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End-to-End Goal-Driven Web Navigation
Paper • 1602.02261 • Published -
Learning Language Games through Interaction
Paper • 1606.02447 • Published -
Naturalizing a Programming Language via Interactive Learning
Paper • 1704.06956 • Published -
Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration
Paper • 1802.08802 • Published • 1
Collections
Discover the best community collections!
Collections including paper arxiv:2210.03629
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ReAct: Synergizing Reasoning and Acting in Language Models
Paper • 2210.03629 • Published • 27 -
If LLM Is the Wizard, Then Code Is the Wand: A Survey on How Code Empowers Large Language Models to Serve as Intelligent Agents
Paper • 2401.00812 • Published • 11 -
DynaSaur: Large Language Agents Beyond Predefined Actions
Paper • 2411.01747 • Published • 36 -
Executable Code Actions Elicit Better LLM Agents
Paper • 2402.01030 • Published • 156
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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 • 297 -
AutoWebGLM: Bootstrap And Reinforce A Large Language Model-based Web Navigating Agent
Paper • 2404.03648 • Published • 29
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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 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 19 -
On the Opportunities and Risks of Foundation Models
Paper • 2108.07258 • Published -
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks
Paper • 2204.07705 • Published • 1
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End-to-End Goal-Driven Web Navigation
Paper • 1602.02261 • Published -
Learning Language Games through Interaction
Paper • 1606.02447 • Published -
Naturalizing a Programming Language via Interactive Learning
Paper • 1704.06956 • Published -
Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration
Paper • 1802.08802 • Published • 1
-
Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning
Paper • 2211.04325 • Published -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 19 -
On the Opportunities and Risks of Foundation Models
Paper • 2108.07258 • Published -
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks
Paper • 2204.07705 • Published • 1
-
ReAct: Synergizing Reasoning and Acting in Language Models
Paper • 2210.03629 • Published • 27 -
If LLM Is the Wizard, Then Code Is the Wand: A Survey on How Code Empowers Large Language Models to Serve as Intelligent Agents
Paper • 2401.00812 • Published • 11 -
DynaSaur: Large Language Agents Beyond Predefined Actions
Paper • 2411.01747 • Published • 36 -
Executable Code Actions Elicit Better LLM Agents
Paper • 2402.01030 • Published • 156
-
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 • 297 -
AutoWebGLM: Bootstrap And Reinforce A Large Language Model-based Web Navigating Agent
Paper • 2404.03648 • Published • 29