--- title: "Mihir Parmar — author profile and papers — Elamur Research" description: "Mihir Parmar, Google: 6 papers on Elamur Research (2023–2026), h-index 15 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/mihir-parmar/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/mihir-parmar/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Mihir Parmar # Mihir Parmar Mihir Parmar has 6 papers in our library, in 2023–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/); often with [Chitta Baral](https://md.research.elamur.ai/free/en/authors/chitta-baral/), [Neeraj Varshney](https://md.research.elamur.ai/free/en/authors/neeraj-varshney/), [Man Luo](https://md.research.elamur.ai/free/en/authors/man-luo/). 6 papers in our library · 2023–2026 [OpenAlex](https://openalex.org/A5106524687) · [**h-index 15**](https://openalex.org/authors/A5106524687) · [57 works](https://openalex.org/works?filter=author.id:A5106524687) · [986 citations](https://openalex.org/works?filter=author.id:A5106524687&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 6 works in our library](https://md.research.elamur.ai/free/en/authors/mihir-parmar/#papers) · [🔗 Cited 757 times in our library](https://md.research.elamur.ai/free/en/authors/mihir-parmar/cited-by/) · [1 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #6383](https://md.research.elamur.ai/free/en/paper-stars/page/64/#star-6383) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Mihir+Parmar) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Mihir+Parmar) · [dblp](https://dblp.org/search?q=Mihir+Parmar) · [ACL Anthology](https://aclanthology.org/search/?q=Mihir+Parmar) ## Affiliations [🎓**Arizona State University** Tempe · United States 2022–2026 · 25 papers*current*](https://md.research.elamur.ai/free/en/universities/arizona-state-university/) · [🏢**Google** Mountain View · United States 2026 · 3 papers*current*](https://md.research.elamur.ai/free/en/companies/google/) · [🏥**Mayo Clinic Hospital** Phoenix · United States 2026 · 1 paper*current*](https://ror.org/03660jn93) · [🏥**Mayo Clinic in Arizona** Scottsdale · United States 2026 · 1 paper*current*](https://ror.org/03jp40720) · [🎓**University of Kentucky** Lexington · United States 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/university-of-kentucky/) · [🎓**King Saud University** Riyadh · Saudi Arabia 2013–2017 · 8 papers](https://md.research.elamur.ai/free/en/universities/king-saud-university/) · [🎓**Jawaharlal Nehru Technological University, Hyderabad** Hyderabad · India 2018–2019 · 6 papers](https://ror.org/002tchr49) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed. ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 5 The field of science this work belongs to (OpenAlex fields).[Computer Science · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 5 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Language and Linguistics · 5 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) 🧭 Topics 3 Research subjects and languages the work is about.[Language models & pretraining · 5 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning · 4 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) ## Works by year ### 2020s [**2026** 1 paper](https://md.research.elamur.ai/free/en/authors/mihir-parmar/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/mihir-parmar/year/2025/) · [**2024** 3 papers](https://md.research.elamur.ai/free/en/authors/mihir-parmar/year/2024/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/mihir-parmar/year/2023/) ## Papers The most cited first (OpenAlex and our library). 1. **[LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language Models](https://md.research.elamur.ai/free/en/papers/parmar-2024-logicbench-systematic-evaluation-logical-reasoning/)** *(2024 · 93 citations)* Most logical reasoning benchmarks for LLMs either blend logic with other skills (LogiQA, ReClor) or stick to one logic type and a few rules such as modus ponens (FOLIO, ProntoQA). 2. **[Multi-LogiEval: Towards Evaluating Multi-Step Logical Reasoning Ability of Large Language Models](https://md.research.elamur.ai/free/en/papers/patel-2024-multi-logieval-evaluating-multi-step/)** *(2024 · 39 citations)* Benchmarks for logical reasoning in LLMs usually test only single inference steps, rely on a few rules such as modus ponens, or cover only one kind of logic. 3. **[A Survey of Small Language Models](https://md.research.elamur.ai/free/en/papers/nguyen-2024-survey-small-language-models/)** *(2024 · 31 citations)* Large language models perform well but need heavy compute, memory and data, so they usually run on centralized, specialized hardware. 4. **[Towards LogiGLUE: A Brief Survey and A Benchmark for Analyzing Logical Reasoning Capabilities of Language Models](https://md.research.elamur.ai/free/en/papers/luo-2023-towards-logiglue-brief-survey-benchmark/)** *(2023 · 27 citations)* The paper asks how well language models handle logical reasoning expressed in natural language. Formal knowledge-representation systems needed heavy expert effort and did not scale. The authors first survey the field. They cover three reasoning types (deductive, inductive, abductive), the usual task formats, how… 5. **[PlanGEN: A Multi-Agent Framework for Generating Planning and Reasoning Trajectories for Complex Problem Solving](https://md.research.elamur.ai/free/en/papers/parmar-2025-plangen-multi-agent-framework-generating/)** *(2025 · 16 citations)* LLM-based agents and test-time search methods often fail on "natural planning" tasks, such as scheduling meetings or planning trips described in plain language. 6. **[CoAct: Co-Active LLM Preference Learning with Human-AI Synergy](https://md.research.elamur.ai/free/en/papers/xu-2026-coact-co-active-llm-preference/)** *(2026 · 1 citation)* Preference-based alignment of LLMs depends on human-labelled response pairs, which are costly to collect. Self-rewarding pipelines produce such pairs cheaply, but they can amplify the model's own mistakes. Active preference learning keeps labels trustworthy, yet it leaves most of the unlabeled pool unused. CoAct… ## All works 7 works of theirs in our library, the most cited first; 6 with a page here, the others link their original until we summarise them. 1. **[Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks ↗](https://aclanthology.org/2022.emnlp-main.340/) Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing · no summary yet**Yizhong Wang et al.*2022 · 849 citations* 2. **[LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language Models](https://md.research.elamur.ai/free/en/papers/parmar-2024-logicbench-systematic-evaluation-logical-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mihir Parmar, Nisarg Patel, Neeraj Varshney, et al.*2024 · 93 citations* 3. **[Multi-LogiEval: Towards Evaluating Multi-Step Logical Reasoning Ability of Large Language Models](https://md.research.elamur.ai/free/en/papers/patel-2024-multi-logieval-evaluating-multi-step/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nisarg Patel, Mohith Kulkarni, Mihir Parmar, et al.*2024 · 39 citations* 4. [**A Survey of Small Language Models arXiv:2410.20011**Chien Van Nguyen, Xuan Shen, Ryan Aponte, et al.*2024 · 31 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2024-survey-small-language-models/) 5. [**Towards LogiGLUE: A Brief Survey and A Benchmark for Analyzing Logical Reasoning Capabilities of Language Models arXiv:2310.00836**Man Luo, Shrinidhi Kumbhar, Ming shen, et al.*2023 · 27 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-towards-logiglue-brief-survey-benchmark/) 6. **[PlanGEN: A Multi-Agent Framework for Generating Planning and Reasoning Trajectories for Complex Problem Solving](https://md.research.elamur.ai/free/en/papers/parmar-2025-plangen-multi-agent-framework-generating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mihir Parmar, Xin Liu, Palash Goyal, et al.*2025 · 16 citations* 7. **[CoAct: Co-Active LLM Preference Learning with Human-AI Synergy](https://md.research.elamur.ai/free/en/papers/xu-2026-coact-co-active-llm-preference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruiyao Xu, Mihir Parmar, Tiankai Yang, et al.*2026 · 1 citation* ## Co-authors here 12 of 27 co-authors with a page, the most papers together first. - [Chitta Baral](https://md.research.elamur.ai/free/en/authors/chitta-baral/) ×4 - [Neeraj Varshney](https://md.research.elamur.ai/free/en/authors/neeraj-varshney/) ×3 - [Man Luo](https://md.research.elamur.ai/free/en/authors/man-luo/) ×2 - [Mutsumi Nakamura](https://md.research.elamur.ai/free/en/authors/mutsumi-nakamura/) ×2 - [Nisarg Patel](https://md.research.elamur.ai/free/en/authors/nisarg-patel/) ×2 - [Arindam Mitra](https://md.research.elamur.ai/free/en/authors/arindam-mitra/) - [Chen-Yu Lee](https://md.research.elamur.ai/free/en/authors/chen-yu-lee/) - [Chien Van Nguyen](https://md.research.elamur.ai/free/en/authors/chien-van-nguyen/) - [Hootan Nakhost](https://md.research.elamur.ai/free/en/authors/hootan-nakhost/) - [Jian Chen](https://md.research.elamur.ai/free/en/authors/jian-chen/) - [Jindong Gu](https://md.research.elamur.ai/free/en/authors/jindong-gu/) - [Joe Barrow](https://md.research.elamur.ai/free/en/authors/joe-barrow/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/) ×3: [EMNLP 2025](https://md.research.elamur.ai/free/en/venues/emnlp/2025/), [EMNLP 2024](https://md.research.elamur.ai/free/en/venues/emnlp/2024/) - [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/) ×2: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/), [ACL 2024](https://md.research.elamur.ai/free/en/venues/acl/2024/) ## Cited by Papers of our library cite their works 757 times (of the 149,439 papers whose bibliographies we read); [195 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/mihir-parmar/cited-by/). Updated 31 October 2026