The FLaNN Workshop submission deadline has been extended to Feb 19! Invited talks + posters (non-archival): expressivity, computation, and learning in neural nets/LLMs. Previous work welcome. Graduate students encouraged to submit! 📍 Yale University 🗓️ May 11-13, 2026

@pentagonalize.bsky.social · 6mo ago

📣 FLaNN 2026 at Yale 🍮 Invited talks+posters (non-archival): expressivity, computation, and learning in neural nets/LLMs Speakers: Pablo Barceló, David Chiang, Will Merrill, Naomi Saphra, Gail Weiss Abstracts due Feb 12, 2026 Details: flann.cs.yale.edu

📣 FLaNN 2026 at Yale 🍮 Invited talks+posters (non-archival): expressivity, computation, and learning in neural nets/LLMs Speakers: Pablo Barceló, David Chiang, Will Merrill, Naomi Saphra, Gail Weiss Abstracts due Feb 12, 2026 Details: flann.cs.yale.edu

Deadline in just under two weeks!

Marco@mcognetta.bsky.social · 6mo ago

CFP for the First Workshop on Formal Languages and Neural Networks! "We welcome posters dicussing the formal expressivity, computational properties, and learning behavior of neural networks!" Call for posters: flann.cs.yale.edu/cfp.html Deadline: February 12, 2026 @pentagonalize.bsky.social

Announcing the first Workshop on Formal Languages and Neural Networks (FLaNN)! We invite the submission of abstracts for posters that discuss the formal expressivity, computational properties, and learning behavior of neural network models, including large language models (LLMs).

We present The Transformer Cookbook: a collection of recipes for programming algorithms directly into transformers! Hungry for an induction head? Craving a Dyck language recognizer? We show you step-by-step how to cook up transformers for these algorithms and many more!

The Transformer Cookbook

We present the transformer cookbook: a collection of techniques for directly encoding algorithms into a transformer's parameters. This work addresses the steep learning curve of such endeavors, a prob...

arxiv.org

New paper and two not-so-new papers on arXiv about transformer expressivity: (1) With @pentagonalize and Dana Angluin, "Simulating Hard Attention Using Soft Attention" arxiv.org/abs/2412.09925

Simulating Hard Attention Using Soft Attention

We study conditions under which transformers using soft attention can simulate hard attention, that is, effectively focus all attention on a subset of positions. First, we examine several variants of ...

arxiv.org