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Transformers have become the foundational architecture for a broad spectrum of sequence modeling applications, underpinning state-of-the-art systems in natural language processing, vision, and beyond. However, their theoretical limitations…

Computation and Language · Computer Science 2026-02-13 Michelle Yuan , Weiyi Sun , Amir H. Rezaeian , Jyotika Singh , Sandip Ghoshal , Yao-Ting Wang , Miguel Ballesteros , Yassine Benajiba

Memory constraint of always-on devices is one of the major concerns when deploying speech processing models on these devices. While larger models trained with sufficiently large amount of data generally perform better, making them fit in…

Computation and Language · Computer Science 2024-01-09 Yiming Wang , Jinyu Li

Many real world data sets exhibit an embedding of low-dimensional structure in a high-dimensional manifold. Examples include images, videos and internet traffic data. It is of great significance to reduce the storage requirements and…

Methodology · Statistics 2015-06-05 Yuejie Chi , Yonina C. Eldar , Robert Calderbank

Given a sequence of tokens, such as words, the task of next-token prediction is to predict the next-token conditional probability distribution. Decoder-only transformers have become effective models for this task, but their properties are…

Machine Learning · Computer Science 2025-11-25 Liam Madden , Curtis Fox , Christos Thrampoulidis

Sequence-to-sequence models have achieved impressive results on various tasks. However, they are unsuitable for tasks that require incremental predictions to be made as more data arrives or tasks that have long input sequences and output…

Machine Learning · Computer Science 2016-08-08 Navdeep Jaitly , David Sussillo , Quoc V. Le , Oriol Vinyals , Ilya Sutskever , Samy Bengio

We answer an open question in the theory of transducer degrees initially posed in [3], on the structure of polynomial transducer degrees, in particular the question of what degrees, if any, lie below the degree of $n^3$. Transducer degrees…

Formal Languages and Automata Theory · Computer Science 2021-11-15 Noah Kaufmann

In fields such as medicine and drug discovery, the ultimate goal of a classification is not to guess a class, but to choose the optimal course of action among a set of possible ones, usually not in one-one correspondence with the set of…

Machine Learning · Computer Science 2023-02-22 K. Dyrland , A. S. Lundervold , P. G. L. Porta Mana

Modern large language models (LLMs) excel at tasks that require storing and retrieving knowledge, such as factual recall and question answering. Transformers are central to this capability because they can encode information during training…

Machine Learning · Statistics 2026-03-18 Nuri Mert Vural , Alberto Bietti , Mahdi Soltanolkotabi , Denny Wu

We generalize the notion of the stopping redundancy in order to study the smallest size of a trapping set in Tanner graphs of linear block codes. In this context, we introduce the notion of the trapping redundancy of a code, which…

Information Theory · Computer Science 2016-11-17 Stefan Laendner , Thorsten Hehn , Olgica Milenkovic , Johannes B. Huber

You might know that the name "tree transducers" refers to various kinds of automata that compute functions on ranked trees, i.e. terms over a first-order signature. But have you ever wondered about how to remember what a macro tree…

Formal Languages and Automata Theory · Computer Science 2024-09-12 Lê Thành Dũng Nguyên

A few models have tried to tackle the link prediction problem, also known as knowledge graph completion, by embedding knowledge graphs in comparably lower dimensions. However, the state-of-the-art results are attained at the cost of…

Machine Learning · Computer Science 2022-11-29 Peyman Baghershahi , Reshad Hosseini , Hadi Moradi

Top-down tree transducers are a convenient formalism for describing tree transformations. They can be equipped with regular look-ahead, which allows them to inspect a subtree before processing it. In certain cases, such a look-ahead can be…

Formal Languages and Automata Theory · Computer Science 2015-12-04 Joost Engelfriet , Sebastian Maneth , Helmut Seidl

Binary embedding is a nonlinear dimension reduction methodology where high dimensional data are embedded into the Hamming cube while preserving the structure of the original space. Specifically, for an arbitrary $N$ distinct points in…

Data Structures and Algorithms · Computer Science 2019-01-24 Xinyang Yi , Constantine Caramanis , Eric Price

A MapReduce algorithm can be described by a mapping schema, which assigns inputs to a set of reducers, such that for each required output there exists a reducer that receives all the inputs that participate in the computation of this…

Databases · Computer Science 2015-01-28 Foto Afrati , Shlomi Dolev , Ephraim Korach , Shantanu Sharma , Jeffrey D. Ullman

In this paper, I introduce the retrieval problem, a simple yet common reasoning task that can be solved only by transformers with a minimum number of layers, which grows logarithmically with the input size. I empirically show that large…

Machine Learning · Computer Science 2025-10-29 Tiberiu Musat

Single-ended circuit topologies, and a theorem for the development thereof, are presented with which one may realize constant-resistance (or reflectionless) filters, having ideally zero reflection coefficient at all frequencies and from all…

Instrumentation and Methods for Astrophysics · Physics 2019-04-09 Augusto Guilabert , Matthew Morgan , Tod Boyd

Codes over permutations under the infinity norm have been recently suggested as a coding scheme for correcting limited-magnitude errors in the rank modulation scheme. Given such a code, we show that a simple relabeling operation, which…

Information Theory · Computer Science 2011-09-20 Itzhak Tamo , Moshe Schwartz

A pebbling move on a graph removes two pebbles at a vertex and adds one pebble at an adjacent vertex. Rubbling is a version of pebbling where an additional move is allowed. In this new move, one pebble each is removed at vertices $v$ and…

Combinatorics · Mathematics 2010-09-28 Gyula Y. Katona , Nandor Sieben

This paper develops new methods to recover the missing entries of a high-rank or even full-rank matrix when the intrinsic dimension of the data is low compared to the ambient dimension. Specifically, we assume that the columns of a matrix…

Machine Learning · Computer Science 2019-12-17 Jicong Fan , Yuqian Zhang , Madeleine Udell

Visibly pushdown transducers form a subclass of pushdown transducers that (strictly) extends finite state transducers with a stack. Like visibly pushdown automata, the input symbols determine the stack operations. In this paper, we prove…

Formal Languages and Automata Theory · Computer Science 2015-05-18 Emmanuel Filiot , Jean-François Raskin , Pierre-Alain Reynier , Frédéric Servais , Jean-Marc Talbot