---
title: "Laleh Seyyed-Kalantari — author profile and papers"
description: "Laleh Seyyed-Kalantari: 2 papers on Elamur Research (2026) — affiliations, topics, co-authors and who cites them in our library."
canonical: "https://research.elamur.ai/free/en/authors/laleh-seyyed-kalantari/"
---
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# Laleh Seyyed-Kalantari

2 papers on this site · 2026

Laleh Seyyed-Kalantari has 2 papers on this site, in 2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/); often with [Arash Asgari](https://md.research.elamur.ai/free/en/authors/arash-asgari/), [Ali Emami](https://md.research.elamur.ai/free/en/authors/ali-emami/), [Hassan Sajjad](https://md.research.elamur.ai/free/en/authors/hassan-sajjad/).

No OpenAlex profile matched yet.

[2 works on this site](https://md.research.elamur.ai/free/en/authors/laleh-seyyed-kalantari/#papers)

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=Laleh+Seyyed-Kalantari) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Laleh+Seyyed-Kalantari) · [dblp](https://dblp.org/search?q=Laleh+Seyyed-Kalantari) · [ACL Anthology](https://aclanthology.org/search/?q=Laleh+Seyyed-Kalantari)

## Topics

[Language models & pretraining 1](https://md.research.elamur.ai/free/en/topics/language-models/) · [Evaluation & benchmarks 1](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/)

## Papers

The most cited first (OpenAlex and our library).

1. **[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/)** *(2026)* The bias of large language models is evaluated with dozens of metrics and benchmarks. However, until now there has been no way to check whether these tools agree with one another and whether they rank models consistently. The authors propose two measures. The Metric Agreement Score (MeAS) shows how similarly…
2. **[ZIP: Quantifying Which Words Matter in Zero-Shot Instructional Prompts](https://md.research.elamur.ai/free/en/papers/sadr-2026-zip-quantifying-which-words-matter/)** *(2026)* Zero-shot instructional prompts such as the Chain-of-Thought cue "Let's think step-by-step" reliably improve LLM accuracy, but it has been unclear which individual words produce the gain.

## Co-authors here

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

- [Arash Asgari](https://md.research.elamur.ai/free/en/authors/arash-asgari/) ×2
- [Ali Emami](https://md.research.elamur.ai/free/en/authors/ali-emami/)
- [Hassan Sajjad](https://md.research.elamur.ai/free/en/authors/hassan-sajjad/)