🔗 Who cites «Unfamiliar Finetuning Examples Control How Language Models Hallucinate»

40 papers of our library cite it (of the 149,439 whose bibliographies we read) · 5 with a page here, the most cited first · ← back to «Unfamiliar Finetuning Examples Control How Language Models Hallucinate»

1. Recursive Introspection: Teaching Language Model Agents How to Self-ImproveConference on Neural Information Processing Systems (NeurIPS)Yuxiao Qu, Tianjun Zhang, Naman Garg, et al.2024 · 75 citations
2. Can Large Language Models Faithfully Express Their Intrinsic Uncertainty in Words?Conference on Empirical Methods in Natural Language Processing (EMNLP)Gal Yona, Roee Aharoni, Mor Geva2024 · 40 citations
3. LoGU: Long-form Generation with Uncertainty ExpressionsAnnual Meeting of the Association for Computational Linguistics (ACL)Ruihan Yang, Caiqi Zhang, Zhisong Zhang, et al.2025 · 13 citations
4. Aligning Large Language Models to Follow Instructions and Hallucinate Less via Effective Data FilteringAnnual Meeting of the Association for Computational Linguistics (ACL)Shuzheng Si, Haozhe Zhao, Gang Chen, et al.2025 · 11 citations
5. KnowRL: Exploring Knowledgeable Reinforcement Learning for FactualityAnnual Meeting of the Association for Computational Linguistics (ACL)Baochang Ren, Shuofei Qiao, Ningyu Zhang, et al.2026 · 5 citations

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

This page in Markdown → https://md.research.elamur.ai/free/en/papers/kang-2025-unfamiliar-finetuning-examples-control-how/cited-by/