Haoran Que

According to our database1, Haoran Que authored at least 16 papers between 2023 and 2026.

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Timeline

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Bibliography

2026
COIG-P: A High-Quality and Large-Scale Chinese Preference Dataset for Alignment with Human Values.
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2026, 2026

2025
Scaling Latent Reasoning via Looped Language Models.
CoRR, October, 2025

Reverse-Engineered Reasoning for Open-Ended Generation.
CoRR, September, 2025

A Comprehensive Survey on Long Context Language Modeling.
CoRR, March, 2025

MIO: A Foundation Model on Multimodal Tokens.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

PIC: Unlocking Long-Form Text Generation Capabilities of Large Language Models via Position ID Compression.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

Enhancing LLMs via High-Knowledge Data Selection.
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024
MIO: A Foundation Model on Multimodal Tokens.
CoRR, 2024

HelloBench: Evaluating Long Text Generation Capabilities of Large Language Models.
CoRR, 2024

E^2-LLM: Efficient and Extreme Length Extension of Large Language Models.
CoRR, 2024

D-CPT Law: Domain-specific Continual Pre-Training Scaling Law for Large Language Models.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

DDK: Distilling Domain Knowledge for Efficient Large Language Models.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

RoleAgent: Building, Interacting, and Benchmarking High-quality Role-Playing Agents from Scripts.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

E2-LLM: Efficient and Extreme Length Extension of Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models.
CoRR, 2023


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