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From the 1 of 13 linked papers with an AI index.

activity
20242026
collaborators

13 papers

cs.GT2026

Generalised Reachability Games

Sougata Bose, Nathanael Fijalkow, Daniel Hausmann +4

The paper investigates two-player turn-based games on graphs where a player must visit multiple target sets (generalised reachability), analyzing the computational complexity, para…

cs.LG2026

Transformers Linearly Represent Highly Structured World Models

Roman Kniazev, Nathanaël Fijalkow

Do transformers, when trained on sequential reasoning traces, build internal models of the underlying task? And if so, does the structure of those internal representations mirror t…

cs.PL2026

GPU-Accelerated Synthesis of Mixed-Boolean Arithmetic: Beyond Caching

Gabriel Bathie, Baptiste Mouillon, Nathanaël Fijalkow

Synthesizing Mixed-Boolean Arithmetic (MBA) expressions from input-output examples is central to program deobfuscation and also useful for compiler optimization, reverse engineerin…

cs.AI2026

Computing the Reachability Value of Posterior-Deterministic POMDPs

Nathanaël Fijalkow, Arka Ghosh, Roman Kniazev +2

Partially observable Markov decision processes (POMDPs) are a fundamental model for sequential decision-making under uncertainty. However, many verification and synthesis problems…

cs.AI2026

Scalable Anytime Algorithms for Learning Fragments of Linear Temporal Logic

Ritam Raha, Rajarshi Roy, Nathanaël Fijalkow +1

Linear temporal logic (LTL) is a specification language for finite sequences (called traces) widely used in program verification, motion planning in robotics, process mining, and m…

cs.AI2026

LTL Learning Meets Boolean Set Cover

Gabriel Bathie, Nathanaël Fijalkow, Théo Matricon +2

Learning formulas in Linear Temporal Logic (LTLf) from finite traces is a fundamental research problem which has found applications in artificial intelligence, software engineering…