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Showing papers from Eindhoven University of Technology Show all papers

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On the Tightness and Computational Tractability of Higher-Dimensional Confidence Sequences

Fabian Denoodt, Sibylle Hess, Joaquin Vanschoren, Christian Andersson Naesseth

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Decomposing Effects in Neural Causal Models

Matej Zečević, Devendra Singh Dhami, Kristian Kersting

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

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57%Worth a look
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Unpacking the Evaluators: How Configuration Shapes the Evaluation of Alignment in Explainable AI

Gizem Karagoz, Tanir Özçelebi, Nirvana Meratnia

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
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67%Highly rated
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SWE-GPU-Bench: Can Language Models Solve Real-World GPU Software Engineering Tasks?

Feng Chen, binbin liu, Wenhan Han, Yin Zheng

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

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AI panel: 2 of 20 reviewers recommend it
lenient 2/5
medium 0/10
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45%Niche pick
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PDHFormer: Progressive Dual-Head Transformer for Behavioral Choice Prediction

Hao Zhou, Jing Chen, Yaoxin Wu, Jie Gao and 1 more

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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74%Highly rated
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TransmissiveGS: Residual-Guided Disentangled Gaussian Splatting for Transmissive Scene Reconstruction and Rendering

TransmissiveGS disentangles reflective and transmissive components via dual Gaussian representations and residual-guided multi-view separation for transmissive scene reconstruction.

Zhenyu Liang, Xiao Zhang, Tianchao Li, Jack C Cheng and 1 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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AI panel: 9 of 20 reviewers recommend it
lenient 4/5
medium 5/10
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83%Must read
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KroQuant: Kronecker-Structured Block Transforms for Efficient Post-Training Quantization of Diffusion Transformers

KroQuant applies a learned Kronecker-structured block transform to DiT activations for efficient W4A4 post-training quantization that outperforms SVDQuant and LoRaQ on image quality.

Yann Bouquet, Alireza Khodamoradi, Kristof Denolf, Mathieu Salzmann

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

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13/20 AI panelreviewers recommend it

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AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 0/5
70%Highly rated
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Causal Abstractions, Categorically Unified

A categorical framework defines causal abstractions as natural transformations between Markov functors, unifying prior notions, yielding graphical consistency conditions, and validating high-level do-calculus on low-level graphs with unobserved confounders.

Markus Englberger, Devendra Singh Dhami

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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AI panel: 4 of 20 reviewers recommend it
lenient 1/5
medium 2/10
strict 1/5
76%Highly rated
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Matching-Based Few-Shot Semantic Segmentation Models Are Interpretable by Design

Affinity Explainer leverages matching-based FSS architectures to extract support-pixel attribution maps outperforming standard attribution methods and enabling model diagnosis.

Pasquale De Marinis, Uzay Kaymak, Rogier Brussee, Gennaro Vessio and 1 more

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

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AI panel: 10 of 20 reviewers recommend it
lenient 4/5
medium 6/10
strict 0/5
86%Must read
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LoRaQ: Optimized Low Rank Approximation for 4-bit Quantization

LoRaQ uses data-free optimization to quantize low-rank branches for 4-bit diffusion transformers, outperforming high-precision methods at equal overhead.

Yann Bouquet, Alireza Khodamoradi, Sophie Y Shen, Kristof Denolf and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 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
74%Highly rated
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Computing Thiele Rules on Interval Elections and their Generalizations

Thiele rules are polynomial-time computable on voter-interval and linearly consistent domains via integral linear programming, and linearly consistent domains strictly contain voter-candidate interval domains, though tree-based extensions are NP-hard.

Dimitris Avramidis, Alexandra Anna Lassota, Ulrike Schmidt-Kraepelin, Adrian Vetta

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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9/20 AI panelreviewers recommend it

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AI panel: 9 of 20 reviewers recommend it
lenient 0/5
medium 6/10
strict 3/5
80%Must read
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LithoBench: Benchmarking Large Multimodal Models for Remote-Sensing Lithology Interpretation

LithoBench evaluates large multimodal models on remote-sensing lithology interpretation via expert-annotated multi-level tasks, revealing substantial limitations in geological reasoning.

jun wang, Fengpeng Li, Tianjin Huang, Hang Dong 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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12/20 AI panelreviewers recommend it

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AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 5/10
strict 2/5