Skip to content
@xlang-ai

XLANG NLP Lab

Building language model agents that ground language instructions into code or actions executable in real-world environments

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.

Pinned Loading

  1. OSWorld OSWorld Public

    OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments

    Python 1k 125

  2. OpenAgents OpenAgents Public

    OpenAgents: An Open Platform for Language Agents in the Wild

    Python 3.7k 398

  3. instructor-embedding instructor-embedding Public

    [ACL 2023] One Embedder, Any Task: Instruction-Finetuned Text Embeddings

    Python 1.8k 131

  4. text2reward text2reward Public

    [ICLR 2024] Code for the paper "Text2Reward: Automated Dense Reward Function Generation for Reinforcement Learning"

    Jupyter Notebook 104 5

  5. Binder Binder Public

    [ICLR 2023] Code for the paper "Binding Language Models in Symbolic Languages"

    Python 288 33

  6. DS-1000 DS-1000 Public

    [ICML 2023] Data and code release for the paper "DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation".

    Python 203 24

Repositories

Showing 10 of 15 repositories
  • Spider2-V Public

    Spider2-V: How Far Are Multimodal Agents From Automating Data Science and Engineering Workflows?

    xlang-ai/Spider2-V’s past year of commit activity
    Jupyter Notebook 18 Apache-2.0 0 0 0 Updated Jun 24, 2024
  • OSWorld Public

    OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments

    xlang-ai/OSWorld’s past year of commit activity
    Python 1,028 Apache-2.0 125 4 0 Updated Jun 23, 2024
  • arks Public
    xlang-ai/arks’s past year of commit activity
    Python 41 Apache-2.0 6 2 0 Updated Jun 16, 2024
  • BRIGHT Public
    xlang-ai/BRIGHT’s past year of commit activity
    Python 4 CC-BY-4.0 0 0 0 Updated Jun 13, 2024
  • OpenAgents Public

    OpenAgents: An Open Platform for Language Agents in the Wild

    xlang-ai/OpenAgents’s past year of commit activity
    Python 3,718 Apache-2.0 398 11 2 Updated May 28, 2024
  • DS-1000 Public

    [ICML 2023] Data and code release for the paper "DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation".

    xlang-ai/DS-1000’s past year of commit activity
    Python 203 CC-BY-SA-4.0 24 2 0 Updated Apr 29, 2024
  • 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
    318 11 0 0 Updated Apr 29, 2024
  • instructor-embedding Public

    [ACL 2023] One Embedder, Any Task: Instruction-Finetuned Text Embeddings

    xlang-ai/instructor-embedding’s past year of commit activity
    Python 1,771 Apache-2.0 131 27 2 Updated Apr 24, 2024
  • batch-prompting Public

    [EMNLP 2023 Industry Track] A simple prompting approach that enables the LLMs to run inference in batches.

    xlang-ai/batch-prompting’s past year of commit activity
    Python 60 5 1 1 Updated Mar 8, 2024
  • 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
    Jupyter Notebook 104 5 1 0 Updated Dec 30, 2023

People

This organization has no public members. You must be a member to see who’s a part of this organization.

Top languages

Loading…

Most used topics

Loading…