---
title: "Who cites Eric Zelikman — page 5 — 1,551 papers of our library"
description: "1,551 papers of the Elamur Research library cite the works of Eric Zelikman, found in their bibliographies · page 5 of 5 · 401–458; the most…"
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---
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# Who cites Eric Zelikman

1,597 citations of their works from 1,551 papers of our library (of the 149,439 whose bibliographies we read) · 458 with a page here, the most cited first · page 5 of 5 · 401–458 · [← Eric Zelikman](https://md.research.elamur.ai/free/en/authors/eric-zelikman/)

[← prev](https://md.research.elamur.ai/free/en/authors/eric-zelikman/cited-by/page/4/) [1](https://md.research.elamur.ai/free/en/authors/eric-zelikman/cited-by/) … [4](https://md.research.elamur.ai/free/en/authors/eric-zelikman/cited-by/page/4/) **5**

401. **[Discovering and Causally Validating Emotion-Sensitive Neurons in Large Audio-Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2026-discovering-causally-validating-emotion-sensitive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiutian Zhao, Björn Schuller, Berrak Sisman*2026 · 1 citation*
402. **[Evaluating Linguistic Knowledge of LLMs in Tamil: The ILAKKANAM Benchmark](https://md.research.elamur.ai/free/en/papers/varsha-2026-evaluating-linguistic-knowledge-llms-tamil/) [workshop on Challenges in Processing South Asian Languages](https://md.research.elamur.ai/free/en/venues/chipsal/)**Jeyarajalingam Varsha, Menan Velayuthan, Sumirtha Karunakaran, et al.*2026 · 1 citation*
403. [**MÖVE: A Holistic LLM Benchmark for the German Public Sector arXiv:2606.13111**Camilla Dalerci, Thilo Michael, Robin Schaefer, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/dalerci-2026-m-ove-holistic-llm-benchmark/)
404. **[ReAttn: Improving Attention-based Re-ranking via Attention Re-weighting](https://md.research.elamur.ai/free/en/papers/tian-2026-reattn-improving-attention-based-re/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuxing Tian, Fengran Mo, Weixu Zhang, et al.*2026 · 1 citation*
405. **[Rethinking Scale: Deployment Trade-offs of Small Language Models under Agent Paradigms](https://md.research.elamur.ai/free/en/papers/wang-2026-rethinking-scale-deployment-trade-offs/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinlin Wang*2026 · 1 citation*
406. **[Solve-Detect-Verify: Inference-Time Scaling with Flexible Generative Verifier](https://md.research.elamur.ai/free/en/papers/zhong-2026-solve-detect-verify-inference-time/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianyuan Zhong, Zeju Li, Zhijian Xu, et al.*2026 · 1 citation*
407. **[The Mighty ToRR: A Benchmark for Table Reasoning and Robustness in LLMs](https://md.research.elamur.ai/free/en/papers/tahan-2026-mighty-torr-benchmark-table-reasoning/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Shir Ashury-Tahan, Yifan Mai, Rajmohan C, et al.*2026 · 1 citation*
408. **[Thinking Beyond the Local: Multi-View Instructed Adaptive Reasoning in KG-Enhanced LLMs](https://md.research.elamur.ai/free/en/papers/zhang-2026-thinking-beyond-local-multi-view/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Minghan Zhang, Shu Zhao, Zhen Yang, et al.*2026 · 1 citation*
409. **[User Perceptions vs. Proxy LLM Judges: Privacy and Helpfulness in LLM Responses to Privacy-Sensitive Scenarios](https://md.research.elamur.ai/free/en/papers/wu-2026-user-perceptions-vs-proxy-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyuan Wu, Roshni Kaushik, Wenkai Li, et al.*2026 · 1 citation*
410. [**Learning from Convenience Samples: A Case Study on Fine-Tuning LLMs for Survey Non-response in the German Longitudinal Election Study arXiv:2509.25063**Tobias Holtdirk, Dennis Assenmacher, Arnim Bleier, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/holtdirk-2025-learning-convenience-samples-case-study/)
411. [**Aquila2 Technical Report arXiv:2408.07410**Bo-Wen Zhang, Liangdong Wang, Jijie Li, et al.*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/zhang-2024-aquila2-technical-report/)
412. **[A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and Solutions](https://md.research.elamur.ai/free/en/papers/yu-2026-survey-reinforcement-learning-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyin Yu, Yuchen Mou, Juncheng Yan, et al.*2026*
413. **[Accelerating LLM Fine-Tuning via Embedding Knowledge Transfer](https://md.research.elamur.ai/free/en/papers/peng-2026-accelerating-llm-fine-tuning-embedding/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Meishu Peng, Ziyue Zhang, Yi Zhang, et al.*2026*
414. **[Actionable Interpretability for Churn Classification: A Text Bottleneck Model Case Study at a Major Telecom Provider](https://md.research.elamur.ai/free/en/papers/sauter-2026-actionable-interpretability-churn-classification-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Adrian Sauter, Vera Neplenbroek, Georgios Vlassopoulos, et al.*2026*
415. **[AgentFactory: A Self-Evolving Framework Through Executable Subagent Accumulation and Reuse](https://md.research.elamur.ai/free/en/papers/zhang-2026-agentfactory-self-evolving-framework-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhang Zhang, Shuqi Lu, Hongjin Qian, et al.*2026*
416. **[AICA-Bench: Holistically Examining the Capabilities of VLMs in Affective Image Content Analysis](https://md.research.elamur.ai/free/en/papers/she-2026-aica-bench-holistically-examining-capabilities/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dong She, Xianrong Yao, Liqun Chen, et al.*2026*
417. [**ArabicNumBench: Evaluating Arabic Number Reading in Large Language Models arXiv:2602.18776**Anas Alhumud, Abdulaziz Alhammadi, Muhammad Badruddin Khan*2026*](https://md.research.elamur.ai/free/en/papers/alhumud-2026-arabicnumbench-evaluating-arabic-number-reading/)
418. **[Automatic Paper Analysis and Categorisation for Systematic Reviews with Combined Reasoning-Augmented SFT and DAPO RL](https://md.research.elamur.ai/free/en/papers/lorandi-2026-automatic-paper-analysis-categorisation-systematic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Michela Lorandi, Anya Belz, Simon Mille, et al.*2026*
419. **[Benchmark Data Contamination in Underrepresented Languages: A Comprehensive Analysis Using Brazilian Data](https://md.research.elamur.ai/free/en/papers/vilar-2026-benchmark-data-contamination-underrepresented-languages/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Iriedson Souto Maior de Moraes Vilar, David Candeia Maia, João Brunet, et al.*2026*
420. **[BenchNavigator: A Discovery Interface for Comparing LLM Benchmarks](https://md.research.elamur.ai/free/en/papers/sokol-2026-benchnavigator-discovery-interface-comparing-llm/) [Workshop on Evaluating Evaluations (EvalEval)](https://md.research.elamur.ai/free/en/venues/evaleval/)**Anna Sokol, Inge Vejsbjerg, Elizabeth M. Daly, et al.*2026*
421. **[Beyond Marginal Distributions: A Framework to Evaluate the Representativeness of Demographic-Aligned LLMs](https://md.research.elamur.ai/free/en/papers/williams-2026-beyond-marginal-distributions-framework-evaluate/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tristan Williams, Franziska Weeber, Sebastian Padó, et al.*2026*
422. **[Beyond the Singular: Revealing the Value of Multiple Generations in Benchmark Evaluation](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-singular-revealing-value-multiple/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenbo Zhang, Hengrui Cai, Wenyu Chen*2026*
423. [**CEI: A Benchmark for Evaluating Pragmatic Reasoning in Language Models arXiv:2603.09993**Jon Chun, Hannah Sussman, Adrian Mangine, et al.*2026*](https://md.research.elamur.ai/free/en/papers/chun-2026-cei-benchmark-evaluating-pragmatic-reasoning/)
424. **[Charting the European LLM Benchmarking Landscape: A New Taxonomy and Registry](https://md.research.elamur.ai/free/en/papers/vintar-2026-charting-european-llm-benchmarking-landscape/) [Shaping Multilingual, Multimodal AI for the Social Sciences and Humanities @ LREC](https://md.research.elamur.ai/free/en/venues/llms4ssh/)**Spela Vintar, Mojca Brglez, Taja Kuzman Pungeršek, et al.*2026*
425. **[CLARO: Controlled Attribute-Driven Reasoning Optimization for Efficient Chain-of-Thought](https://md.research.elamur.ai/free/en/papers/schlesinger-2026-claro-controlled-attribute-driven-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Oded Schlesinger, Young Kyung Kim, J. Matias Di Martino, et al.*2026*
426. [**Computational models of pragmatic reasoning with flexible generation of meaning and expression alternatives arXiv:2607.18443**Polina Tsvilodub, Fausto Carcassi, Michael Franke*2026*](https://md.research.elamur.ai/free/en/papers/tsvilodub-2026-computational-models-pragmatic-reasoning-flexible/)
427. **[Contract-Coding: Towards Repo-Level Generation via Structured Symbolic Paradigm](https://md.research.elamur.ai/free/en/papers/yilin-2026-contract-coding-repo-level-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yilin, Lujin Zhao, Yijie Shi*2026*
428. **[Crossing the Reward Bridge: Expanding Reinforcement Learning with Verifiable Rewards Across Diverse Domains](https://md.research.elamur.ai/free/en/papers/su-2026-crossing-reward-bridge-expanding-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yi Su, Dian Yu, Linfeng Song, et al.*2026*
429. **[Disagreement-Driven Joint Refinement of Retrieval and Decision Rules for Imbalanced Counseling Risk Classification](https://md.research.elamur.ai/free/en/papers/shao-2026-disagreement-driven-joint-refinement-retrieval/) [Workshop on Clinical Natural Language Processing (Clinical NLP) @ LREC](https://md.research.elamur.ai/free/en/venues/clinicalnlp/)**Zhihao Shao, Ryo Sekizaki, Shengzhou Yi, et al.*2026*
430. **[EpiCaR: Knowing What You Don't Know Matters for Better Reasoning in LLMs](https://md.research.elamur.ai/free/en/papers/yeom-2026-epicar-knowing-what-you-don/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jewon Yeom, Jaewon Sok, Seonghyeon Park, et al.*2026*
431. **[Evaluating Language Model Pluralism through In-the-wild Crowd Discussions](https://md.research.elamur.ai/free/en/papers/mundada-2026-evaluating-language-model-pluralism-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gagan Mundada, Rohan Surana, Nandhini Swaminathan, et al.*2026*
432. **[Evaluating LLM Style Transfer Through Readability-Based Age Assessments](https://md.research.elamur.ai/free/en/papers/maro-2026-evaluating-llm-style-transfer-through/) [International Workshop on Spoken Dialogue System Technology](https://md.research.elamur.ai/free/en/venues/iwsds/)**Maria Di Maro, Antonio Origlia, Leonilda Bilo, et al.*2026*
433. **[FINEST: Improving LLM Responses to Sensitive Topics Through Fine-Grained Evaluation](https://md.research.elamur.ai/free/en/papers/oh-2026-finest-improving-llm-responses-sensitive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Juhyun Oh, Nayeon Lee, Chani Jung, et al.*2026*
434. [**From Global Benchmarks to Local Evaluations: Benchmarking LLMs for the German Public Sector arXiv:2608.17827**Camilla Dalerci, Thilo Michael, Robin Schaefer, et al.*2026*](https://md.research.elamur.ai/free/en/papers/dalerci-2026-global-benchmarks-local-evaluations-benchmarking/)
435. **[GSM-Noise: Exploring and Enhancing Large Language Models' Reasoning under Noisy Inputs](https://md.research.elamur.ai/free/en/papers/zhang-2026-gsm-noise-exploring-enhancing-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhengxin Zhang, Chengyu Huang, Xufu Liu, et al.*2026*
436. **[Harnessing the Latent Space: From Steering Vectors to Model Calibrators for Control and Trust](https://md.research.elamur.ai/free/en/papers/subramani-2026-harnessing-latent-space-steering-vectors/) [Big Picture v2: Crafting a Research Narrative](https://md.research.elamur.ai/free/en/venues/bigpicture/)**Nishant Subramani*2026*
437. [**HEBATRON: A Hebrew-Specialized Open-Weight Mixture-of-Experts Language Model**Noam Kayzer, Dan Revital, Ori Bar Joseph, et al.*2026*](https://md.research.elamur.ai/free/en/papers/kayzer-2026-hebatron-hebrew-specialized-open-weight/)
438. **[How Far Can Bias Go? Tracing Bias from Pre-Training Data to Alignment](https://md.research.elamur.ai/free/en/papers/thaler-2026-how-far-can-bias-go/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Marion Thaler, Abdullatif Köksal, Alina Leidinger, et al.*2026*
439. **[Learning from Mistakes: Negative Reasoning Samples Enhance Out-of-Domain Generalization](https://md.research.elamur.ai/free/en/papers/xueyun-2026-learning-mistakes-negative-reasoning-samples/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tian Xueyun, MingHua Ma, Bingbing Xu, et al.*2026*
440. **[Lexical Popularity: Quantifying the Impact of Pre-training for LLM Performance](https://md.research.elamur.ai/free/en/papers/ruzzetti-2026-lexical-popularity-quantifying-impact-pre/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Elena Sofia Ruzzetti, Fabio Massimo Zanzotto, Tommaso Caselli*2026*
441. **[On the Cultural Anachronism and Temporal Reasoning in Vision Language Models](https://md.research.elamur.ai/free/en/papers/ranjan-2026-cultural-anachronism-temporal-reasoning-vision/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mukul Ranjan, Prince Jha, Khushboo Kumari, et al.*2026*
442. **[Persona-Aware Evaluation of Cognitive Bias in LLMs: From Benchmark to Applied Decision-Making](https://md.research.elamur.ai/free/en/papers/yoshikawa-2026-persona-aware-evaluation-cognitive-bias/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Katsumasa Yoshikawa, Junya Takayama, Takato Yamazaki*2026*
443. **[Quantifying Metric and Model Agreement in Bias Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/asgari-2026-quantifying-metric-model-agreement-bias/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Arash Asgari, Huan Wu, Amirreza Naziri, et al.*2026*
444. **[ReasMark: A Robust Watermark for Attributing LLM Reasoning Under Knowledge Distillation Attacks](https://md.research.elamur.ai/free/en/papers/lv-2026-reasmark-robust-watermark-attributing-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peizhuo Lv, Ruihua Zhou, Yunpeng Li, et al.*2026*
445. **[Revisiting German Complex Word Identification: Contextualized LLMs and Feature Injection](https://md.research.elamur.ai/free/en/papers/schomacker-2026-revisiting-german-complex-word-identification/) [Joint Workshop on Readability and Text Simplification (READIxTSAR) @ LREC](https://md.research.elamur.ai/free/en/venues/readi/)**Thorben Schomacker, Seid Muhie Yimam, Chris Biemann, et al.*2026*
446. **[Routing with Generated Data: Annotation-Free LLM Skill Estimation and Expert Selection](https://md.research.elamur.ai/free/en/papers/niu-2026-routing-generated-data-annotation-free/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyi Niu, Justin Chen, Genta Indra Winata, et al.*2026*
447. **[SD-E2: Semantic Exploration for Reasoning Under Token Budgets](https://md.research.elamur.ai/free/en/papers/mishra-2026-sd-e2-semantic-exploration-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kshitij Mishra, Nils Lukas, Salem Lahlou*2026*
448. **[Self-Consistency from Only Two Samples: CoT–PoT Ensembling for Efficient LLM Reasoning](https://md.research.elamur.ai/free/en/papers/saparkhan-2026-self-consistency-only-two-samples/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Raman Saparkhan, Majd Hawasly, Md Rizwan Parvez, et al.*2026*
449. **[SynthAgent: Adapting Web Agents with Synthetic Supervision](https://md.research.elamur.ai/free/en/papers/wang-2026-synthagent-adapting-web-agents-synthetic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaoyang Wang, Yiming Liang, Xuchao Zhang, et al.*2026*
450. **[The Retrieval Bottleneck: Scaling Laws for Reinforcement Learning in RAG](https://md.research.elamur.ai/free/en/papers/zhou-2026-retrieval-bottleneck-scaling-laws-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shu Zhou, Jinman Leng, Yufei Song, et al.*2026*
451. **[Thinking Twice Makes Large Language Models Safer and More Helpful](https://md.research.elamur.ai/free/en/papers/mou-2026-thinking-twice-makes-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yutao Mou, Yuxiao Luo, Shikun Zhang, et al.*2026*
452. **[Toward Dialect-Aware Safety Evaluation for Arabic Large Language Models](https://md.research.elamur.ai/free/en/papers/zaghouani-2026-dialect-aware-safety-evaluation-arabic/) [Workshop on Trustworthy NLP](https://md.research.elamur.ai/free/en/venues/trustnlp/)**Wajdi Zaghouani*2026*
453. **[Toward Responsible and Epistemically Grounded Multilingual LLMs for Computational Social Science and Humanities](https://md.research.elamur.ai/free/en/papers/zaghouani-2026-responsible-epistemically-grounded-multilingual-llms/) [Shaping Multilingual, Multimodal AI for the Social Sciences and Humanities @ LREC](https://md.research.elamur.ai/free/en/venues/llms4ssh/)**Wajdi Zaghouani*2026*
454. **[Towards IP Intelligence: Benchmarking Large Language Models on Intellectual Property Knowledge and Practice](https://md.research.elamur.ai/free/en/papers/wang-2026-ip-intelligence-benchmarking-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiyao Wang, Guhong Chen, Hongbo Wang, et al.*2026*
455. **[TRAC: Teacher-Guided Token Reward with Adaptive Calibration for Robust Policy Optimization](https://md.research.elamur.ai/free/en/papers/wu-2026-trac-teacher-guided-token-reward/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sitong Wu, Haoru Tan, Xichen Zhang, et al.*2026*
456. **[TURTLEAI: Benchmarking Multimodal Models for Visual Programming in Turtle Graphics](https://md.research.elamur.ai/free/en/papers/wen-2026-turtleai-benchmarking-multimodal-models-visual/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chao Wen, Jacqueline Staub, Adish Singla*2026*
457. **[Vinclat: Evaluating Reasoning, Cognition and Culture in One Game](https://md.research.elamur.ai/free/en/papers/pamies-2026-vinclat-evaluating-reasoning-cognition-culture/) [Workshop on Multilingual Multicultural Evaluation](https://md.research.elamur.ai/free/en/venues/mme/)**Marc Pàmies, Javier Aula-Blasco, Aitor Gonzalez-Agirre, et al.*2026*
458. **[🧑‍🍳 Cooking Up Creativity: Enhancing LLM Creativity through Structured Recombination](https://md.research.elamur.ai/free/en/papers/mizrahi-2026-cooking-up-creativity-enhancing-llm/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Moran Mizrahi, Chen Shani, Gabriel Stanovsky, et al.*2026*

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