Runchuan Zhu
According to our database1,
Runchuan Zhu authored at least 14 papers
between 2023 and 2026.
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Bibliography
2026
Evaluating an evidence-guided reinforcement learning framework in aligning light-parameter large language models with decision-making cognition in psychiatric clinical reasoning.
CoRR, February, 2026
2025
EL4NER: Ensemble Learning for Named Entity Recognition via Multiple Small-Parameter Large Language Models.
CoRR, May, 2025
Evaluating Large Language Model with Knowledge Oriented Language Specific Simple Question Answering.
CoRR, May, 2025
PM4Bench: A Parallel Multilingual Multi-Modal Multi-task Benchmark for Large Vision Language Model.
CoRR, March, 2025
CoRR, February, 2025
GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation.
CoRR, February, 2025
GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025
3DS: Medical Domain Adaptation of LLMs via Decomposed Difficulty-based Data Selection.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025
Parenting: Optimizing Knowledge Selection of Retrieval-Augmented Language Models with Parameter Decoupling and Tailored Tuning.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025
Utilize the Flow Before Stepping into the Same River Twice: Certainty Represented Knowledge Flow for Refusal-Aware Instruction Tuning.
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025
KnowPO: Knowledge-Aware Preference Optimization for Controllable Knowledge Selection in Retrieval-Augmented Language Models.
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025
2024
3DS: Decomposed Difficulty Data Selection's Case Study on LLM Medical Domain Adaptation.
CoRR, 2024
2023
CoRR, 2023