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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 84 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
Collections
Discover the best community collections!
Collections including paper arxiv:2402.13064
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AgentInstruct: Toward Generative Teaching with Agentic Flows
Paper • 2407.03502 • Published • 50 -
Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing
Paper • 2406.08464 • Published • 71 -
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
Paper • 2404.14219 • Published • 257 -
DataDreamer: A Tool for Synthetic Data Generation and Reproducible LLM Workflows
Paper • 2402.10379 • Published • 31
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Textbooks Are All You Need
Paper • 2306.11644 • Published • 146 -
Textbooks Are All You Need II: phi-1.5 technical report
Paper • 2309.05463 • Published • 88 -
TinyStories: How Small Can Language Models Be and Still Speak Coherent English?
Paper • 2305.07759 • Published • 36 -
Scaling Synthetic Data Creation with 1,000,000,000 Personas
Paper • 2406.20094 • Published • 104
-
DataDreamer: A Tool for Synthetic Data Generation and Reproducible LLM Workflows
Paper • 2402.10379 • Published • 31 -
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Paper • 2402.13064 • Published • 50 -
Qwen/Qwen2.5-Coder-14B-Instruct
Text Generation • 15B • Updated • 97.3k • • 129 -
670
Open Deep-Research
🏆OpenAI's Deep Research, but open
-
Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling
Paper • 2401.16380 • Published • 50 -
Best Practices and Lessons Learned on Synthetic Data for Language Models
Paper • 2404.07503 • Published • 31 -
WizardLM: Empowering Large Language Models to Follow Complex Instructions
Paper • 2304.12244 • Published • 13 -
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Paper • 2402.13064 • Published • 50
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Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
ReFT: Reasoning with Reinforced Fine-Tuning
Paper • 2401.08967 • Published • 31 -
Tuning Language Models by Proxy
Paper • 2401.08565 • Published • 22 -
TrustLLM: Trustworthiness in Large Language Models
Paper • 2401.05561 • Published • 69
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KAN or MLP: A Fairer Comparison
Paper • 2407.16674 • Published • 43 -
MathScale: Scaling Instruction Tuning for Mathematical Reasoning
Paper • 2403.02884 • Published • 17 -
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Paper • 2402.13064 • Published • 50 -
DPTDR: Deep Prompt Tuning for Dense Passage Retrieval
Paper • 2208.11503 • Published
-
Best Practices and Lessons Learned on Synthetic Data for Language Models
Paper • 2404.07503 • Published • 31 -
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences
Paper • 2404.03715 • Published • 62 -
Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing
Paper • 2406.08464 • Published • 71 -
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Paper • 2402.13064 • Published • 50
-
DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data
Paper • 2405.14333 • Published • 41 -
Automatic Data Curation for Self-Supervised Learning: A Clustering-Based Approach
Paper • 2405.15613 • Published • 17 -
DataDreamer: A Tool for Synthetic Data Generation and Reproducible LLM Workflows
Paper • 2402.10379 • Published • 31 -
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Paper • 2402.13064 • Published • 50
-
LLM2LLM: Boosting LLMs with Novel Iterative Data Enhancement
Paper • 2403.15042 • Published • 27 -
Design2Code: How Far Are We From Automating Front-End Engineering?
Paper • 2403.03163 • Published • 97 -
OS-Copilot: Towards Generalist Computer Agents with Self-Improvement
Paper • 2402.07456 • Published • 46 -
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Paper • 2402.13064 • Published • 50
-
Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 84 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
-
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
ReFT: Reasoning with Reinforced Fine-Tuning
Paper • 2401.08967 • Published • 31 -
Tuning Language Models by Proxy
Paper • 2401.08565 • Published • 22 -
TrustLLM: Trustworthiness in Large Language Models
Paper • 2401.05561 • Published • 69
-
AgentInstruct: Toward Generative Teaching with Agentic Flows
Paper • 2407.03502 • Published • 50 -
Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing
Paper • 2406.08464 • Published • 71 -
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
Paper • 2404.14219 • Published • 257 -
DataDreamer: A Tool for Synthetic Data Generation and Reproducible LLM Workflows
Paper • 2402.10379 • Published • 31
-
KAN or MLP: A Fairer Comparison
Paper • 2407.16674 • Published • 43 -
MathScale: Scaling Instruction Tuning for Mathematical Reasoning
Paper • 2403.02884 • Published • 17 -
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Paper • 2402.13064 • Published • 50 -
DPTDR: Deep Prompt Tuning for Dense Passage Retrieval
Paper • 2208.11503 • Published
-
Textbooks Are All You Need
Paper • 2306.11644 • Published • 146 -
Textbooks Are All You Need II: phi-1.5 technical report
Paper • 2309.05463 • Published • 88 -
TinyStories: How Small Can Language Models Be and Still Speak Coherent English?
Paper • 2305.07759 • Published • 36 -
Scaling Synthetic Data Creation with 1,000,000,000 Personas
Paper • 2406.20094 • Published • 104
-
Best Practices and Lessons Learned on Synthetic Data for Language Models
Paper • 2404.07503 • Published • 31 -
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences
Paper • 2404.03715 • Published • 62 -
Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing
Paper • 2406.08464 • Published • 71 -
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Paper • 2402.13064 • Published • 50
-
DataDreamer: A Tool for Synthetic Data Generation and Reproducible LLM Workflows
Paper • 2402.10379 • Published • 31 -
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Paper • 2402.13064 • Published • 50 -
Qwen/Qwen2.5-Coder-14B-Instruct
Text Generation • 15B • Updated • 97.3k • • 129 -
670
Open Deep-Research
🏆OpenAI's Deep Research, but open
-
DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data
Paper • 2405.14333 • Published • 41 -
Automatic Data Curation for Self-Supervised Learning: A Clustering-Based Approach
Paper • 2405.15613 • Published • 17 -
DataDreamer: A Tool for Synthetic Data Generation and Reproducible LLM Workflows
Paper • 2402.10379 • Published • 31 -
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Paper • 2402.13064 • Published • 50
-
Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling
Paper • 2401.16380 • Published • 50 -
Best Practices and Lessons Learned on Synthetic Data for Language Models
Paper • 2404.07503 • Published • 31 -
WizardLM: Empowering Large Language Models to Follow Complex Instructions
Paper • 2304.12244 • Published • 13 -
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Paper • 2402.13064 • Published • 50
-
LLM2LLM: Boosting LLMs with Novel Iterative Data Enhancement
Paper • 2403.15042 • Published • 27 -
Design2Code: How Far Are We From Automating Front-End Engineering?
Paper • 2403.03163 • Published • 97 -
OS-Copilot: Towards Generalist Computer Agents with Self-Improvement
Paper • 2402.07456 • Published • 46 -
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Paper • 2402.13064 • Published • 50