---
title: "Who cites Saiteja Utpala — page 2 — 322 papers of our library"
description: "322 papers of the Elamur Research library cite the works of Saiteja Utpala, found in their bibliographies · page 2 of 2 · 101–124; the most cited first."
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---
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# Who cites Saiteja Utpala

328 citations of their works from 322 papers of our library (of the 149,439 whose bibliographies we read) · 124 with a page here, the most cited first · page 2 of 2 · 101–124 · [← Saiteja Utpala](https://md.research.elamur.ai/free/en/authors/saiteja-utpala/)

[← prev](https://md.research.elamur.ai/free/en/authors/saiteja-utpala/cited-by/) [1](https://md.research.elamur.ai/free/en/authors/saiteja-utpala/cited-by/) **2**

101. **[AgentGym2: Benchmarking Large Language Model Agents in De-Idealized Real-World Environments](https://md.research.elamur.ai/free/en/papers/xi-2026-agentgym2-benchmarking-large-language-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiheng Xi, Dingwen Yang, Jiaqi Liu, et al.*2026*
102. **[Agentic CLEAR: Automating Multi-Level Evaluation of LLM Agents](https://md.research.elamur.ai/free/en/papers/yehudai-2026-agentic-clear-automating-multi-level/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Asaf Yehudai, Lilach Eden, Michal Shmueli-Scheuer*2026*
103. **[Bi-Text Mining across German Dialects: On the Role of Synthetic Training Data for Dialect Adaptation](https://md.research.elamur.ai/free/en/papers/wang-2026-bi-text-mining-across-german/) [Workshop on Building and Using Comparable Corpora (BUCC)](https://md.research.elamur.ai/free/en/venues/bucc/)**Jing Wang, Barbara Plank, Robert Litschko*2026*
104. **[BrowseConf: Confidence-Guided Test-Time Scaling for Web Agents](https://md.research.elamur.ai/free/en/papers/ou-2026-browseconf-confidence-guided-test-time/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Litu Ou, Kuan Li, Huifeng Yin, et al.*2026*
105. **[DeepSynth-Eval: Objectively Evaluating Information Consolidation in Deep Survey Writing](https://md.research.elamur.ai/free/en/papers/zhang-2026-deepsynth-eval-objectively-evaluating-information/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hongzhi Zhang, Yuanze Hu, Tinghai Zhang, et al.*2026*
106. **[Generative Gamer: Learning Equilibrium Strategy by LLM-driven Dynamic Deduction](https://md.research.elamur.ai/free/en/papers/zhang-2026-generative-gamer-learning-equilibrium-strategy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yadong Zhang, Xinshu Shen, Yupei Ren, et al.*2026*
107. **[Information Representation Fairness in Long-Document Embeddings: The Peculiar Interaction of Positional and Language Bias](https://md.research.elamur.ai/free/en/papers/schuhmacher-2026-information-representation-fairness-long-document/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Elias Schuhmacher, Andrianos Michail, Juri Opitz, et al.*2026*
108. **[LLMs Meet Isolation Kernel: Lightweight, Learning-free Binary Embeddings for Fast Retrieval](https://md.research.elamur.ai/free/en/papers/zhang-2026-llms-meet-isolation-kernel-lightweight/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhibo Zhang, Yang Xu, Kai Ming Ting, et al.*2026*
109. **[Modeling semantic association in self-paced reading with language model embeddings](https://md.research.elamur.ai/free/en/papers/ostergaard-2026-modeling-semantic-association-self-paced/) [Workshop on Cognitive Modeling and Computational Linguistics (CMCL)](https://md.research.elamur.ai/free/en/venues/cmcl/)**Sara Møller Østergaard, Kenneth Enevoldsen, Afra Alishahi, et al.*2026*
110. **[MorphoBench: A Benchmark with Difficulty Adaptive to Model Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2026-morphobench-benchmark-difficulty-adaptive-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xukai Wang, Xuanbo Liu, Mingrui Chen, et al.*2026*
111. **[MTRouter: Cost-Aware Multi-Turn LLM Routing with History–Model Joint Embeddings](https://md.research.elamur.ai/free/en/papers/zhang-2026-mtrouter-cost-aware-multi-turn/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiqun Zhang, Hao Li, Zihan Wang, et al.*2026*
112. **[PaperScope: A Multi-Modal Multi-Document Benchmark for Agentic Deep Research Across Massive Scientific Papers](https://md.research.elamur.ai/free/en/papers/xiong-2026-paperscope-multi-modal-multi-document/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lei Xiong, Huaying Yuan, Zheng Liu, et al.*2026*
113. **[Parallelism and Generation Order in Masked Diffusion Language Models: Limits Today, Potential Tomorrow](https://md.research.elamur.ai/free/en/papers/zhong-2026-parallelism-generation-order-masked-diffusion/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yangyang Zhong, Yanmei Gu, Zhengqing Zang, et al.*2026*
114. [**Qwen3.8-Omni: Towards Native Omni-Modal Agents arXiv:2609.25611**Qwen Team*2026*](https://md.research.elamur.ai/free/en/papers/qwen-team-2026-qwen3-8-omni-native/)
115. **[R ESEARCH QA: Evaluating Scholarly Question Answering at Scale Across 75 Fields with Survey-Mined Questions and Rubrics](https://md.research.elamur.ai/free/en/papers/yifei-2026-r-esearch-qa-evaluating-scholarly/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Li S. Yifei, Allen Chang, Chaitanya Malaviya, et al.*2026*
116. **[SAGE: Steerable Agentic Data Generation for Deep Search with Execution Feedback](https://md.research.elamur.ai/free/en/papers/xu-2026-sage-steerable-agentic-data-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fangyuan Xu, Rujun Han, Yanfei Chen, et al.*2026*
117. **[SciExplore: Evaluating Autonomous Agents from Scientific Navigation to Information Integration](https://md.research.elamur.ai/free/en/papers/tang-2026-sciexplore-evaluating-autonomous-agents-scientific/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yinhao Tang, Youqing Fang, Yanan Sun, et al.*2026*
118. **[SkMTEB: Slovak Massive Text Embedding Benchmark and Model Adaptation](https://md.research.elamur.ai/free/en/papers/suppa-2026-skmteb-slovak-massive-text-embedding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Marek Suppa, Andrej Ridzik, Daniel Hládek, et al.*2026*
119. **[The Dog the Cat Chased Stumped the Model: Measuring When Language Models Abandon Structure for Shortcuts](https://md.research.elamur.ai/free/en/papers/madhusudan-2026-dog-cat-chased-stumped-model/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sangmitra Madhusudan, Kaige Chen, Ali Emami*2026*
120. **[The Overlooked Role of Graded Relevance Thresholds in Multilingual Dense Retrieval](https://md.research.elamur.ai/free/en/papers/wullach-2026-overlooked-role-graded-relevance-thresholds/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tomer Wullach, Ori Shapira, Amir David Nissan Cohen*2026*
121. **[Training Biomedical Retrievers From Large-Scale Citation Contexts](https://md.research.elamur.ai/free/en/papers/wang-2026-training-biomedical-retrievers-large-scale/) [BioNLP](https://md.research.elamur.ai/free/en/venues/bionlp/)**Xing David Wang, Duy Le Thanh, Ulf Leser*2026*
122. **[VRPO: Rethinking Value Modeling for Robust RL under Noisy Supervision in LLM Post-Training](https://md.research.elamur.ai/free/en/papers/zhu-2026-vrpo-rethinking-value-modeling-robust/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dingwei Zhu, Shihan Dou, Zhiheng Xi, et al.*2026*
123. **[WebClipper: Efficient Evolution of Web Agents with Graph-based Trajectory Pruning](https://md.research.elamur.ai/free/en/papers/wang-2026-webclipper-efficient-evolution-web-agents/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junjie Wang, Zequn Xie, Dan Yang, et al.*2026*
124. **[Why do Large Language Models Fail in Low-resource Translation? Unraveling the Token Dynamics of Large Language Models for Machine Translation](https://md.research.elamur.ai/free/en/papers/qian-2026-why-do-large-language-models/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Shenbin Qian, Yves Scherrer*2026*

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