🧑‍🔬 Who cites Karishma Mandyam

82 citations of their works from 82 papers of our library (of the 149,439 whose bibliographies we read) · 19 with a page here, the most cited first · ← Karishma Mandyam

1. Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language ModelsComputational LinguisticsYue Zhang, Yafu Li, Leyang Cui, et al.2023 · 977 citations
2. Query Rewriting in Retrieval-Augmented Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Xinbei Ma, Yeyun Gong, Pengcheng He, et al.2023 · 384 citations
3. TimeLMs: Diachronic Language Models from TwitterAnnual Meeting of the Association for Computational Linguistics (ACL)Daniel Loureiro, Francesco Barbieri, Leonardo Neves, et al.2022 · 331 citations
4. Knowledge Conflicts for LLMs: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.2024 · 182 citations
5. RealTime QA: What's the Answer Right Now?Conference on Neural Information Processing Systems (NeurIPS)Jungo Kasai, Keisuke Sakaguchi, Yoichi Takahashi, et al.2022 · 181 citations
6. Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large Language Models in Knowledge ConflictsarXiv:2305.13300Jian Xie, Kai Zhang, Jiangjie Chen, et al.2023 · 168 citations
7. Branch-Train-Merge: Embarrassingly Parallel Training of Expert Language ModelsarXiv:2208.03306Margaret Li, Suchin Gururangan, Tim Dettmers, et al.2022 · 114 citations
8. A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & ToxicityarXiv:2305.13169Shayne Longpre, Gregory Yauney, Emily Reif, et al.2023 · 104 citations
9. R-Tuning: Instructing Large Language Models to Say ‘I Don't Know'Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)Hanning Zhang, Shizhe Diao, Yong Lin, et al.2024 · 99 citations
10. Tuning Language Models by ProxyarXiv:2401.08565Alisa Liu, Xiaochuang Han, Yizhong Wang, et al.2024 · 79 citations
11. Kimi K2.5: Visual Agentic IntelligencearXiv:2602.02276Kimi Team, Tongtong Bai, Yifan Bai, et al.2026 · 66 citations
12. From Storage to Experience: A Survey on the Evolution of LLM Agent Memory MechanismsFindings of the Association for Computational LinguisticsJinghao Luo, Yuchen Tian, Chuxue Cao, et al.2026 · 3 citations
13. When Seeing Overrides Knowing: Disentangling Knowledge Conflicts in Vision-Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Francesco Ortu, Zhijing Jin, Diego Doimo, et al.2026 · 2 citations
14. SPARD: Self-Paced Curriculum for RL Alignment via Integrating Reward Dynamics and Data UtilityAnnual Meeting of the Association for Computational Linguistics (ACL)Xuyang Zhi, Peilun Zhou, Chengqiang Lu, et al.2026 · 1 citation
15. Can Large Language Models Effectively Support Decision-Making in Sudden Emergencies?Findings of the Association for Computational LinguisticsMengna Zhu, Jibing Wu, Lihua Liu, et al.2026
16. Complex-IF and Beyond: Expert Rubrics for RLVRWorkshop on Generation, Evaluation and Metrics (GEM)Sushant Mehta, Liudas Panavas, Eleanor Fleming, et al.2026
17. Data-Efficient Adaptation to Contextual Shifts in LLM-based Conversational RecommendationFindings of the Association for Computational LinguisticsHyeongjun Yang, Donghyun Kim, Seokju Hwang, et al.2026
18. Dissecting GraphRAG: A Modular Analysis of Knowledge Structuring for Factoid Question AnsweringTransactions of the Association for Computational Linguistics (TACL)Noriki Nishida, Rumana Ferdous Munne, Shanshan Liu, et al.2026
19. Measuring Distribution Shift in User Prompts and Its Effects on LLM PerformanceAnnual Meeting of the Association for Computational Linguistics (ACL)Parker Seegmiller, Sarah Masud Preum2026

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