mlsanityData to 7 Oct 2026

LLMs as Science Journalists: Supporting Early-stage Researchers in Communicating Their Science to the Public

arXiv 2601.05821 ↗First posted 9 Jan 2026cs.CLcited by 2

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Abstract (arXiv)

The scientific community needs tools that help early-stage researchers effectively communicate their findings and innovations to the public. Although existing general-purpose Large Language Models (LLMs) can assist in this endeavor, they are not optimally aligned for it. To address this, we propose a framework for training LLMs to emulate the role of a science journalist that can be used by early-stage researchers to learn how to properly communicate their papers to the general public. We evaluate the usefulness of our trained LLM Journalists in leading conversations with both simulated and human researchers. %compared to the general-purpose ones. Our experiments indicate that LLMs trained using our framework ask more relevant questions that address the societal impact of research, prompting researchers to clarify and elaborate on their findings. In the user study, the majority of participants who interacted with our trained LLM Journalist appreciated it more than interacting with general-purpose LLMs.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 11 of its 40 references that are in the map. First posted on arXiv 9 Jan 2026.

Builds on

11 of 40 references.

References · 11

  1. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  2. 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 7,916
  3. 2023Efficient Memory Management for Large Language Model Serving with PagedAttentioncited by 5,767
  4. 2023AlignScore: Evaluating Factual Consistency with a Unified Alignment Functioncited by 284
  5. 2020TLDR: Extreme Summarization of Scientific Documentscited by 136
  6. 2025Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Taskcited by 103
  7. 2025Training LLM-based Tutors to Improve Student Learning Outcomes in Dialoguescited by 40
  8. 2024Large Language Models for Education: A Surveycited by 32
  9. 2021A Training-free and Reference-free Summarization Evaluation Metric via Centrality-weighted Relevance and Self-referenced Redundancycited by 21
  10. 2024SciNews: From Scholarly Complexities to Public Narratives -- A Dataset for Scientific News Report Generationcited by 12
  11. 2016On the Diagnostic of Road Pathway Visibilitycited by 10

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Citing papers per year: 2026: 2.

2 papers.