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Le Yan

This page is a disambiguation page, it actually contains multiple papers from persons of the same or a similar name.

Bibliography

2025

Harnessing Pairwise Ranking Prompting Through Sample-Efficient Ranking Distillation.

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Paul Suganthan G. C.

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Harrie Oosterhuis

CoRR, July, 2025

Adapting Decoder-Based Language Models for Diverse Encoder Downstream Tasks.

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Enrique Alfonseca

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CoRR, March, 2025

Synergistic Systems of Digitalization and Urbanization in Driving Urban Green Development: A Configurational Analysis of China's Yellow River Basin.

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Syst., 2025

Impact of fit between knowledge potential and organizational routine updating on subsidiaries' new product development performance.

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J. Knowl. Manag., 2025

MCRanker: Generating Diverse Criteria On-the-Fly to Improve Pointwise LLM Rankers.

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Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining, 2025

2024

Generating Diverse Criteria On-the-Fly to Improve Point-wise LLM Rankers.

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CoRR, 2024

Beyond Yes and No: Improving Zero-Shot LLM Rankers via Scoring Fine-Grained Relevance Labels.

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Michael Bendersky

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Short Papers, 2024

Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting.

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Michael Bendersky

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024

Consolidating Ranking and Relevance Predictions of Large Language Models through Post-Processing.

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Michael Bendersky

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Harrie Oosterhuis

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

Learning to Rank when Grades Matter.

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CoRR, 2023

RD-Suite: A Benchmark for Ranking Distillation.

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Rama Kumar Pasumarthi

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Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Towards Disentangling Relevance and Bias in Unbiased Learning to Rank.

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Michael Bendersky

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Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Regression Compatible Listwise Objectives for Calibrated Ranking with Binary Relevance.

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Michael Bendersky

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Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

Revisiting Two-tower Models for Unbiased Learning to Rank.

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Michael Bendersky

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Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Scale Calibration of Deep Ranking Models.

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Michael Bendersky

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Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

Rank4Class: A Ranking Formulation for Multiclass Classification.

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Michael Bendersky

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CoRR, 2021

Born Again Neural Rankers.

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Michael Bendersky

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CoRR, 2021

Diversification-Aware Learning to Rank using Distributed Representation.

[DOI]

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Rama Kumar Pasumarthi

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Michael Bendersky

Proceedings of the WWW '21: The Web Conference 2021, 2021

Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees?

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Rama Kumar Pasumarthi

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Michael Bendersky

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Proceedings of the 9th International Conference on Learning Representations, 2021

2019

Event-triggered set-membership filtering for discrete-time memristive neural networks subject to measurement saturation and fadings.

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Neurocomputing, 2019

2017

H<sub>∞</sub> state estimation for memristive neural networks with multiple fading measurements.

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Fuad E. Alsaadi

Neurocomputing, 2017

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