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Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code
Paper • 2311.07989 • Published • 26 -
Advancing Requirements Engineering through Generative AI: Assessing the Role of LLMs
Paper • 2310.13976 • Published -
PuoBERTa: Training and evaluation of a curated language model for Setswana
Paper • 2310.09141 • Published • 1 -
HugNLP: A Unified and Comprehensive Library for Natural Language Processing
Paper • 2302.14286 • Published
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Collections including paper arxiv:2311.07989
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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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Technical Report: Large Language Models can Strategically Deceive their Users when Put Under Pressure
Paper • 2311.07590 • Published • 17 -
Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code
Paper • 2311.07989 • Published • 26 -
Llamas Know What GPTs Don't Show: Surrogate Models for Confidence Estimation
Paper • 2311.08877 • Published • 7 -
A Challenger to GPT-4V? Early Explorations of Gemini in Visual Expertise
Paper • 2312.12436 • Published • 15
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MFTCoder: Boosting Code LLMs with Multitask Fine-Tuning
Paper • 2311.02303 • Published • 12 -
CodeFuse-13B: A Pretrained Multi-lingual Code Large Language Model
Paper • 2310.06266 • Published • 2 -
CoBa: Convergence Balancer for Multitask Finetuning of Large Language Models
Paper • 2410.06741 • Published • 3 -
Every Sample Matters: Leveraging Mixture-of-Experts and High-Quality Data for Efficient and Accurate Code LLM
Paper • 2503.17793 • Published • 23
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Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code
Paper • 2311.07989 • Published • 26 -
SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
Paper • 2310.06770 • Published • 9 -
CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution
Paper • 2401.03065 • Published • 11 -
Copilot Evaluation Harness: Evaluating LLM-Guided Software Programming
Paper • 2402.14261 • Published • 11
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Alpha-CLIP: A CLIP Model Focusing on Wherever You Want
Paper • 2312.03818 • Published • 34 -
Scaling Laws of Synthetic Images for Model Training ... for Now
Paper • 2312.04567 • Published • 9 -
Large Language Models for Mathematicians
Paper • 2312.04556 • Published • 13 -
LooseControl: Lifting ControlNet for Generalized Depth Conditioning
Paper • 2312.03079 • Published • 16
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ChatAnything: Facetime Chat with LLM-Enhanced Personas
Paper • 2311.06772 • Published • 35 -
Fine-tuning Language Models for Factuality
Paper • 2311.08401 • Published • 30 -
Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code
Paper • 2311.07989 • Published • 26 -
Instruction-Following Evaluation for Large Language Models
Paper • 2311.07911 • Published • 22
-
Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code
Paper • 2311.07989 • Published • 26 -
Advancing Requirements Engineering through Generative AI: Assessing the Role of LLMs
Paper • 2310.13976 • Published -
PuoBERTa: Training and evaluation of a curated language model for Setswana
Paper • 2310.09141 • Published • 1 -
HugNLP: A Unified and Comprehensive Library for Natural Language Processing
Paper • 2302.14286 • Published
-
MFTCoder: Boosting Code LLMs with Multitask Fine-Tuning
Paper • 2311.02303 • Published • 12 -
CodeFuse-13B: A Pretrained Multi-lingual Code Large Language Model
Paper • 2310.06266 • Published • 2 -
CoBa: Convergence Balancer for Multitask Finetuning of Large Language Models
Paper • 2410.06741 • Published • 3 -
Every Sample Matters: Leveraging Mixture-of-Experts and High-Quality Data for Efficient and Accurate Code LLM
Paper • 2503.17793 • Published • 23
-
Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code
Paper • 2311.07989 • Published • 26 -
SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
Paper • 2310.06770 • Published • 9 -
CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution
Paper • 2401.03065 • Published • 11 -
Copilot Evaluation Harness: Evaluating LLM-Guided Software Programming
Paper • 2402.14261 • Published • 11
-
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
-
Alpha-CLIP: A CLIP Model Focusing on Wherever You Want
Paper • 2312.03818 • Published • 34 -
Scaling Laws of Synthetic Images for Model Training ... for Now
Paper • 2312.04567 • Published • 9 -
Large Language Models for Mathematicians
Paper • 2312.04556 • Published • 13 -
LooseControl: Lifting ControlNet for Generalized Depth Conditioning
Paper • 2312.03079 • Published • 16
-
Technical Report: Large Language Models can Strategically Deceive their Users when Put Under Pressure
Paper • 2311.07590 • Published • 17 -
Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code
Paper • 2311.07989 • Published • 26 -
Llamas Know What GPTs Don't Show: Surrogate Models for Confidence Estimation
Paper • 2311.08877 • Published • 7 -
A Challenger to GPT-4V? Early Explorations of Gemini in Visual Expertise
Paper • 2312.12436 • Published • 15
-
ChatAnything: Facetime Chat with LLM-Enhanced Personas
Paper • 2311.06772 • Published • 35 -
Fine-tuning Language Models for Factuality
Paper • 2311.08401 • Published • 30 -
Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code
Paper • 2311.07989 • Published • 26 -
Instruction-Following Evaluation for Large Language Models
Paper • 2311.07911 • Published • 22