🔗 Who cites «RetroLLM: Empowering Large Language Models to Retrieve Fine-grained Evidence within Generation»

11 papers of our library cite it (of the 149,439 whose bibliographies we read) · 7 with a page here, the most cited first · ← back to «RetroLLM: Empowering Large Language Models to Retrieve Fine-grained Evidence within Generation»

1. Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement LearningarXiv:2503.09516Bowen Jin, Hansi Zeng, Zhenrui Yue, et al.2025 · 322 citations
2. Search-o1: Agentic Search-Enhanced Large Reasoning ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Xiaoxi Li, Guanting Dong, Jiajie Jin, et al.2025 · 211 citations
3. ZeroSearch: Incentivize the Search Capability of LLMs without SearchingarXiv:2505.04588Hao Sun, Zile Qiao, Jiayan Guo, et al.2025 · 50 citations
4. Hierarchical Document Refinement for Long-context Retrieval-augmented GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Jiajie Jin, Xiaoxi Li, Guanting Dong, et al.2025 · 25 citations
5. RAG-Critic: Leveraging Automated Critic-Guided Agentic Workflow for Retrieval Augmented GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Guanting Dong, Jiajie Jin, Xiaoxi Li, et al.2025 · 14 citations
6. Progressive Multimodal Reasoning via Active RetrievalAnnual Meeting of the Association for Computational Linguistics (ACL)Guanting Dong, Chenghao Zhang, Mengjie Deng, et al.2025 · 10 citations
7. Autonomous Knowledge Graph Exploration with Adaptive Breadth-Depth RetrievalAnnual Meeting of the Association for Computational Linguistics (ACL)Joaquin Polonuer, Lucas Vittor, Iñaki Arango, et al.2026

4 more papers of our library cite it; they have no page here yet.

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