129 ELLIS Posters
Microcanonical Langevin Ensembles: Advancing the Sampling of Bayesian Neural Networks
Emanuel Sommer, Jakob Robnik, Giorgi Nozadze, Uros Seljak, David Rügamer
Multilingual Pretraining for Pixel Language Models
Ilker Kesen, Jonas F. Lotz, Ingo Ziegler, Phillip Rust, Desmond Elliott
Systems with Switching Causal Relations: A Meta-Causal Perspective
Moritz Willig, Tim Woydt, Florian Peter Busch, Jonas Seng, Devendra Singh Dhami, Kristian Kersting
QuEST: Stable Training of LLMs with 1-Bit Weights and Activations
Andrei Panferov, Jiale Chen, Soroush Tabesh, Mahdi Nikdan, Dan Alistarh
On Space Folds of Neural Networks
Michal Lewandowski, Hamid Egbalzadeh, Bernhard Heinzl, Raphael Pisoni, Bernhard A.Moser
DiTASK: Multi-Task Fine-Tuning with Diffeomorphic Transformations
Krishna Sri Ipsit Mantri, Carola-Bibiane Schönlieb, Bruno Ribeiro, Chaim Baskin, Moshe Eliasof
On the Low-Rank Parametrization of Reward Models for Controlled Language Generation
Sergey Troshin, Vlad Niculae, Antske Fokkens
Keep your distance: learning dispersed embeddings on Sm
Evgeniia Tokarchuk, Hua Chang Bakker, Vlad Niculae
ASTrA: Adversarial Self-supervised Training with Adaptive-Attacks
Prakash Chandra Chhipa, Gautam Vashishtha, Settur Jithamanyu, Rajkumar Saini, Mubarak Shah, Marcus Liwicki
Cost-aware simulation-based inference
Ayush Bharti, Daolang Huang, Samuel Kaski, Francois-Xavier Briol
Recent advances in likelihood-free Bayesian inference and its applications
There are too many, we want to make a combined poster from multiple highlight papers on the indicated theme
Paths and Ambient Spaces in Neural Loss Landscapes
Daniel Dold, Julius Kobialka, Nicolai Palm, Emanuel Sommer, David Rügamer, Oliver Dürr
Gradient Extrapolation for Debiased Representation Learning
Ihab Asaad, Maha Shadaydeh, Joachim Denzler
On convex decision regions in deep network representations
Lenka Tětková, Thea Brüsch, Teresa Dorszewski, Fabian Martin Mager, Rasmus Ørtoft Aagaard, Jonathan Foldager, Tommy Sonne Alstrøm, Lars Kai Hansen
Guided Sensing, Generative Thinking: Sparse Flow Reconstruction Reimagined
Sajad Salavatidezfouli, Henrik Karstoft, Alexandros Iosifidis, Mahdi Abkar
Density Ratio Estimation with Conditional Probability Paths
Hanlin Yu, Arto Klami, Aapo Hyvärinen, Anna Korba, Omar Chehab
An Efficient Search-and-Score Algorithm for Ancestral Graphs using Multivariate Information Scores for Complex Non-linear and Categorical Data
Nikita Lagrange, Hervé Isambert
Taking a Big Step: Large Learning Rates in Denoising Score Matching Prevent Memorization
Yu-Han Wu, Pierre Marion, Gérard Biau, Claire Boyer
SFESS: Score Function Estimators for k-Subset Sampling
Klas Wijk, Ricardo Vinuesa, Hossein Azizpour
Safe-EF: Error Feedback for Nonsmooth Constrained Optimization
Rustem Islamov, Yarden As, Ilyas Fatkhullin
Efficient Open Set Single Image Test Time Adaptation of Vision Language Models
Manogna Sreenivas, Soma Biswas
Discriminative Ordering Through Ensemble Consensus
Louis Ohl, Fredrik Lindsten
SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation
Hai Pham, Tung Do, Phong Nguyen, Binh-Son Hua, Khoi Nguyen, Rang Nguyen
ColonScopeX: Leveraging Explainable Expert Systems with Multimodal Data for Improved Early Diagnosis of Colorectal Cancer
Natalia Sikora, Robert L. Manschke, Alethea M. Tang, Peter Dunstan, Dean A. Harris, Su Yang
SEKE: Specialised Experts for Keyword Extraction
Matej Martinc ~Matej_Martinc1 , Thi Hong Hanh TRAN, Senja Pollak, Boshko Koloski
How Redundant Is the Transformer Stack in Speech Representation Models?
Teresa Dorszewski, Albert Kjøller Jacobsen, Lenka Tětková, and Lars Kai Hansen
Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences
Niklas Schmidinger ~Niklas_Schmidinger1 , Lisa Schneckenreiter, Philipp Seidl, Johannes Schimunek, Pieter-Jan Hoedt, Johannes Brandstetter, Andreas Mayr, Sohvi Luukkonen, Sepp Hochreiter, Günter Klambauer
TensorSocket: Shared Data Loading for Deep Learning Training
Ties Robroek, Neil Kim Nielsen, Pinar Tozun
A unifying framework for generalised Bayesian online learning in non-stationary environments
Gerardo Duran-Martin, Leandro Sánchez-Betancourt, Alex Shestopaloff, Kevin Patrick Murphy
Position: Causal Machine Learning Requires Rigorous Synthetic Experiments for Broader Adoption
Audrey Poinsot, Panayiotis Panayiotou, Alessandro Leite, Nicolas Chesneau, Özgür Simsek, Marc Schoenauer
Quantifying Fairness in LLMs Beyond Tokens: A Semantic and Statistical Perspective
Weijie Xu, Yiwen Wang, Chi Xue, Xiangkun Hu, Xi Fang, Guimin Dong, Chandan K. Reddy
FalseReject: A Resource for Improving Contextual Safety and Mitigating Over-Refusals in LLMs via Structured Reasoning
Zhehao Zhang , Weijie Xu, Fanyou Wu, Chandan K. Reddy
Improved Variational Inference in Discrete VAEs using Error Correcting Codes
María Martínez-García, Grace Villacrés, David Mitchell, Pablo M. Olmos
The art of deception: Color visual illusions and diffusion models
Alexandra Gomez-Villa, Kai Wang, C Alejandro Parraga, Bartłomiej Twardowski, Jesus Malo, Javier Vazquez-Corral, Joost van den Weijer
ELBOing Stein: Variational bayes with Stein mixture inference
Ola Rønning; Eric Nalisnick; Christophe Ley; Padhraic Smyth; Thomas Hamelryck
GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks
Taraneh Younesian ~Taraneh_Younesian2 , Daniel Daza, Emile van Krieken, Thiviyan Thanapalasingam, Peter Bloem
Energy-Based Flow Matching for Generating 3D Molecular Structure
Wenyin Zhou, Christopher Iliffe Sprague, Vsevolod Viliuga, Matteo Tadiello, Arne Elofsson, Hossein Azizpour
Prediction hubs are context-informed frequent tokens in LLMs
Beatrix MG Nielsen, Iuri Macocco, Marco Baroni
Limits to scalable evaluation at the frontier: LLM as judge won’t beat twice the data
Florian E. Dorner, Vivian Nastl, Moritz Hardt
How to safely discard features based on aggregate SHAP values
Robi Bhattacharjee, Karolin Frohnapfel, Ulrike von Luxburg
All or None: Identifiable Linear Properties of Next-token Predictors in Language Modeling
Emanuele Marconato, Sébastien Lachapelle, Sebastian Weichwald, Luigi Gresele
Disentangling Interactions and Dependencies in Feature Attribution
Gunnar König, Eric Günther, Ulrike von Luxburg
Numerically Robust Fixed-Point Smoothing Without State Augmentation
Nicholas Krämer
A Model Zoo on Phase Transitions in Neural Networks
Konstantin Schürholt, Léo Meynent, Yefan Zhou, Haiquan Lu, Yaoqing Yang, Damian Borth
Can LLMs Separate Instructions From Data? And What Do We Even Mean By That?
Egor Zverev, Sahar Abdelnabi, Soroush Tabesh, Mario Fritz, Christoph H Lampert
Identifying Metric Structures of Deep Latent Variable Models
Stas Syrota, Yevgen Zainchkovskyy, Johnny Xi, Benjamin Bloem-Reddy, Søren Hauberg
Unstructured Evidence Attribution for Long Context Query Focused Summarization
Dustin Wright , Zain Muhammad Mujahid, Lu Wang, Isabelle Augenstein, David Jurgens
Efficient Knowledge Injection in LLMs via Self-Distillation
Kalle Kujanpää, Pekka Marttinen, Harri Valpola, Alexander Ilin
How Much Do LLMs Hallucinate across Languages? On Realistic Multilingual Estimation of LLM Hallucination
Saad Obaid Ul Islam, Anne Lauscher, Goran Glavaš
TinyFoA: Memory Efficient Forward-Only Algorithm for On-Device Learning
Baichuan Huang, Amir Aminifar
The Impact of Inference Acceleration on Bias of LLMs
Elisabeth Kirsten, Ivan Habernal, Vedant Nanda, Muhammad Bilal Zafar
Multi-Modal Framing Analysis of News
Arnav Arora, Srishti Yadav, Maria Antoniak, Serge Belongie, Isabelle Augenstein
From Sound to Sight: Towards AI-authored Music Videos
Leo Vitasovic, Stella Graßhof, Agnes Mercedes Kloft, Ville V. Lehtola, Martin Cunneen, Justyna Starostka, Glenn McGarry, Kun Li, Sami S. Brandt
Archetypal Analysis for Binary Data
A. Emilie J. Wedenborg, Morten Mørup
S2WTM: Spherical Sliced-Wasserstein Autoencoder for Topic Modeling
Suman Adhya, Debarshi Kumar Sanyal
Relational Conformal Prediction for Correlated Time Series
Andrea Cini, Alexander Jenkins, Danilo Mandic, Cesare Alippi, Filippo Maria Bianchi
Zero-shot Imputation with Foundation Inference Models for Dynamical Systems
Patrick Seifner, Kostadin Cvejoski, Antonia Körner, Ramses Sanchez
MaxCutPool: differentiable feature-aware Maxcut for pooling in graph neural networks
Carlo Abate, Filippo Maria Bianchi
CodeSSM: Towards State Space Models for Code Understanding
Shweta Verma, Abhinav Anand, Mira Mezini
Stabilizing Humanoid Robot Trajectory Generation via Physics-Informed Learning and Control-Informed Steering
Evelyn D'Elia, Paolo Maria Viceconte, Lorenzo Rapetti, Diego Ferigo, Giulio Romualdi, Giuseppe L'Erario, Raffaello Camoriano, Daniele Pucci
No Task Left Behind: Isotropic Model Merging with Common and Task-Specific Subspaces
Daniel Marczak, Simone Magistri, Sebastian Cygert, Bartłomiej Twardowski, Andrew D. Bagdanov, Joost van de Weijer
TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis
Shiyu Wang, Jiawei Li, Xiaoming Shi, Zhou Ye, Baichuan Mo, Wenze Lin, Shengtong Ju, Zhixuan Chu, Ming Jin
Image Generation Diversity Issues and How to Tame Them
Mischa Dombrowski; Weitong Zhang; Sarah Cechnicka; Hadrien Reynaud; Bernhard Kainz
Echoes of Agreement: Argument driven opinion shifts in Large Language models
Avneet Kaur
Video-Language Critic: Transferable Reward Functions for Language-Conditioned Robotics
Minttu Alakuijala, Reginald McLean, Isaac Woungang, Nariman Farsad, Samuel Kaski, Pekka Marttinen, Kai Yuan
Pre-Forgettable Models: Prompt Learning as a Native Mechanism for Unlearning
Rutger Hendrix, Giovanni Patanè, Leonardo G Russo, Simone Carnemolla, Giovanni Bellitto, Federica Proietto Salanitri, Concetto Spampinato, Matteo Pennisi
Video-Panda: Parameter-efficient Alignment for Encoder-free Video-Language Models
Jinhui Yi, Syed Talal Wasim, Yanan Luo, Muzammal Naseer, Juergen Gall
MixANT: Observation-dependent Memory Propagation for Stochastic Dense Action Anticipation
Syed Talal Wasim, Hamid Suleman, Olga Zatsarynna, Muzammal Naseer, Juergen Gall
Multi-Hop Reasoning for Question Answering with Hyperbolic Representations
Simon Welz, Lucie Flek, Akbar Karimi
Understanding the sources of performance in deep drug response models reveals insights and improvements
Nikhil Branson, Pedro R Cutillas, Conrad Bessant
SyncVP: Joint Diffusion for Synchronous Multi-Modal Video Prediction
Enrico Pallotta, Sina Mokhtarzadeh Azar, Shuai Li, Olga Zatsarynna, Jürgen Gall
MixANT: Observation-dependent Memory Propagation for Stochastic Dense Action Anticipation
Syed Talal Wasim, Hamid Suleman, Olga Zatsarynna, Muzammal Naseer, Juergen Gall
REPEAT: improving uncertainty estimation in representation learning explainability
Kristoffer K. Wickstrøm, Thea Brüsch, Michael C. Kampffmeyer, Robert Jenssen
Capturing Temporal Dynamics in Large-Scale Canopy Tree Height Estimation
Jan Pauls, Max Zimmer, Berkant Turan, Sassan Saatchi, Philippe Ciais, Sebastian Pokutta, Fabian Gieseke
Start Smart: Leveraging Gradients For Enhancing Mask-based XAI Methods
Buelent Uendes, Shujian Yu, Mark Hoogendoorn
Certified Guidance for Planning with Deep Generative Models
Francesco Giacomarra, Mehran Hosseini, Nicola Paoletti, Francesca Cairoli
Robust Finite-Memory Policy Gradients for Hidden-Model POMDPs
Maris F. L. Galesloot, Roman Andriushchenko, Milan Ceska, Sebastian Junges, Nils Jansen
Optimistically Optimistic Exploration for Provably Efficient Infinite-Horizon Reinforcement and Imitation Learning
Antoine Moulin, Gergely Neu, Luca Viano
Towards Generalizing Temporal Action Segmentation to Unseen Views
Emad Bahrami, Olga Zatsarynna, Gianpiero Francesca, Juergen Gall
Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders
Rogelio A Mancisidor, Robert Jenssen, Shujian Yu, Michael Kampffmeyer
CausalRivers - Scaling up benchmarking of causal discovery for real-world time-series
Gideon Stein, Maha Shadaydeh, Jan Blunk, Niklas Penzel, Joachim Denzler
Of Dice and Games: A Theory of Generalized Boosting
Marco Bressan, Nataly Brukhim, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen
Hyper-Transforming Latent Diffusion Models
Ignacio Peis, Batuhan Koyuncu, Isabel Valera and Jes Frellsen
Graph-Guided Textual Explanation Generation Framework
Shuzhou Yuan, Jingyi Sun, Ran Zhang, Michael Färber, Steffen Eger, Pepa Atanasova, Isabelle Augenstein
Not All LLM-Generated Data Are Equal: Rethinking Data Weighting in Text Classification
Hsun-Yu Kuo, Yin-Hsiang Liao, Yu-Chieh Chao, Wei-Yun Ma, Pu-Jen Cheng
VITAL: More Understandable Feature Visualization through Distribution Alignment and Relevant Information Flow
Ada Görgün, Bernt Schiele, Jonas Fischer
Graph Inverse Style Transfer for Counterfactual Explainability
Bardh Prenkaj, Efstratios Zaradoukas, Gjergji Kasneci
A Bias-Variance Decomposition for Ensembles over Multiple Synthetic Datasets
Ossi Räisä, Antti Honkela
Subgroups Matter for Robust Bias Mitigation
Anissa Alloula, Charles Jones, Ben Glocker, Bartłomiej W. Papiez˙
Can Community Notes Replace Professional Fact-Checkers?
Nadav Borenstein, Greta Warren, Desmond Elliott, Isabelle Augenstein
MANTA: Diffusion Mamba for Efficient and Effective Stochastic Long-Term Dense Anticipation
Olga Zatsarynna, Emad Bahrami, Yazan Abu Farha, Gianpiero Francesca, Juergen Gal
Consistent performance of large language models in rare disease diagnosis across ten languages and 4917 cases
Leonardo Chimirri, J. Harry Caufield, Yasemin Bridges, Nicolas Matentzoglu, Michael Gargano, Mario Cazalla, Shihan Chen, Daniel Danis, Alexander J.M. Dingemans, Klara Gehle, Petra Gehle, Adam S.L. Graefe, Weihong Gu, Markus S. Ladewig, Pablo Lapunzina, Julián Nevado, Enock Niyonkuru, Soichi Ogishima, Dominik Seelow, Jair A. Tenorio Castaño, Marek Turnovec, Bert B.A. de Vries, Kai Wang, Kyran Wissink, Zafer Yüksel, Gabriele Zucca, Melissa A. Haendel, Christopher J. Mungall, Justin Reese, Peter N. Robinson
Truthful Elicitation of Imprecise Forecasts
Anurag Singh, Siu Lun Chau, Krikamol Muandet
Convergence Analysis of Policy Gradient Methods with Dynamic Stochasticity
Alessandro Montenegro, Marco Mussi, Matteo Papini, Alberto Maria Metelli
GRaMPa: Subword Regularisation by Sampling Biased Uniformly Random Tokenisations from a Vocabulary-constrained Path-counting Markov Model
Thomas Bauwens, David Kaczér, Miryam de Lhoneux
Self-Critique and Refinement for Faithful Natural Language Explanations
Yingming Wang, Pepa Atanasova
On the Generalizability of "Competition of Mechanisms: Tracing How Language Models Handle Facts and Counterfactuals"
Asen Dotsinski, Udit Thakur, Marko Ivanov, Mohammad Hafeez Khan, Maria Heuss
Learning Graph Node Embeddings by Smooth Pair Samp
Konstantin Kutzkov
Bayes without Underfitting: Fully Correlated Deep Learning Posteriors via Alternating Projections
Marco Miani, Hrittik Roy, Søren Hauberg
BPE Stays on SCRIPT: Structured Encoding for Robust Multilingual Pretokenization
Sander Land, Catherine Arnett
Fast and Effective GNN Training through Sequences of Random Path Graphs
Francesco Bonchi, Claudio Gentile, Francesco Paolo Nerini, André Panisson, Fabio Vitale
Are Ensembles Getting Better all the Time?
Pierre-Alexandre Mattei, Damien Garreau
4DSegStreamer: Streaming 4D Panoptic Segmentation via Dual Threads Track
Ling Liu, Jun Tian, Li Yi
Amharic News Topic Classification: Dataset and Transformer-Based Model Benchmarks
Dagnachew Mekonnen Marilign and Eyob Nigussie Alemu
Skeleton Motion Words for Unsupervised Skeleton-Based Temporal Action Segmentation
Uzay Goekay, Federico Spurio, Dominik Bach, Jürgen Gall
A Fine-grained Characterization of PAC Learnability
Marco Bressan, Nataly Brukhim, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen
A foundation model to predict and capture human cognition
Marcel Binz, Elif Akata, Matthias Bethge, Franziska Brändle, Fred Callaway, Julian Coda-Forno, Peter Dayan, Can Demircan, Maria K. Eckstein, Noémi Éltető, Thomas L. Griffiths, Susanne Haridi, Akshay K. Jagadish, Li Ji-An, Alexander Kipnis, Sreejan Kumar, Tobias Ludwig, Marvin Mathony, Marcelo Mattar, Alireza Modirshanechi, Surabhi S. Nath, Joshua C. Peterson, Milena Rmus, Evan M. Russek, Tankred Saanum, Johannes A. Schubert, Luca M. Schulze Buschoff, Nishad Singhi, Xin Sui, Mirko Thalmann, Fabian J. Theis, Vuong Truong, Vishaal Udandarao, Konstantinos Voudouris, Robert Wilson, Kristin Witte, Shuchen Wu, Dirk U. Wulff, Huadong Xiong & Eric Schulz
Fleet of Agents: Coordinated Problem Solving with Large Language Models
Lars Henning Klein, Nearchos Potamitis, Roland Aydin, Robert West, Caglar Gulcehre, Akhil Arora
Cache Saver: A Modular Framework for Efficient, Affordable, and Reproducible LLM Inference
Nearchos Potamitis, Lars Henning Klein, Bardia Mohammadi, Chongyang Xu, Attreyee Mukherjee, Niket Tandon, Laurent Bindschaedler, Akhil Arora
What Changed? Detecting and Evaluating Instruction-Guided Image Edits with Multimodal Large Language Models
Lorenzo Baraldi, Davide Bucciarelli, Federico Betti, Marcella Cornia, Lorenzo Baraldi, Nicu Sebe, Rita Cucchiara
SIKeD: Self-guided Iterative Knowledge Distillation for Mathematical Reasoning
Shivam Adarsh, Kumar Shridhar, Caglar Gulcehre, Nicholas Monath, Mrinmaya Sachan
Inverse decision-making using neural amortized Bayesian actors
Dominik Straub, Tobias Fabian Niehues, Jan Peters, Constantin Rothkopf
Tiling artifacts and trade-offs of feature normalization in the segmentation of large biological image
Elena Buglakova, Anwai Archit, Edoardo D'Imprima, Julia Mahamid, Constantin Pape, Anna Kreshuk
Kinetic Langevin Diffusion for Crystalline Materials Generation
François Cornet, Federico Bergamin, Arghya Bhowmik, Juan Maria Garcia Lastra, Jes Frellsen, Mikkel N. Schmidt
Learning Interpretable Hierarchical Dynamical Systems Models from Time Series Data
Manuel Brenner, Elias Weber, Georgia Koppe, Daniel Durstewitz
Characterizing Vision Backbones for Dense Prediction with Dense Attentive Probing
Timo Lüddecke, Alexander Ecker
Table Foundation Models: on knowledge pre-training for tabular learning
Myung Jun Kim, Félix Lefebvre, Gaëtan Brison, Alexandre Perez-Lebel, Gaël Varoquaux
AI Contextual Framework: A Zoning Approach to Ethical AI Deployment
Yao Xie
Bi-Mamba: Towards Accurate 1-Bit State Space Models
Shengkun Tang, Liqun Ma, Haonan Li, Mingjie Sun, Zhiqiang Shen
MosaicDiff: Training-free Structural Pruning for Diffusion Model Acceleration Reflecting Pretraining Dynamics
Bowei Guo, Shengkun Tang, Cong Zeng, Zhiqiang Shen
Hierarchical Vector Quantization for Unsupervised Action Segmentation
Federico Spurio, Emad Bahrami, Gianpiero Francesca, Juergen Gall
Large Language Models Meet Knowledge Graphs for Question Answering: Synthesis and Opportunities
Chuangtao Ma, Yongrui Chen, Tianxing Wu, Arijit Khan, Haofen Wang
PABBO: Preferential Amortized Black-Box Optimization
Xinyu Zhang, Daolang Huang, Samuel Kaski, Julien Martinelli
Uncovering Anomalous Events for Marine Environmental Monitoring via Visual Anomaly Detection
Laura Weihl, Stefan H. Bengtson, Nejc Novak, Malte Pedersen
Epistemic Uncertainty in Conformal Scores: A Unified Approach
Luben M. C. Cabezas, Vagner S. Santos, Thiago R. Ramos, Rafael Izbicki
TARS: Traffic-Aware Radar Scene Flow Estimation
Jialong Wu, Marco Braun, Dominic Spata, Matrhias Rottmann
Detecting Systematic Weaknesses in Vision Models along Predefined Human-Understandable Dimensions
Sujan Sai Gannamaneni, Rohil Prakash Rao, Michael Mock, Maram Akila, Stefan Wrobel
Causal Estimation of Tokenisation Bias
Pietro Lesci, Clara Meister, Thomas Hofmann, Andreas Vlachos, Tiago Pimentel
Detecting Systematic Weaknesses in Vision Models along Predefined Human-Understandable Dimensions
Sujan Sai Gannamaneni , Rohil Prakash Rao, Michael Mock, Maram Akila, Stefan Wrobel