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A presença pública do Alibaba-NLP no GitHub é focada em tecnologias de busca em IA, com uma ampla gama de repositórios. Entre os projetos notáveis estão DeepResearch, ZeroSearch e VRAG, todos desenvolvidos em Python, refletindo o compromisso da equipe do Tongyi Lab, Alibaba Group, com a pesquisa em inteligência artificial.
Tongyi Deep Research, the Leading Open-source Deep Research Agent
ZeroSearch: Incentivize the Search Capability of LLMs without Searching
Multimodal Retrieval-augmented Generation Framework Built by Tongyi Lab, Alibaba Group.
[EMNLP 2025] ViDoRAG: Visual Document Retrieval-Augmented Generation via Dynamic Iterative Reasoning Agents
Repo for Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-adaptive Planning Agent
[ACL-IJCNLP 2021] Automated Concatenation of Embeddings for Structured Prediction
Repo for NAACL 2025 Paper "Unfolding the Headline: Iterative Self-Questioning for News Retrieval and Timeline Summarization"
An Instruction-tuned Large Language Model for E-commerce
qqr is an RL training framework for open-ended agents.
Hierarchy-Aware Global Model for Hierarchical Text Classification
SeqGPT: An Out-of-the-box Large Language Model for Open Domain Sequence Understanding
[SIGIR 2022] Multi-CPR: A Multi Domain Chinese Dataset for Passage Retrieval
Winner system (DAMO-NLP) of SemEval 2022 MultiCoNER shared task over 10 out of 13 tracks.
Repo for "MaskSearch: A Universal Pre-Training Framework to Enhance Agentic Search Capability"
[ACL-IJCNLP 2021] Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning
[ACL 2020] Structure-Level Knowledge Distillation For Multilingual Sequence Labeling
E2Rank: Your Text Embedding can Also be an Effective and Efficient Listwise Reranker
The code for LaRA Benchmark
Nenhuma descrição fornecida para este repositório.
code for paper 《RankingGPT: Empowering Large Language Models in Text Ranking with Progressive Enhancement》
Code for 'Prototypical Representation Learning for Relation Extraction'.
[EMNLP 2021] MuVER: Improving First-Stage Entity Retrieval with Multi-View Entity Representations
[ICASSP 2022] AISHELL-NER: Named Entity Recognition from Chinese Speech
Coupling Distant Annotation and Adversarial Training for Cross-Domain Chinese Word Segmentation
[ACL 2023] MANNER: A Variational Memory-Augmented Model for Cross Domain Few-Shot Named Entity Recognition
Hybrid List Aware Transformer Reranking
Code for our EMNLP 2020 Paper "AIN: Fast and Accurate Sequence Labeling with Approximate Inference Network"
CDQA: Chinese Dynamic Question Answering Benchmark
Codes for the EMNLP'2020 paper "Predicting Clinical Trial Results by Implicit Evidence Integration".
[ACL-IJCNLP 2021] Structural Knowledge Distillation: Tractably Distilling Information for Structured Predictor
A new evaluation paradigm for deep search that identifies specific LLM failure sources, introduces challenging hint-free datasets with holistic evaluation, and offers a strong baseline incorporating memory and verification.
Source code of paper Improving "Retrieval Augmented Open-Domain Question-Answering with Vectorized Contexts
This is the official repository for the IBKD knowledge distillation method, as described in the paper .
Nenhuma descrição fornecida para este repositório.
[EMNLP 2025] Code for "Detecting Knowledge Boundary of Vision Large Language Models by Sampling-Based Inference"
Nenhuma descrição fornecida para este repositório.
Implementation of NeurIPS 20 paper: Latent Template Induction with Gumbel-CRFs
Implementation of AAAI 21 paper: Nested Named Entity Recognition with Partially Observed TreeCRFs
Nenhuma descrição fornecida para este repositório.
[ACL 2022 Findings] Fusing Heterogeneous Factors with Triaffine Mechanism for Nested Named Entity Recognition
[ACL 2022] Code Synonyms Do Matter: Multiple Synonyms Matching Network for Automatic ICD Coding
Codes and data for Alibaba's winning systems at the TREC Precision Medicine Track 2020.
Implementation of ICLR 21 paper: Probing BERT in Hyperbolic Spaces
Alibaba-NLP desenvolve uma variedade de projetos relacionados a tecnologias de busca em inteligência artificial, incluindo repositórios como DeepResearch, ZeroSearch e VRAG, que são amplamente utilizados na comunidade de pesquisa.
O Alibaba-NLP utiliza principalmente Python em seus projetos. Essa escolha de linguagem permite a implementação de algoritmos complexos e a integração com bibliotecas de aprendizado de máquina.
Sim, todos os repositórios do Alibaba-NLP são públicos. Isso permite que outros desenvolvedores e pesquisadores acessem e contribuam para os projetos, promovendo a colaboração na área de inteligência artificial.
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