265 citations · 318 across the 16 of their papers we have counts for
16 papers
Agent-Pro: Learning to Evolve via Policy-Level Reflection and Optimization
Wenqi Zhang, Ke Tang, Hai Wu +7
Large Language Models (LLMs) exhibit robust problem-solving capabilities for diverse tasks. However, most LLM-based agents are designed as specific task solvers with sophisticated…
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…
Variational Cross-Graph Reasoning and Adaptive Structured Semantics Learning for Compositional Temporal Grounding
Juncheng Li, Siliang Tang, Linchao Zhu +5
Temporal grounding is the task of locating a specific segment from an untrimmed video according to a query sentence. This task has achieved significant momentum in the computer vis…
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…
Citation Trajectory Prediction via Publication Influence Representation Using Temporal Knowledge Graph
Chang Zong, Yueting Zhuang, Weiming Lu +2
Predicting the impact of publications in science and technology has become an important research area, which is useful in various real world scenarios such as technology investment…
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…
Towards Communication-Efficient and Privacy-Preserving Federated Representation Learning
Haizhou Shi, Youcai Zhang, Zijin Shen +4
This paper investigates the feasibility of federated representation learning under the constraints of communication cost and privacy protection. Existing works either conduct annot…
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…