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From Code Foundation Models to Agents and Applications: A Practical Guide to Code Intelligence
Paper • 2511.18538 • Published • 249 -
Neural Machine Translation by Jointly Learning to Align and Translate
Paper • 1409.0473 • Published • 7 -
Attention Is All You Need
Paper • 1706.03762 • Published • 105 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 24
Collections
Discover the best community collections!
Collections including paper arxiv:2106.09685
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Agents: An Open-source Framework for Autonomous Language Agents
Paper • 2309.07870 • Published • 42 -
Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game
Paper • 2310.18940 • Published -
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
Paper • 2504.01990 • Published • 300 -
AutoWebGLM: Bootstrap And Reinforce A Large Language Model-based Web Navigating Agent
Paper • 2404.03648 • Published • 30
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Attention Is All You Need
Paper • 1706.03762 • Published • 105 -
LoRA: Low-Rank Adaptation of Large Language Models
Paper • 2106.09685 • Published • 54 -
Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity
Paper • 2101.03961 • Published • 13 -
Proximal Policy Optimization Algorithms
Paper • 1707.06347 • Published • 11
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A LoRA-Based Approach to Fine-Tuning LLMs for Educational Guidance in Resource-Constrained Settings
Paper • 2504.15610 • Published • 1 -
Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models
Paper • 2502.13533 • Published • 13 -
LoRA-SP: Streamlined Partial Parameter Adaptation for Resource-Efficient Fine-Tuning of Large Language Models
Paper • 2403.08822 • Published -
LoRA-Pro: Are Low-Rank Adapters Properly Optimized?
Paper • 2407.18242 • Published
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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 • 24 -
On the Opportunities and Risks of Foundation Models
Paper • 2108.07258 • Published • 1 -
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks
Paper • 2204.07705 • Published • 2
-
From Code Foundation Models to Agents and Applications: A Practical Guide to Code Intelligence
Paper • 2511.18538 • Published • 249 -
Neural Machine Translation by Jointly Learning to Align and Translate
Paper • 1409.0473 • Published • 7 -
Attention Is All You Need
Paper • 1706.03762 • Published • 105 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 24
-
Attention Is All You Need
Paper • 1706.03762 • Published • 105 -
LoRA: Low-Rank Adaptation of Large Language Models
Paper • 2106.09685 • Published • 54 -
Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity
Paper • 2101.03961 • Published • 13 -
Proximal Policy Optimization Algorithms
Paper • 1707.06347 • Published • 11
-
A LoRA-Based Approach to Fine-Tuning LLMs for Educational Guidance in Resource-Constrained Settings
Paper • 2504.15610 • Published • 1 -
Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models
Paper • 2502.13533 • Published • 13 -
LoRA-SP: Streamlined Partial Parameter Adaptation for Resource-Efficient Fine-Tuning of Large Language Models
Paper • 2403.08822 • Published -
LoRA-Pro: Are Low-Rank Adapters Properly Optimized?
Paper • 2407.18242 • Published
-
Agents: An Open-source Framework for Autonomous Language Agents
Paper • 2309.07870 • Published • 42 -
Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game
Paper • 2310.18940 • Published -
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
Paper • 2504.01990 • Published • 300 -
AutoWebGLM: Bootstrap And Reinforce A Large Language Model-based Web Navigating Agent
Paper • 2404.03648 • Published • 30
-
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 • 24 -
On the Opportunities and Risks of Foundation Models
Paper • 2108.07258 • Published • 1 -
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks
Paper • 2204.07705 • Published • 2