Noam Wies

Noam Wies has 2 papers in our library, in 2023, most of them on Language models & pretraining; often with Amnon Shashua, Yoav Levine.

2 papers in our library · 2023

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).

Fundamental Limitations of Alignment in Large Language Models (2023 · 114 citations)
Wolf et al. ask whether aligning a large language model, via RLHF finetuning or aligning prompts, can make it robust to adversarial users. To analyze this, they develop Behavior Expectation Bounds (BEB), a framework grounded in probability theory. Each behavior vertical (e.g., helpfulness, politeness) assigns…
The Learnability of In-Context Learning (2023 · 53 citations)
In-context learning lets a large language model take on a downstream task from labeled examples placed in its prompt, without any weight updates.

2 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 102 times (of the 149,439 papers whose bibliographies we read); 22 citing papers with a page here →.

Updated 30 October 2026