265 citations · 318 across the 16 of their papers we have counts for
12 papers · 1 filter
Triad: A Framework Leveraging a Multi-Role LLM-based Agent to Solve Knowledge Base Question Answering
Chang Zong, Yuchen Yan, Weiming Lu +4
Recent progress with LLM-based agents has shown promising results across various tasks. However, their use in answering questions from knowledge bases remains largely unexplored. I…
Self-Contrast: Better Reflection Through Inconsistent Solving Perspectives
Wenqi Zhang, Yongliang Shen, Linjuan Wu +4
The reflection capacity of Large Language Model (LLM) has garnered extensive attention. A post-hoc prompting strategy, e.g., reflexion and self-refine, refines LLM's response based…
TaskBench: Benchmarking Large Language Models for Task Automation
Yongliang Shen, Kaitao Song, Xu Tan +6
In recent years, the remarkable progress of large language models (LLMs) has sparked interest in task automation, which involves decomposing complex tasks described by user instruc…
Data-Copilot: Bridging Billions of Data and Humans with Autonomous Workflow
Wenqi Zhang, Yongliang Shen, Zeqi Tan +3
Industries such as finance, meteorology, and energy generate vast amounts of data daily. Efficiently managing, processing, and displaying this data requires specialized expertise a…
PromptNER: Prompt Locating and Typing for Named Entity Recognition
Yongliang Shen, Zeqi Tan, Shuhui Wu +5
Prompt learning is a new paradigm for utilizing pre-trained language models and has achieved great success in many tasks. To adopt prompt learning in the NER task, two kinds of met…
DiffusionNER: Boundary Diffusion for Named Entity Recognition
Yongliang Shen, Kaitao Song, Xu Tan +3
In this paper, we propose DiffusionNER, which formulates the named entity recognition task as a boundary-denoising diffusion process and thus generates named entities from noisy sp…
DAMO-NLP at SemEval-2023 Task 2: A Unified Retrieval-augmented System for Multilingual Named Entity Recognition
Zeqi Tan, Shen Huang, Zixia Jia +8
The MultiCoNER \RNum{2} shared task aims to tackle multilingual named entity recognition (NER) in fine-grained and noisy scenarios, and it inherits the semantic ambiguity and low-c…
HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face
Yongliang Shen, Kaitao Song, Xu Tan +3
Solving complicated AI tasks with different domains and modalities is a key step toward artificial general intelligence. While there are numerous AI models available for various do…
Query-based Instance Discrimination Network for Relational Triple Extraction
Zeqi Tan, Yongliang Shen, Xuming Hu +4
Joint entity and relation extraction has been a core task in the field of information extraction. Recent approaches usually consider the extraction of relational triples from a ste…
Parallel Instance Query Network for Named Entity Recognition
Yongliang Shen, Xiaobin Wang, Zeqi Tan +5
Named entity recognition (NER) is a fundamental task in natural language processing. Recent works treat named entity recognition as a reading comprehension task, constructing type-…
DAMO-NLP at SemEval-2022 Task 11: A Knowledge-based System for Multilingual Named Entity Recognition
Xinyu Wang, Yongliang Shen, Jiong Cai +9
The MultiCoNER shared task aims at detecting semantically ambiguous and complex named entities in short and low-context settings for multiple languages. The lack of contexts makes…
CIL: Contrastive Instance Learning Framework for Distantly Supervised Relation Extraction
Tao Chen, Haizhou Shi, Siliang Tang +3
The journey of reducing noise from distant supervision (DS) generated training data has been started since the DS was first introduced into the relation extraction (RE) task. For t…