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Kaveh Hassani

Kaveh Hassani has 2 papers in our library, in 2026, most of them on Language models & pretraining; often with Dongqi Fu, Hanghang Tong, Hanqing Zeng.

2 papers in our library · 2026

OpenAlex · ORCID · Wikidata · h-index 11 · 53 works · 968 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 5 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #12243

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

🎓ETH ZurichZurich · Switzerland2026 · 1 papercurrent🎓University of OttawaOttawa · Canada2013–2017 · 14 papers🏢MetaMenlo Park · United States2024–2025 · 4 papers🏢AutodeskSan Francisco · United States2019–2022 · 4 papers🎓K. N. Toosi University of TechnologyTehran · Iran2013 · 3 papers🏢AutodeskMontreal · Canada2019–2022 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 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 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksPhysics and Astronomy · 1 workStatistical and Nonlinear Physics · 1 work

🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Imbalanced Gradients in RL Post-Training of Multi-Task LLMs (2026 · 3 citations)
    When an LLM is post-trained on several tasks at once, the datasets are usually pooled and optimized together.
  2. How to Make LMs Strong Node Classifiers? (2026)
    The paper asks whether standard, instruction-tuned text-to-text LMs can classify nodes in Text-Attributed Graphs (TAGs) as well as specialized graph models, without changing the LM's architecture.

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Unsupervised Multi-Task Feature Learning on Point Clouds ↗IEEE/CVF International Conference on Computer Vision (ICCV) · no summary yetKaveh Hassani, Mike Haley2019 · 184 citations
  2. Imbalanced Gradients in RL Post-Training of Multi-Task LLMsFindings of the Association for Computational LinguisticsRunzhe Wu, Ankur Samanta, Ayush Jain, et al.2026 · 3 citations
  3. How to Make LMs Strong Node Classifiers?Findings of the Association for Computational LinguisticsZhe Xu, Kaveh Hassani, Si Zhang, et al.2026

 Co-authors here

5 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 5 times (of the 149,439 papers whose bibliographies we read).

Updated

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