Good Papers

Showing papers from Vrije Universiteit Amsterdam Show all papers

45%Niche pick
?Niche pickVote to see the score

EDMA: Entropy-Driven Multimodal Answering

Emanuele Mezzi, Gertjan Burghouts, Fabio Massacci, Mengyuan Zhang

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

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

Cornerstones or Stumbling Blocks? Deciphering the Rock Tokens in On-Policy Distillation

Yuxuan Jiang, Runchao Li, Shubhashis Roy Dipta, Dawei Li and 1 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

Where to Approximate in Neurosymbolic Inference?

Samy Badreddine, Emile van Krieken, Luciano Serafini, Antonio Vergari

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

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
83%Must read
?Must readVote to see the score

Hadamard Representation: Scaffolding Performance Across Model-free RL

Hadamard Representation replaces hidden layers with element-wise products of two layers, reducing neuron dormancy and increasing effective rank to consistently improve model-free RL performance.

Jacob Eeuwe Kooi, Zhao Yang, Mark Hoogendoorn, Vincent Francois-Lavet

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

– ReadersNo votes yet
13/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 13 of 20 reviewers recommend it
lenient 4/5
medium 8/10
strict 1/5
80%Must read
?Must readVote to see the score

Hierarchical Conformal Classification

Hierarchical conformal classification extends prediction sets to class hierarchies via constrained optimization, maintaining coverage guarantees while yielding smaller, semantically structured sets that annotators prefer.

Floris den Hengst, Inès Blin, Majid Mohammadi, Syed I Shah and 1 more

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

– ReadersNo votes yet
12/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 1/5
76%Highly rated
?Highly ratedVote to see the score

EMERGE: A Benchmark for Updating Knowledge Graphs with Emerging Textual Knowledge

EMERGE benchmarks knowledge graph updates via 233K Wikipedia passages mapped to 1.45M Wikidata edits across 2019, 2025. Experiments highlight challenges integrating emerging textual knowledge with existing graph structures.

Klim Zaporojets, Daniel Daza, Edoardo Barba, Ira Assent and 2 more

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

– ReadersNo votes yet
10/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 10 of 20 reviewers recommend it
lenient 5/5
medium 3/10
strict 2/5
89%Must read
?Must readVote to see the score

Predicting Only from Selected Evidence: A Tempered Product-of-Experts Bottleneck for Auditable EEG Diagnosis

tPoE-EIB constrains EEG diagnosis to selected evidence via tempered product-of-experts fusion, improving auditable selection and integration faithfulness while preserving accuracy.

Yinghao WANG, Shujian Yu, Duc-Han LE, Zhikai Yu and 2 more

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

– ReadersNo votes yet
16/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 16 of 20 reviewers recommend it
lenient 5/5
medium 10/10
strict 1/5
70%Highly rated
?Highly ratedVote to see the score

Neural Backward Filtering Forward Guiding

NBFFG uses a proxy linear-Gaussian backward filter and neural residual to guide inference in nonlinear continuous tree processes, reducing training cost to path-length dependence and outperforming baselines in phylogenetic reconstruction.

Gefan Yang, Frank van der Meulen, Stefan Sommer

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

– ReadersNo votes yet
5/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 5 of 20 reviewers recommend it
lenient 3/5
medium 2/10
strict 0/5
80%Must read
?Must readVote to see the score

Temporal Consistency Improves Generalization in Contextual Offline Meta Reinforcement Learning

Enforcing multi-step latent predictions improves context-based offline meta-RL by capturing task dynamics, reducing value errors, and boosting zero-shot and few-shot generalization.

Mohammadreza Nakhaeinezhad, Aidan Scannell, Kevin Luck, Joni Pajarinen

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

– ReadersNo votes yet
12/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 12 of 20 reviewers recommend it
lenient 3/5
medium 8/10
strict 1/5