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Showing papers from Hebrew University of Jerusalem Show all papers

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NeurIPS 2026MasarykBar Ilan University, TechnionBen Gurion University of the NegU California, RiversideBar IlanAdversarial robustness

Pareto DNN Verification: Fast for Most Queries

Yizhak Y. Elboher, Avraham Raviv, Amihay Elboher, Zhouxing Shi and 2 more

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

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NeurIPS 2026Hebrew University of JerusalemMasarykExplainable AI

Provable Explanations for Any-Order Neural Additive Models

Idan Refaeli, Shahaf Bassan, Yizhak Y. Elboher, Guy Katz

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

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83%Must read
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NeurIPS 2026OralHebrew University of JerusalemDiffusion models

Colored Noise Diffusion Sampling

Colored Noise Sampling replaces uniform noise with dynamic frequency-dependent schedules to exploit diffusion spectral bias, substantially reducing FID across architectures as a training-free plug-in.

Hadar Davidson, Noam Issachar, Sagie Benaim

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 19 on Hugging Face · Code ★ 45

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AI panel: 13 of 20 reviewers recommend it
lenient 3/5
medium 9/10
strict 1/5
76%Highly rated
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NeurIPS 2026SpotlightHebrew University of JerusalemLearning theory

Domination-Avoiding Learning Agents Cannot Collude

Domination-avoiding learning agents provably avoid collusion in competitive markets and converge to non-dominated strategies.

Noam Nisan, Emmanuel Zerah

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

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lenient 3/5
medium 4/10
strict 3/5
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NeurIPS 2026The Hebrew University of JerusalNew YorkHebrew University of JerusalemColumbia University, GoogleLLM reasoning & chain of thought

Discrete Diffusion Models Exploit Asymmetry to Solve Lookahead Planning Tasks

Discrete diffusion models exploit reverse generation asymmetry to solve lookahead planning with exponentially less data and shallower architectures than autoregressive models.

Itamar Trainin, Shauli Ravfogel, Omri Abend, Amir Feder

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

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AI panel: 10 of 20 reviewers recommend it
lenient 4/5
medium 5/10
strict 1/5
88%Must read
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NeurIPS 2026AmazonTel AvivHebrew University of JerusalemControllable generation

TrajLoc: Trajectory-Attention Localization for Multi-Object Motion Control

TrajLoc isolates per-object attention via Gaussian heatmaps to control multi-object motion, improving trajectory adherence by 51% and PSNR by 4.3 dB.

Omer Sela, Inbar Huberman-Spiegelglas, Michael Rotman, Sagie Benaim and 1 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 1 on Hugging Face · Code ★ 2

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15/20 AI panelreviewers recommend it

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AI panel: 15 of 20 reviewers recommend it
lenient 4/5
medium 8/10
strict 3/5