Turn Complexity of Context-free Languages, Pushdown Automata and One-Counter Automata

This paper investigates the computational complexity of context-free, pushdown, and one-counter automata based on the number of "turns" (switches between increasing and decreasing stack height) in accepting computations, proving that determining whether this number is bounded is undecidable, establishing non-recursive trade-offs between automata types, and demonstrating an infinite hierarchy of complexity classes defined by sublinear turn bounds.

Giovanni PighizziniTue, 10 Ma💻 cs

Randomise Alone, Reach as a Team

This paper investigates concurrent graph games with distributed randomization where team players lack a shared random source, establishing that memoryless strategies suffice for the threshold problem (placing it in R\exists\mathbb{R} and proving NP-hardness) and that almost-sure reachability is NP-complete, while introducing the IRATL logic and a corresponding solver.

Léonard Brice, Thomas A. Henzinger, Alipasha Montaseri, Ali Shafiee, K. S. ThejaswiniTue, 10 Ma💻 cs

Mining Beyond the Bools: Learning Data Transformations and Temporal Specifications

This paper proposes a novel approach to mining data-aware temporal specifications from execution traces by combining Syntax Guided Synthesis with a finite-prefix interpretation of Temporal Stream Logic (TSLf_f), enabling the robust and sample-efficient synthesis of reactive programs that capture both data transformations and temporal behaviors.

Sam Nicholas Kouteili, William Fishell, Christian Scaff, Mark Santolucito, Ruzica PiskacTue, 10 Ma💻 cs

FATE: A Formal Benchmark Series for Frontier Algebra of Multiple Difficulty Levels

The paper introduces FATE, a new formal algebra benchmark series spanning from undergraduate exercises to PhD-level research problems, which reveals that current state-of-the-art LLMs struggle significantly with formalizing advanced mathematical reasoning, achieving near-zero accuracy on the most difficult tasks despite stronger natural-language performance.

Jiedong Jiang, Wanyi He, Yuefeng Wang, Guoxiong Gao, Yongle Hu, Jingting Wang, Nailin Guan, Peihao Wu, Chunbo Dai, Liang Xiao, Bin DongTue, 10 Ma🤖 cs.LG

The Generation-Recognition Asymmetry: Six Dimensions of a Fundamental Divide in Formal Language Theory

This paper proposes a unified framework for the generation-recognition asymmetry in formal language theory by identifying six distinct dimensions of divergence, challenging the oversimplified view that generation is inherently easy while parsing is hard, and exploring the implications of these operational differences for fields ranging from compiler design to large language models.

Romain PeyrichouThu, 12 Ma💬 cs.CL

Attention Meets Reachability: Structural Equivalence and Efficiency in Grammar-Constrained LLM Decoding

This paper establishes that while language-equivalent context-free grammars yield identical token masks in grammar-constrained decoding, their structural differences significantly impact computational efficiency by introducing variable state-space blowups and ambiguity costs, leading to fundamental lower bounds on decoding work and new distortion metrics for masked sampling.

Faruk Alpay, Bilge SenturkMon, 09 Ma🤖 cs.LG

Reachability in VASS Extended with Integer Counters

This paper investigates the reachability problem for VASS extended with integer counters (VASS+Z), establishing that the problem is NP-complete for a single nonnegative counter, lies in the complexity class Fd+2\mathcal{F}_{d+2} for d2d \geq 2 via a KLMST-based algorithm, and significantly lowers the dimension required for PSPACE and TOWER hardness compared to standard VASS.

Clotilde Bizière, Wojciech Czerwiński, Roland Guttenberg + 5 more2026-03-06💻 cs

Why Are Linear RNNs More Parallelizable?

This paper establishes a theoretical foundation for the superior parallelizability of linear RNNs by demonstrating that they correspond to log-depth arithmetic circuits (NC1\mathsf{NC}^1-complete), whereas nonlinear RNNs are fundamentally limited by their ability to solve L\mathsf{L}- and P\mathsf{P}-complete problems, thereby explaining why linear variants can be efficiently parallelized like transformers while traditional nonlinear RNNs cannot.

William Merrill, Hongjian Jiang, Yanhong Li + 2 more2026-03-06💻 cs