Get started
Author

Dehai Min

Observed name: Min, Dehai
OpenAlex ID: A5121164783
QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation
2026 · Dehai Min, Kailin Zhang, et al. · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · 1
PDF
Reinforcement Learning with Evolving Rubrics as Rewards for Audio Reasoning
2026 · Yu, Fangxu, Feng, Tao, et al. · arXiv (Cornell University)
PDF
Pandora: Leveraging Code-Driven Knowledge Transfer for Unified Structured Knowledge Reasoning
2026 · Yongrui Chen, Junhao He, et al. · IEEE Transactions on Knowledge and Data Engineering
PDF
One Skill, Two Masters: Serving Users and Attackers through Skill Injection
2026 · Hao, Haochang, Min, Dehai, et al. · arXiv (Cornell University)
PDF
QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation
2026 · Association for Computational Linguistics 2026, Cheng, Lu, et al. · Underline Science Inc.
Beyond Math and Code: Lightweight Corpus-Grounded Process Rewards for Factual Question Answering
2026 · Fan, Shicheng, Hao, Haochang, et al. · arXiv (Cornell University)
PDF
Stop When Reasoning Converges: Semantic-Preserving Early Exit for Reasoning Models
2026 · Min, Dehai, Vaccarino, Giovanni, et al. · arXiv (Cornell University)
PDF
Latent Thoughts Tuning: Bridging Context and Reasoning with Fused Information in Latent Tokens
2026 · Liu, Weihao, Min, Dehai, et al. · arXiv (Cornell University)
PDF
EpiQAL: Benchmarking Large Language Models in Epidemiological Question Answering and Reasoning
2026 · Mingyang Wei, Dehai Min, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP)
PDF
Scaling LLM Agent Learning with Data Synthesis: A Comprehensive Survey
2026 · Hanrong Zhang, Yankai Chen, et al.
QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation
2025 · Min, Dehai, Zhang, Kailin, et al. · arXiv (Cornell University)
PDF
Works count: 11
Citation count: 1
H-index: 1
I10-index:
Year
Topic
Type