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Parshin Shojaee

Parshin Shojaee has 5 papers in our library, in 2023–2025, most of them on Language models & pretraining, Reasoning, Evaluation & benchmarks; often with Chandan K. Reddy, Amir Barati Farimani, Kazem Meidani.

5 papers in our library · 2023–2025

OpenAlex · h-index 7 · 28 works · 292 citations OpenAlex, 2026-10-14

📄 5 works in our library · 🔗 Cited 173 times in our library · ⭐ Paper Stars ranking: #6448

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Virginia TechBlacksburg · United States2020–2026 · 17 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 more institutions on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 14The field of science this work belongs to (OpenAlex fields).Computer Science · 5 worksArtificial Intelligence · 2 worksPhysics and Astronomy · 3 worksArts and Humanities · 1 workLanguage and Linguistics · 1 workComputational Theory and Mathematics · 3 worksStatistical and Nonlinear Physics · 3 worksComputer Science Applications · 1 workInformation Systems · 1 workSoftware · 1 workMaterials Chemistry · 1 workMaterials Science · 1 workMathematics · 1 workModeling and Simulation · 1 work

🧭 Topics 4Research subjects and languages the work is about.Reasoning · 2 worksLanguage models & pretraining · 3 worksCode & programming languages · 1 workEvaluation & benchmarks · 1 work

 Works by year

2020s

20252 papers20241 paper20232 papers

 Papers

The most cited first (OpenAlex and our library).

  1. The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity (2025 · 104 citations)
    Benchmarks for Large Reasoning Models (LRMs) mostly score final answers on math and coding sets. These sets may be contaminated and say little about the reasoning trace itself. The Apple authors replace them with algorithmic puzzles: Tower of Hanoi, River Crossing, Blocks World and a checker puzzle. In each puzzle…
  2. LLM-SR: Scientific Equation Discovery via Programming with Large Language Models (2024 · 47 citations)
    Symbolic regression aims to recover compact, interpretable formulas from observations. The search space is combinatorially huge (the task is NP-hard), and classic tools such as genetic programming over expression trees ignore the domain knowledge that human scientists bring. LLM-SR addresses this by asking a large…
  3. Execution-based Code Generation using Deep Reinforcement Learning (2023 · 47 citations)
    Pre-trained code models such as CodeT5 or PLBART are usually fine-tuned with token-level objectives borrowed from text generation.
  4. LLM-SRBench: A New Benchmark for Scientific Equation Discovery with Large Language Models (2025 · 18 citations)
    Benchmarks for symbolic regression, such as Feynman, SRBench and SRSD, mostly contain textbook physics laws.
  5. SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training (2023 · 8 citations)
    Deep learning models for mathematics usually handle either symbolic expressions or numeric data, and they are typically trained with supervision for one specific task.

 Co-authors here

10 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 173 times (of the 149,439 papers whose bibliographies we read); 52 citing papers with a page here →.

Updated

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