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Showing papers from Jagiellonian University Show all papers

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NeurIPS 2026Jagiellonian University CracowJagiellonian University, GMUMJagiellonianExplainable AI

ProDG: Prototypes for Data-Free Generative Post-Hoc Explainability

Piotr Borycki, Magdalena Trędowicz, Jacek Tabor, Łukasz Struski and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026NASK - National Research InstituJagiellonianWarsaw University of Technology,NASK - National Research InstituProbing & representation analysis

Monitoring the Internal Monologue: Probe Trajectories Reveal Reasoning Dynamics

Maciej Chrabaszcz, Aleksander Szymczyk, Marcin Sendera, Tomasz Trzcinski and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026JagiellonianLLM evaluation & benchmarks

FACBench: A Benchmark for Formal-Anchor Collisions in Multilingual Mathematical Grounding

Piotr Kuterba, Józef Spałek

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026U Toronto, Vector InstituteU WaterlooThe Hospital for Sick ChildrenU TorontoJagiellonianMolecules & drug discovery

Hit Expansion via Localized Exploration of Synthesizable Chemical Space

Walter Virany, Yidong Jin, Andrew Lian, Dmytro Shevchuk and 5 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026JagiellonianHelmholtz Zentrum München GmbH FJohns Hopkins University, UniBo,Johns HopkinsNational Medical Institute of thVision-language models

Anatomy-Activated Mixture-of-Experts for 3D Medical Vision-Language Pre-training

Szymon Płotka, Gizem Mert, Pedro R. A. S. Bassi, Wenxuan Li and 8 more

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

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76%Highly rated
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NeurIPS 2026Wroclaw TechJagiellonian University in KrakoJagiellonianWroclaw University of Science anExplainable AI

CounterFlowNet: From Minimal Changes to Meaningful Counterfactual Explanations

CounterFlowNet uses generative flow networks to generate sequential, sparse counterfactual explanations for tabular data with enforced actionability constraints and improved validity-sparsity trade-offs.

Oleksii Furman, Patryk Marszałek, Jan Masłowski, Marek Śmieja and 2 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 10 of 20 reviewers recommend it
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medium 6/10
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74%Highly rated
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NeurIPS 2026Jagiellonian University in KrakoIDEAS Research Institute JagiellJagiellonianIDEAS Research InstituteRepresentation & contrastive learning

InTAct: Interval-based Task Activation Consolidation for Continual Learning

InTAct prevents catastrophic forgetting via neuron-level activation interval constraints providing functional invariance guarantees with greater efficiency than weight-space methods.

Patryk Krukowski, Jan Miksa, Piotr Helm, Jacek Tabor and 2 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 9 of 20 reviewers recommend it
lenient 4/5
medium 5/10
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78%Highly rated
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NeurIPS 2026U Edinburgh, United KingdomJagiellonian University, ul. GołJagiellonian University in KrakoJagiellonianExplainable AI

B-XAIC Dataset: Benchmarking Explainable AI for Graph Neural Networks Using Chemical Data

B-XAIC benchmark evaluates explainable AI for graph neural networks on real molecular tasks with ground-truth rationales, revealing major limitations in current explanation methods.

Magdalena Proszewska, Tomasz Danel, Antoni Antoszek, Dawid Damian Rymarczyk

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 11 of 20 reviewers recommend it
lenient 5/5
medium 5/10
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