Lingyong Yan

Orcid: 0000-0002-6547-1984

According to our database1, Lingyong Yan authored at least 27 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
MAIR: A Massive Benchmark for Evaluating Instructed Retrieval.
CoRR, 2024

MACPO: Weak-to-Strong Alignment via Multi-Agent Contrastive Preference Optimization.
CoRR, 2024

Chain of Tools: Large Language Model is an Automatic Multi-tool Learner.
CoRR, 2024

The Real, the Better: Aligning Large Language Models with Online Human Behaviors.
CoRR, 2024

Learning to Use Tools via Cooperative and Interactive Agents.
CoRR, 2024

Knowing What LLMs DO NOT Know: A Simple Yet Effective Self-Detection Method.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

ATM: Adversarial Tuning Multi-agent System Makes a Robust Retrieval-Augmented Generator.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Learning to Use Tools via Cooperative and Interactive Agents.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

KnowTuning: Knowledge-aware Fine-tuning for Large Language Models.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Retrieving, Rethinking and Revising: The Chain-of-Verification Can Improve Retrieval Augmented Generation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

MAIR: A Massive Benchmark for Evaluating Instructed Retrieval.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Improving the Robustness of Large Language Models via Consistency Alignment.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

2023
Instruction Distillation Makes Large Language Models Efficient Zero-shot Rankers.
CoRR, 2023

DiQAD: A Benchmark Dataset for End-to-End Open-domain Dialogue Assessment.
CoRR, 2023

Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agent.
CoRR, 2023

Learning to Tokenize for Generative Retrieval.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

DiQAD: A Benchmark Dataset for Open-domain Dialogue Quality Assessment.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agents.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2021
Progressive Adversarial Learning for Bootstrapping: A Case Study on Entity Set Expansion.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

From Learning-to-Match to Learning-to-Discriminate: Global Prototype Learning for Few-shot Relation Classification.
Proceedings of the Chinese Computational Linguistics - 20th China National Conference, 2021

Element Intervention for Open Relation Extraction.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Knowledgeable or Educated Guess? Revisiting Language Models as Knowledge Bases.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020
From Bag of Sentences to Document: Distantly Supervised Relation Extraction via Machine Reading Comprehension.
CoRR, 2020

Global Bootstrapping Neural Network for Entity Set Expansion.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Reinforcement Learning for Clue Selection in Web-Based Entity Translation Mining.
Proceedings of the Knowledge Graph and Semantic Computing: Knowledge Graph and Cognitive Intelligence, 2020

End-to-End Bootstrapping Neural Network for Entity Set Expansion.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Learning to Bootstrap for Entity Set Expansion.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019


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