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We give deterministic black-box polynomial identity testing algorithms for multilinear read-once oblivious algebraic branching programs (ROABPs), in n^(lg^2 n) time. Further, our algorithm is oblivious to the order of the variables. This is…

Computational Complexity · Computer Science 2013-09-24 Michael A. Forbes , Ramprasad Saptharishi , Amir Shpilka

Large Vision-Language Models (LVLMs) demonstrate exceptional performance across multimodal tasks, yet remain vulnerable to jailbreak attacks that bypass built-in safety mechanisms to elicit restricted content generation. Existing black-box…

Computation and Language · Computer Science 2025-06-23 Lei Jiang , Zixun Zhang , Zizhou Wang , Xiaobing Sun , Zhen Li , Liangli Zhen , Xiaohua Xu

There has been substantial progress in the inference of formal behavioural specifications from sample trajectories, for example, using Linear Temporal Logic (LTL). However, these techniques cannot handle specifications that correctly…

Logic in Computer Science · Computer Science 2025-05-20 Rajarshi Roy , Yash Pote , David Parker , Marta Kwiatkowska

Large Reasoning Models (LRMs) have recently demonstrated impressive performances across diverse domains. However, how the safety of Large Language Models (LLMs) benefits from enhanced reasoning capabilities against jailbreak queries remains…

Computation and Language · Computer Science 2025-09-23 Junda Zhu , Lingyong Yan , Shuaiqiang Wang , Dawei Yin , Lei Sha

As fragments of first-order logic, Description logics (DLs) do not provide nonmonotonic features such as defeasible inheritance and default rules. Since many applications would benefit from the availability of such features, several…

Logic in Computer Science · Computer Science 2014-01-16 Piero A. Bonatti , Carsten Lutz , Frank Wolter

In a previous work Baillot and Terui introduced Dual light affine logic (DLAL) as a variant of Light linear logic suitable for guaranteeing complexity properties on lambda calculus terms: all typable terms can be evaluated in polynomial…

Logic in Computer Science · Computer Science 2015-07-01 Vincent Atassi , Patrick Baillot , Kazushige Terui

The low-degree polynomial framework has been highly successful in predicting computational versus statistical gaps for high-dimensional problems in average-case analysis and machine learning. This success has led to the low-degree…

Machine Learning · Statistics 2026-03-04 He Jia , Aravindan Vijayaraghavan

We investigate fine-grained algorithmic aspects of identification problems in graphs and set systems, with a focus on Locating-Dominating Set and Test Cover. We prove the (tight) conditional lower bounds for these problems when…

Data Structures and Algorithms · Computer Science 2025-08-25 Dipayan Chakraborty , Florent Foucaud , Diptapriyo Majumdar , Prafullkumar Tale

Augmented Language Models (ALMs) blend the reasoning capabilities of Large Language Models (LLMs) with tools that allow for knowledge retrieval and action execution. Existing ALM systems trigger LLM thought processes while pulling…

Computation and Language · Computer Science 2023-05-31 Binfeng Xu , Zhiyuan Peng , Bowen Lei , Subhabrata Mukherjee , Yuchen Liu , Dongkuan Xu

A {\it dynamic reasoning system} (DRS) is an adaptation of a conventional formal logical system that explicitly portrays reasoning as a temporal activity, with each extralogical input to the system and each inference rule application being…

Artificial Intelligence · Computer Science 2014-04-30 Daniel G. Schwartz

Offline reinforcement learning (RL) enables policy learning from pre-collected datasets, avoiding costly and risky online interactions, but it often struggles with long-horizon tasks involving sparse rewards. Existing goal-conditioned and…

Machine Learning · Computer Science 2026-01-14 Chengyang Gu , Yuxin Pan , Hui Xiong , Yize Chen

Safely exploring an unknown dynamical system is critical to the deployment of reinforcement learning (RL) in physical systems where failures may have catastrophic consequences. In scenarios where one knows little about the dynamics, diverse…

Machine Learning · Computer Science 2017-12-01 Tyler Lu , Martin Zinkevich , Craig Boutilier , Binz Roy , Dale Schuurmans

Offline reinforcement learning (RL) aims to find an optimal policy for Markov decision processes (MDPs) using a pre-collected dataset. In this work, we revisit the linear programming (LP) reformulation of Markov decision processes for…

Machine Learning · Computer Science 2024-12-11 Asuman Ozdaglar , Sarath Pattathil , Jiawei Zhang , Kaiqing Zhang

Partial Differential Equations (PDEs) are central to science and engineering. Since solving them is computationally expensive, a lot of effort has been put into approximating their solution operator via both traditional and recently…

Machine Learning · Computer Science 2025-02-14 Alessandro Longhi , Danny Lathouwers , Zoltán Perkó

The relevance of polynomial formula classes to deductive efficiency motivated their search, and currently, a great number of such classes is known. Nonetheless, they have been exclusively sought in the setting of clausal form and…

Logic in Computer Science · Computer Science 2021-10-26 Gonzalo E. Imaz

The Description Logic EL has recently drawn considerable attention since, on the one hand, important inference problems such as the subsumption problem are polynomial. On the other hand, EL is used to define large biomedical ontologies.…

Artificial Intelligence · Computer Science 2015-07-01 Franz Baader , Barbara Morawska

We combine dependent types with linear type systems that soundly and completely capture polynomial time computation. We explore two systems for capturing polynomial time: one system that disallows construction of iterable data, and one,…

Logic in Computer Science · Computer Science 2023-11-16 Robert Atkey

Reducing the conditions under which a given set satisfies the stipulations of the subset sum proposition to a set of linear relationships, the question of whether a set satisfies subset sum may be answered in a polynomial number of steps by…

Data Structures and Algorithms · Computer Science 2017-05-16 Aubrey Alston

We define the notion of rational closure in the context of Description Logics extended with a tipicality operator. We start from ALC+T, an extension of ALC with a typicality operator T: intuitively allowing to express concepts of the form…

Artificial Intelligence · Computer Science 2013-05-07 Laura Giordano , Valentina Gliozzi , Nicola Olivetti , Gian Luca Pozzato

We introduce a proof system for Hajek's logic BL based on a relational hypersequents framework. We prove that the rules of our logical calculus, called RHBL, are sound and invertible with respect to any valuation of BL into a suitable…

Logic in Computer Science · Computer Science 2007-05-23 S. Bova , F. Montagna