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Showing papers from Institute of Science and Technology Austria Show all papers

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Speculative Self-Distillation enables Efficient Knowledge Internalization

Shayan Talaei, Agam Bhatia, Arshia Soltani Moakhar, Jonas Hübotter 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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57%Worth a look
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MorphGen: Controllable Cell-Image Generation with Biological Representation Alignment

Berker Demirel, Marco Fumero, Theofanis Karaletsos, Francesco Locatello

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

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AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
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Causal Discovery Under Hard Selection Bias: A New Robust Score-Matching Approach

Yiwen Qiu, Francesco Montagna, Shimeng Huang, Francesco Locatello

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

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AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
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On Differentially Private Mechanisms for Linear Regression

Bardiya Aryanfard, Monika Henzinger, Farhood Rostamkhani

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
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Symplectic Reck: In-Situ Learning of Gaussian Quantum Operations

Janet Zhong, Renwen Yu, Charles Roques-Carmes, Paul-Alexis MOR and 3 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
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78%Highly rated
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Causal learning with the invariance principle

Assuming acyclic, invariant causal relations across environments, two auxiliary environments identify arbitrary nonlinear causal graphs and enable correct counterfactual inference.

Francesco Montagna, Francesco Locatello

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

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11/20 AI panelreviewers recommend it

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AI panel: 11 of 20 reviewers recommend it
lenient 5/5
medium 5/10
strict 1/5
71%Highly rated
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Sink vs. diagonal patterns as mechanisms for attention switch and oversmoothing prevention

Sinks and diagonal patterns serve as attention switches and anti-oversmoothing mechanisms, with sinks favored in pretrained transformers due to lower representation costs.

Peter Súkeník, Cristina Lopez Amado, Christoph Lampert, Marco Mondelli

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

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6/20 AI panelreviewers recommend it

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AI panel: 6 of 20 reviewers recommend it
lenient 1/5
medium 3/10
strict 2/5
71%Highly rated
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Reconciling Causality and Non-Equilibrium Thermodynamics with Hamiltonian Causal Models

Hamiltonian Causal Models separate equations of motion from intervenable mechanisms and define causal effects as interventional path discrepancies, showing entropy production witnesses trajectory-level causal effects invisible to standard average treatment effects.

Dario Rancati, Max Welling, Francesco Locatello

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

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AI panel: 6 of 20 reviewers recommend it
lenient 2/5
medium 4/10
strict 0/5
76%Highly rated
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The Rate-Distortion-Polysemanticity Tradeoff in SAEs

Sparse autoencoders face a rate-distortion-polysemanticity tradeoff where monosemanticity raises reconstruction cost and data co-occurrence drives polysemanticity.

Tommaso Mencattini, Francesco Montagna, Francesco Locatello

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

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10/20 AI panelreviewers recommend it

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AI panel: 10 of 20 reviewers recommend it
lenient 4/5
medium 5/10
strict 1/5
86%Must read
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Assessing Sample Quality in Conditional Generation under Compositional Shift

A per-sample trust score combining global realism and attribute-wise faithfulness evaluates conditional generations under compositional shift without reference data, enabling filtering and ranking that improves biological imaging and vision benchmarks.

Berker Demirel, Valentino Maiorca, Marco Fumero, Theofanis Karaletsos and 1 more

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

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14/20 AI panelreviewers recommend it

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AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 1/5
70%Highly rated
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Multi-Environment POMDPs with Finite-Horizon Objectives

Finite-horizon multi-environment POMDP optimization is PSPACE-complete, and a new practical algorithm significantly outperforms prior methods on benchmarks.

Léonard Brice, Filip Cano, Krishnendu Chatterjee, Thomas Henzinger and 1 more

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

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5/20 AI panelreviewers recommend it

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AI panel: 5 of 20 reviewers recommend it
lenient 1/5
medium 3/10
strict 1/5