Rafiq Ali

3 papers in our library · 2026

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

Affiliations

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

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

The most cited first (OpenAlex and our library).

Do Large Language Models Reflect Demographic Pluralism in Safety? (2026 · 3 citations)
Safety judgments about LLM outputs differ across communities, yet widely used alignment resources such as ANTHROPIC-HH and DICES draw on narrow annotator pools.
Do Clinical Question Answering Systems Really Need Specialised Medical Fine Tuning? (2026 · 1 citation)
The paper questions a common assumption in industrial clinical question answering (CQA): that a model must be fine-tuned on medical data to perform well.
Are Large Language Models Economically Viable for Industry Deployment? (2026)
Industry teams choosing an LLM must weigh energy, latency, hardware use and cost, but common benchmarks report mostly accuracy.

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

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

Papers of our library cite their works 2 times (of the 149,439 papers whose bibliographies we read).

Updated 1 November 2026