XLANG NLP Lab (xlang-ai)

XLANG NLP Lab

xlang-ai

Geek Repo

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

Home Page:https://xlang.ai/

Twitter:@XLangNLP

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XLANG NLP Lab's repositories

OpenAgents

[COLM 2024] OpenAgents: An Open Platform for Language Agents in the Wild

Language:PythonLicense:Apache-2.0Stargazers:3796Issues:42Issues:98

instructor-embedding

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

Language:PythonLicense:Apache-2.0Stargazers:1795Issues:17Issues:107

OSWorld

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

Language:PythonLicense:Apache-2.0Stargazers:1067Issues:24Issues:22

UnifiedSKG

[EMNLP 2022] Unifying and multi-tasking structured knowledge grounding with language models

Language:PythonLicense:Apache-2.0Stargazers:542Issues:11Issues:39

xlang-paper-reading

Paper collection on building and evaluating language model agents via executable language grounding

Binder

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

Language:PythonLicense:Apache-2.0Stargazers:289Issues:10Issues:8

DS-1000

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

Language:PythonLicense:CC-BY-SA-4.0Stargazers:207Issues:9Issues:19

text2reward

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

Language:Jupyter NotebookStargazers:107Issues:6Issues:2

icl-selective-annotation

[ICLR 2023] Code for our paper "Selective Annotation Makes Language Models Better Few-Shot Learners"

batch-prompting

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

Spider2-V

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

Language:Jupyter NotebookLicense:Apache-2.0Stargazers:59Issues:2Issues:0
Language:PythonLicense:Apache-2.0Stargazers:43Issues:6Issues:2

diagrams_toolkit

Source code for diagrams in the paper of NLPers from HKU.

Language:PythonLicense:MITStargazers:5Issues:4Issues:0
Language:PythonLicense:CC-BY-4.0Stargazers:4Issues:4Issues:0