents Is All You Need
Paper • 2402.05120 • Published • 51
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Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP
Paper • 2212.14024 • Published • 3 -
DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines
Paper • 2310.03714 • Published • 30 -
DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines
Paper • 2312.13382 • Published • 3 -
ReST meets ReAct: Self-Improvement for Multi-Step Reasoning LLM Agent
Paper • 2312.10003 • Published • 34
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Black-Box Prompt Optimization: Aligning Large Language Models without Model Training
Paper • 2311.04155 • Published • 1 -
DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines
Paper • 2310.03714 • Published • 30 -
OpenPrompt: An Open-source Framework for Prompt-learning
Paper • 2111.01998 • Published • 1
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Self-Rewarding Language Models
Paper • 2401.10020 • Published • 141 -
ReFT: Reasoning with Reinforced Fine-Tuning
Paper • 2401.08967 • Published • 27 -
Tuning Language Models by Proxy
Paper • 2401.08565 • Published • 20 -
TrustLLM: Trustworthiness in Large Language Models
Paper • 2401.05561 • Published • 63
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#InsTag: Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language Models
Paper • 2308.07074 • Published -
Evoke: Evoking Critical Thinking Abilities in LLMs via Reviewer-Author Prompt Editing
Paper • 2310.13855 • Published • 1 -
LIMIT: Less Is More for Instruction Tuning Across Evaluation Paradigms
Paper • 2311.13133 • Published -
Group Preference Optimization: Few-Shot Alignment of Large Language Models
Paper • 2310.11523 • Published
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Detecting Pretraining Data from Large Language Models
Paper • 2310.16789 • Published • 10 -
Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small Models
Paper • 2310.13671 • Published • 18 -
AutoMix: Automatically Mixing Language Models
Paper • 2310.12963 • Published • 14 -
An Emulator for Fine-Tuning Large Language Models using Small Language Models
Paper • 2310.12962 • Published • 14