XLANG NLP Lab
Building language model agents that ground language instructions into code or actions executable in real-world environments
Pinned Repositories
Binder
[ICLR 2023] Code for the paper "Binding Language Models in Symbolic Languages"
DS-1000
[ICML 2023] Data and code release for the paper "DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation".
icl-selective-annotation
[ICLR 2023] Code for our paper "Selective Annotation Makes Language Models Better Few-Shot Learners"
instructor-embedding
[ACL 2023] One Embedder, Any Task: Instruction-Finetuned Text Embeddings
OpenAgents
[COLM 2024] OpenAgents: An Open Platform for Language Agents in the Wild
OSWorld
[NeurIPS 2024] OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments
Spider2-V
[NeurIPS 2024] Spider2-V: How Far Are Multimodal Agents From Automating Data Science and Engineering Workflows?
text2reward
[ICLR 2024] Code for the paper "Text2Reward: Automated Dense Reward Function Generation for Reinforcement Learning"
UnifiedSKG
[EMNLP 2022] Unifying and multi-tasking structured knowledge grounding with language models
xlang-paper-reading
Paper collection on building and evaluating language model agents via executable language grounding
XLANG NLP Lab's Repositories
xlang-ai/OpenAgents
[COLM 2024] OpenAgents: An Open Platform for Language Agents in the Wild
xlang-ai/instructor-embedding
[ACL 2023] One Embedder, Any Task: Instruction-Finetuned Text Embeddings
xlang-ai/OSWorld
[NeurIPS 2024] OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments
xlang-ai/UnifiedSKG
[EMNLP 2022] Unifying and multi-tasking structured knowledge grounding with language models
xlang-ai/xlang-paper-reading
Paper collection on building and evaluating language model agents via executable language grounding
xlang-ai/Binder
[ICLR 2023] Code for the paper "Binding Language Models in Symbolic Languages"
xlang-ai/DS-1000
[ICML 2023] Data and code release for the paper "DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation".
xlang-ai/Spider2
Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows
xlang-ai/text2reward
[ICLR 2024] Code for the paper "Text2Reward: Automated Dense Reward Function Generation for Reinforcement Learning"
xlang-ai/Spider2-V
[NeurIPS 2024] Spider2-V: How Far Are Multimodal Agents From Automating Data Science and Engineering Workflows?
xlang-ai/icl-selective-annotation
[ICLR 2023] Code for our paper "Selective Annotation Makes Language Models Better Few-Shot Learners"
xlang-ai/batch-prompting
[EMNLP 2023 Industry Track] A simple prompting approach that enables the LLMs to run inference in batches.
xlang-ai/BRIGHT
BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval
xlang-ai/arks
xlang-ai/diagrams_toolkit
Source code for diagrams in the paper of NLPers from HKU.
xlang-ai/.github