Hongbang Yuan

According to our database1, Hongbang Yuan authored at least 16 papers between 2022 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
What Do LLM Agents Know About Their World? Task2Quiz: A Paradigm for Studying Environment Understanding.
CoRR, January, 2026

Look Light, Think Heavy: What Multimodal Chain-of-Thought Reasoning Can and Cannot Do.
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

2025
Omni-Reward: Towards Generalist Omni-Modal Reward Modeling with Free-Form Preferences.
CoRR, October, 2025

RULE: Reinforcement UnLEarning Achieves Forget-Retain Pareto Optimality.
CoRR, June, 2025

MMR-V: What's Left Unsaid? A Benchmark for Multimodal Deep Reasoning in Videos.
CoRR, June, 2025

Beyond Under-Alignment: Atomic Preference Enhanced Factuality Tuning for Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025

RAG-RewardBench: Benchmarking Reward Models in Retrieval Augmented Generation for Preference Alignment.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

Towards Robust Knowledge Unlearning: An Adversarial Framework for Assessing and Improving Unlearning Robustness in Large Language Models.
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024
AWeCita: Generating Answer with Appropriate and Well-grained Citations Using LLMs.
Data Intell., 2024

RAG-RewardBench: Benchmarking Reward Models in Retrieval Augmented Generation for Preference Alignment.
CoRR, 2024

Beyond Under-Alignment: Atomic Preference Enhanced Factuality Tuning for Large Language Models.
CoRR, 2024

RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models.
Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Whispers that Shake Foundations: Analyzing and Mitigating False Premise Hallucinations in Large Language Models.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Cutting Off the Head Ends the Conflict: A Mechanism for Interpreting and Mitigating Knowledge Conflicts in Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2022
CogKTR: A Knowledge-Enhanced Text Representation Toolkit for Natural Language Understanding.
Proceedings of the The 2022 Conference on Empirical Methods in Natural Language Processing, 2022

CogKGE: A Knowledge Graph Embedding Toolkit and Benchmark for Representing Multi-source and Heterogeneous Knowledge.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 2022


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