Welcome to the Executable Language Grounding (XLANG) Lab! We are part of the HKU NLP Group at the University of Hong Kong. XLang focuses on building language model agents that transform (“grounding”) language instructions into code or actions executable in real-world environments, including databases (data agent), web applications (plugins/web agent), and the physical world (robotic agent) etc,. It lies at the heart of language model agents or natural language interfaces that can interact with and learn from these real-world environments to facilitate human interaction with data analysis, web applications, and robotic instruction through conversation. Recent advances in XLang incorporate techniques such as LLM + external tools, code generation, semantic parsing, and dialog or interactive systems.
XLANG NLP Lab
Building language model agents that ground language instructions into code or actions executable in real-world environments
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Repositories
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- text2reward Public
[ICLR 2024] Code for the paper "Text2Reward: Automated Dense Reward Function Generation for Reinforcement Learning"
xlang-ai/text2reward’s past year of commit activity - instructor-embedding Public
[ACL 2023] One Embedder, Any Task: Instruction-Finetuned Text Embeddings
xlang-ai/instructor-embedding’s past year of commit activity - xlang-paper-reading Public
Paper collection on building and evaluating language model agents via executable language grounding
xlang-ai/xlang-paper-reading’s past year of commit activity
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