---
title: "MIT Lincoln Laboratory — works of 2026 — Elamur Research"
description: "4 works of MIT Lincoln Laboratory from 2026 in our library, the most cited first. Among them: DIA-HARM: Dialectal Disparities in Harmful…"
canonical: "https://research.elamur.ai/free/en/labs/mit-lincoln-laboratory/year/2026/"
---
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# Works of MIT Lincoln Laboratory from 2026

4 works · the most cited first · [← MIT Lincoln Laboratory](https://md.research.elamur.ai/free/en/labs/mit-lincoln-laboratory/)

1. **[DIA-HARM: Dialectal Disparities in Harmful Content Detection Across 50 English Dialects](https://md.research.elamur.ai/free/en/papers/lucas-2026-dia-harm-dialectal-disparities-harmful/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jason S Lucas, Matt Murtagh White, Ali Al-Lawati, et al.*2026*
2. **[Synthetic Text Detection in the Age of Large Language Models: Watermark vs. Automatic Detection](https://md.research.elamur.ai/free/en/papers/uchendu-2026-synthetic-text-detection-age-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Adaku Uchendu*2026*
3. **[The Shape of Vulnerability: How Adversarial Perturbations Reshape the Topology of Language Model Latent Spaces](https://md.research.elamur.ai/free/en/papers/tsai-2026-shape-vulnerability-how-adversarial-perturbations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Angelina Tsai, Shreya Subramanian, Catherine Liu, et al.*2026*
4. **[Using Topological Data Analysis to Characterize the Layers of Language Models Before and After Word Substitution Attacks](https://md.research.elamur.ai/free/en/papers/tang-2026-topological-data-analysis-characterize-layers/) [Workshop on Customizable NLP: Progress and Challenges in Customizing NLP for a Domain, Application, Group, or Individual](https://md.research.elamur.ai/free/en/venues/customnlp4u/)**Adam Tang, Catherine Liu, Kimberly Lopez, et al.*2026*
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