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CADCrafter: Generating Computer-Aided Design Models from Unconstrained Images
Paper • 2504.04753 • Published • 1 -
Text2CAD: Generating Sequential CAD Models from Beginner-to-Expert Level Text Prompts
Paper • 2409.17106 • Published • 5 -
Neural Kernel Surface Reconstruction
Paper • 2305.19590 • Published -
FlexiDreamer: Single Image-to-3D Generation with FlexiCubes
Paper • 2404.00987 • Published • 23
Collections
Discover the best community collections!
Collections including paper arxiv:2405.15793
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Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning
Paper • 2211.04325 • Published • 1 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 26 -
On the Opportunities and Risks of Foundation Models
Paper • 2108.07258 • Published • 2 -
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks
Paper • 2204.07705 • Published • 2
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Chain-of-Thought Reasoning Without Prompting
Paper • 2402.10200 • Published • 109 -
Large Language Models Cannot Self-Correct Reasoning Yet
Paper • 2310.01798 • Published • 36 -
Premise Order Matters in Reasoning with Large Language Models
Paper • 2402.08939 • Published • 28 -
Chain of Thought Empowers Transformers to Solve Inherently Serial Problems
Paper • 2402.12875 • Published • 13
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CodeBERT: A Pre-Trained Model for Programming and Natural Languages
Paper • 2002.08155 • Published • 2 -
OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement
Paper • 2402.14658 • Published • 84 -
CodeFusion: A Pre-trained Diffusion Model for Code Generation
Paper • 2310.17680 • Published • 74 -
CodePlan: Repository-level Coding using LLMs and Planning
Paper • 2309.12499 • Published • 80
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Fine-Tuning Language Models from Human Preferences
Paper • 1909.08593 • Published • 4 -
PromptCoT: Synthesizing Olympiad-level Problems for Mathematical Reasoning in Large Language Models
Paper • 2503.02324 • Published -
How Difficulty-Aware Staged Reinforcement Learning Enhances LLMs' Reasoning Capabilities: A Preliminary Experimental Study
Paper • 2504.00829 • Published -
GPG: A Simple and Strong Reinforcement Learning Baseline for Model Reasoning
Paper • 2504.02546 • Published • 2
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Executable Code Actions Elicit Better LLM Agents
Paper • 2402.01030 • Published • 192 -
ReAct: Synergizing Reasoning and Acting in Language Models
Paper • 2210.03629 • Published • 34 -
SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering
Paper • 2405.15793 • Published • 7 -
DevBench: A Comprehensive Benchmark for Software Development
Paper • 2403.08604 • Published • 2
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SMOTE: Synthetic Minority Over-sampling Technique
Paper • 1106.1813 • Published • 1 -
Scikit-learn: Machine Learning in Python
Paper • 1201.0490 • Published • 1 -
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
Paper • 1406.1078 • Published • 1 -
Distributed Representations of Sentences and Documents
Paper • 1405.4053 • Published
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CADCrafter: Generating Computer-Aided Design Models from Unconstrained Images
Paper • 2504.04753 • Published • 1 -
Text2CAD: Generating Sequential CAD Models from Beginner-to-Expert Level Text Prompts
Paper • 2409.17106 • Published • 5 -
Neural Kernel Surface Reconstruction
Paper • 2305.19590 • Published -
FlexiDreamer: Single Image-to-3D Generation with FlexiCubes
Paper • 2404.00987 • Published • 23
-
Fine-Tuning Language Models from Human Preferences
Paper • 1909.08593 • Published • 4 -
PromptCoT: Synthesizing Olympiad-level Problems for Mathematical Reasoning in Large Language Models
Paper • 2503.02324 • Published -
How Difficulty-Aware Staged Reinforcement Learning Enhances LLMs' Reasoning Capabilities: A Preliminary Experimental Study
Paper • 2504.00829 • Published -
GPG: A Simple and Strong Reinforcement Learning Baseline for Model Reasoning
Paper • 2504.02546 • Published • 2
-
Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning
Paper • 2211.04325 • Published • 1 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 26 -
On the Opportunities and Risks of Foundation Models
Paper • 2108.07258 • Published • 2 -
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks
Paper • 2204.07705 • Published • 2
-
Executable Code Actions Elicit Better LLM Agents
Paper • 2402.01030 • Published • 192 -
ReAct: Synergizing Reasoning and Acting in Language Models
Paper • 2210.03629 • Published • 34 -
SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering
Paper • 2405.15793 • Published • 7 -
DevBench: A Comprehensive Benchmark for Software Development
Paper • 2403.08604 • Published • 2
-
Chain-of-Thought Reasoning Without Prompting
Paper • 2402.10200 • Published • 109 -
Large Language Models Cannot Self-Correct Reasoning Yet
Paper • 2310.01798 • Published • 36 -
Premise Order Matters in Reasoning with Large Language Models
Paper • 2402.08939 • Published • 28 -
Chain of Thought Empowers Transformers to Solve Inherently Serial Problems
Paper • 2402.12875 • Published • 13
-
CodeBERT: A Pre-Trained Model for Programming and Natural Languages
Paper • 2002.08155 • Published • 2 -
OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement
Paper • 2402.14658 • Published • 84 -
CodeFusion: A Pre-trained Diffusion Model for Code Generation
Paper • 2310.17680 • Published • 74 -
CodePlan: Repository-level Coding using LLMs and Planning
Paper • 2309.12499 • Published • 80
-
SMOTE: Synthetic Minority Over-sampling Technique
Paper • 1106.1813 • Published • 1 -
Scikit-learn: Machine Learning in Python
Paper • 1201.0490 • Published • 1 -
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
Paper • 1406.1078 • Published • 1 -
Distributed Representations of Sentences and Documents
Paper • 1405.4053 • Published