5 papers
Simulating Hard Attention Using Soft Attention
Andy Yang, Lena Strobl, David Chiang +1
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…
Concise One-Layer Transformers Can Do Function Evaluation (Sometimes)
Lena Strobl, Dana Angluin, Robert Frank
While transformers have proven enormously successful in a range of tasks, their fundamental properties as models of computation are not well understood. This paper contributes to t…
Transformers as Transducers
Lena Strobl, Dana Angluin, David Chiang +2
We study the sequence-to-sequence mapping capacity of transformers by relating them to finite transducers, and find that they can express surprisingly large classes of transduction…
Masked Hard-Attention Transformers Recognize Exactly the Star-Free Languages
Andy Yang, David Chiang, Dana Angluin
The expressive power of transformers over inputs of unbounded size can be studied through their ability to recognize classes of formal languages. In this paper, we establish exact…
What Formal Languages Can Transformers Express? A Survey
Lena Strobl, William Merrill, Gail Weiss +2
As transformers have gained prominence in natural language processing, some researchers have investigated theoretically what problems they can and cannot solve, by treating problem…