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Workshop Sat, Dec 6, 2025 • 8:00 AM – 5:00 PM PST

Structured Probabilistic Inference and Generative Modeling

Yuanqi Du ⋅ Dinghuai Zhang ⋅ Jiajun He ⋅ Heli Ben-Hamu ⋅ Francisco Vargas ⋅ Yunan Yang ⋅ Animashree Anandkumar ⋅ Arnaud Doucet ⋅ José Miguel Hernández-Lobato
Project Page [ OpenReview] 

Video

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Schedule

Timezone: America/Los_Angeles
8:30 AM
Opening remark
10:10 AM
Coffee break
2:30 PM
Coffee break
3:40 PM
Closing remark
Ambient Diffusion Omni
Giannis Daras ⋅ Adrian Rodriguez-Munoz ⋅ Adam Klivans ⋅ Antonio Torralba ⋅ Constantinos Daskalakis
SLayR: Scene Layout Generation with Rectified Flow
Cameron Braunstein ⋅ Hevra Petekkaya ⋅ Jan Eric Lenssen ⋅ Mariya Toneva ⋅ Eddy Ilg
Enhancing Diffusion Model Guidance through Calibration and Regularization
Seyed Alireza Javid ⋅ Amirhossein Bagheri ⋅ Nuria Prelcic
DDS-E-Sim: A Transformer-based Probabilistic Generative Framework for Simulating Error-Prone DNA Sequences for DNA Data Storage
Mst. Naznin ⋅ Swarup Sidhartho Mondol ⋅ Adnan Faruq ⋅ Debashmita Saha ⋅ Ahmed Rumi ⋅ A. B. M. Alim Al Islam
ISUM: Inverse Problem Solver via Unbalanced Optimal Transport Map
Donggyu Lee ⋅ Taekyung Lee ⋅ Jaewoong Choi ⋅ Myungjoo Kang
Divergence Minimization Preference Optimization for Diffusion Model Alignment
Binxu Li ⋅ Minkai Xu ⋅ Meihua Dang ⋅ Stefano Ermon
moPPIt-v3: Motif-Specific Peptides Generated via Multi-Objective-Guided Discrete Flow Matching
Tong Chen ⋅ Zachary Quinn ⋅ Yinuo Zhang ⋅ Pranam Chatterjee
Scalable Bayesian Monte Carlo: fast uncertainty estimation beyond deep ensembles
Xinzhu Liang ⋅ Joseph Lukens ⋅ Brian Kirby ⋅ Thomas Searles ⋅ Sanjaya Lohani ⋅ Xin Qiu ⋅ Kody Law
STED and Consistency Scoring: A Framework for Evaluating LLM Structured Output Reliability
Guanghui Wang ⋅ Jinze Yu ⋅ Xing Zhang ⋅ Dayuan jiang ⋅ Yin Song ⋅ Peiyang He ⋅ Xuefeng Liu ⋅ Tomal Deb
Shaping Inductive Bias in Diffusion Models through Frequency-Based Noise Control
Thomas Jiralerspong ⋅ Berton Earnshaw ⋅ Jason Hartford ⋅ Yoshua Bengio ⋅ Luca Scimeca
An Information-Theoretic Discrete Poisson Diffusion Framework
Sagnik Bhattacharya ⋅ Abhiram Gorle ⋅ Ahsan Bilal ⋅ Amit Kumar Singh Yadav ⋅ Connor Ding ⋅ Tsachy Weissman
Information-Guided Diffusion Sampling for Dataset Distillation
Linfeng Ye ⋅ Shayan Mohajer Hamidi ⋅ Guang Li ⋅ Takahiro Ogawa ⋅ Miki Haseyama ⋅ Konstantinos N Plataniotis
BP-Seg: A graphical model approach to unsupervised and non-contiguous text segmentation using belief propagation
Fengyi Li ⋅ Kayhan Behdin ⋅ Xiaofeng Wang ⋅ Ercan Yildiz ⋅ Natesh Pillai ⋅ Zhipeng Wang
Value Matching: Scalable and Gradient-Free Reward-Guided Flow Adaptation
Cristian Jensen ⋅ Luca Schaufelberger ⋅ Riccardo De Santi ⋅ Kjell Jorner ⋅ Andreas Krause
Diffusion Beats Autoregressive in Data-Constrained Settings
Mihir Prabhudesai ⋅ Mengning Wu ⋅ Amir Zadeh ⋅ Katerina Fragkiadaki ⋅ Deepak Pathak
Generative Actor-Critic
Aoyang Qin ⋅ Wei Wang ⋅ Deqian Kong ⋅ Ying Nian Wu ⋅ Song-Chun Zhu ⋅ Sirui Xie
Probabilistic Variational Contrastive Learning
Minoh Jeong ⋅ Seonho Kim ⋅ Alfred Hero
Inference-time Scaling of Diffusion Models through Classical Search
Xiangcheng Zhang ⋅ Haowei Lin ⋅ Haotian Ye ⋅ James Zou ⋅ Jianzhu Ma ⋅ Yitao Liang ⋅ Yilun Du
MMG: Mutual Information Estimation via the MMSE Gap in Diffusion
Longxuan Yu ⋅ Xing Shi ⋅ Xianghao Kong ⋅ Tong Jia ⋅ Greg Ver Steeg
Can We Estimate The Entropy Of Arbitrary Distributions Known Up To A Normalization Constant?
Safa Messaoud ⋅ Skander Charni ⋅ Elaa Bouazza ⋅ Ali Pourghasemi Fatideh ⋅ Halima Bensmail
GNN-Guided Block Selection in Gibbs MCMC
Benjamin Dayan ⋅ Bhaskar Mishra ⋅ Justin Svegliato ⋅ Stuart J Russell
Entropy-Guided Sampling of Flat Modes in Discrete Spaces
Pinaki Mohanty ⋅ Riddhiman Bhattacharya ⋅ Ruqi Zhang
Adaptive Frontier Exploration on Graphs with Applications to Network-Based Disease Testing
XianJun, Davin Choo ⋅ Yuqi Pan ⋅ Tonghan Wang ⋅ Milind Tambe ⋅ Alastair van Heerden ⋅ Cheryl Johnson
Where the Score Lives: A Wavelet View of Diffusion
Emma Finn ⋅ Binxu Wang ⋅ Andy Keller ⋅ Demba Ba
VarDiU: A Variational Diffusive Upper Bound for One-Step Diffusion Distillation
Leyang Wang ⋅ Mingtian Zhang ⋅ Zijing Ou ⋅ David Barber
Trust Region Constrained Measure Transport in Path Space for Stochastic Optimal Control and Inference
Denis Blessing ⋅ Julius Berner ⋅ Lorenz Richter ⋅ Carles Domingo i Enrich ⋅ Yuanqi Du ⋅ Arash Vahdat ⋅ Gerhard Neumann
Probabilistic Image Generation with LLM Priors via Structured Rectified Flow
Mykola Vysotskyi ⋅ Zahar Kohut ⋅ Anna-Alina Bondarets ⋅ Taras Rumezhak
A Theory of Multi-Agent Generative Flow Networks
Leo Brunswic ⋅ Haozhi Wang ⋅ Shuang Luo ⋅ Jianye Hao ⋅ Amir Rasouli ⋅ Yinchuan Li
Improved Sampling from Masked Diffusion Models with Position Contrastive Guidance
Dhruvesh Patel ⋅ Tahira Naseem ⋅ Gaurav Pandey ⋅ Md Arafat Sultan ⋅ Andrew McCallum ⋅ Ramón Astudillo
Hold That Exit: Near Optimal Early-Exit Inference via Recall
Yuanyuan Yang ⋅ Ruimin Zhang ⋅ Jamie Morgenstern ⋅ Haifeng Xu
Beyond Linear Diffusions: Improved Representations for Rare Conditional Generative Modeling
Kulunu Dharmakeerthi ⋅ Yousef El-Laham ⋅ Henry Wong ⋅ Vamsi Potluru ⋅ Changhong He ⋅ Taosong He
Any-Order Flexible Length Masked Diffusion
Jaeyeon Kim ⋅ Lee Kit ⋅ Carles Domingo i Enrich ⋅ Yilun Du ⋅ Sham Kakade ⋅ Timothy Ngotiaoco ⋅ Sitan Chen ⋅ Michael Albergo
Probabilistic Soundness Guarantees in LLM Reasoning Chains
Weiqiu You ⋅ Anton Xue ⋅ Shreya Havaldar ⋅ Delip Rao ⋅ Helen Jin ⋅ Chris Callison-Burch ⋅ Eric Wong
ImmUQBench: A Benchmark on Uncertainty Quantification of Protein Immunogenicity Prediction
Alif Bin Abdul Qayyum ⋅ Amir Hossein Rahmati ⋅ Xiaoning Qian ⋅ Byung-Jun Yoon
The Unwinnable Arms Race of AI Image Detection
Till Aczel ⋅ Lorenzo Vettor ⋅ Andreas Plesner ⋅ Roger Wattenhofer
Variational Deep Learning via Implicit Regularization
Jonathan Wenger ⋅ Beau Coker ⋅ Juraj Marusic ⋅ John Cunningham
Constrained Molecular Generation via Sequential Flow Model Fine-Tuning
Sven Gutjahr ⋅ Riccardo De Santi ⋅ Luca Schaufelberger ⋅ Kjell Jorner ⋅ Andreas Krause
Accelerating Diffusion Models in Offline RL via Reward-Aware Consistency Trajectory Distillation
Xintong Duan ⋅ Yutong He ⋅ Fahim Tajwar ⋅ Ruslan Salakhutdinov ⋅ Zico Kolter ⋅ Jeff Schneider
Zero-Variance Gradients for Variational Autoencoders
Zilei Shao ⋅ Anji Liu ⋅ Guy Van den Broeck
Token-Level Guided Discrete Diffusion for Membrane Protein Design
Shrey Goel ⋅ Peregrine Schray ⋅ Yinuo Zhang ⋅ Sophia Vincoff ⋅ Huong Kratochvil ⋅ Pranam Chatterjee
Improving Iterative Gaussian Processes via Warm Starting Sequential Posteriors
Alan Dong ⋅ Jihao Andreas Lin ⋅ José Miguel Hernández-Lobato
Graph Random Features for Scalable Gaussian Processes
Matthew Zhang ⋅ Jihao Andreas Lin ⋅ Krzysztof M Choromanski ⋅ Adrian Weller ⋅ Richard Turner ⋅ Isaac Reid
Leveraging Probabilistic Modeling for Robust End-to-End Autonomous Driving across Domains
Rajeev Yasarla ⋅ Shizhong Han ⋅ Hsin-Pai Cheng ⋅ Litian Liu ⋅ Shweta Mahajan ⋅ Apratim Bhattacharyya ⋅ Yunxiao Shi ⋅ Risheek Garrepalli ⋅ Herbert Cai ⋅ Fatih Porikli
Posterior Inference in Latent Space for Scalable Constrained Black-box Optimization
Kiyoung Om ⋅ Kyuil Sim ⋅ Taeyoung Yun ⋅ Hyeongyu Kang ⋅ Jinkyoo Park
Semantic Probabilistic Control of Language Models
Kareem Ahmed ⋅ Catarina Belém ⋅ Padhraic Smyth ⋅ Sameer Singh
Inference and Generating Method for Extremely Sparse Networks
Valentin Kilian ⋅ Benjamin Guedj ⋅ Francois Caron
Temporal Alignment Guidance: On-manifold Sampling in Diffusion Models
Youngrok Park ⋅ Hojung Jung ⋅ Sangmin Bae ⋅ Se-Young Yun
Cross-Lingual Multimodal Retrieval-Augmented Generation for Open Question Answering in Tamil and Yoruba
Kiran Raja ⋅ Mobareji Abejide ⋅ Arya Ram ⋅ Utkarsh Sharma ⋅ Benjamin Liu ⋅ Kevin Zhu
Continuous-Token Diffusion for Speaker-Referenced TTS in Multimodal LLMs
Xinlu He ⋅ Harish Mallidi ⋅ JIA-HONG HUANG ⋅ Ashwin Bellur ⋅ M. Maruf ⋅ Chander Chandak ⋅ Venkatesh Ravichandran ⋅ Swayambhu Ray
Generalization of Diffusion Models Arises from a Regularized Representation Space
Zekai Zhang ⋅ Xiang Li ⋅ Xiao Li ⋅ Molei Tao ⋅ Qing Qu
Entangled Schrödinger Bridge Matching
Sophia Tang ⋅ Yinuo Zhang ⋅ Pranam Chatterjee
Score-informed Neural Operator for Enhancing Ordering-based Causal Discovery
Jiyeon Kang ⋅ Songseong Kim ⋅ Chanhui Lee ⋅ Doyeong Hwang ⋅ Joanie Chung ⋅ Yunkyung Ko ⋅ Sumin Lee ⋅ Sungwoong Kim ⋅ Sungbin Lim
Blind Inverse Problem Solving Made Easy by Text-to-Image Latent Diffusion
Michail Dontas ⋅ Yutong He ⋅ Naoki Murata ⋅ Yuki Mitsufuji ⋅ Zico Kolter ⋅ Ruslan Salakhutdinov
BioBO: Biology-informed Bayesian Optimization for Perturbation Design
Yanke Li ⋅ Tianyu Cui ⋅ Tommaso Mansi ⋅ Mangal Prakash ⋅ Rui Liao
On Fitting Flow Models with Large Sinkhorn Couplings
Alireza Mousavi-Hosseini ⋅ Stephen Zhang ⋅ Michal Klein ⋅ Marco Cuturi
Multimodal Bayesian Network for Robust Assessment of Casualty in Autonomous Triage
Szymon Rusiecki ⋅ Cecilia G Morales ⋅ Kimberly Elenberg ⋅ Leonard Weiss ⋅ Artur Dubrawski
A Connection Between Score Matching and Local Intrinsic Dimension
Eric Yeats ⋅ Aaron Jacobson ⋅ Darryl Hannan ⋅ Yiran Jia ⋅ Tim Doster ⋅ Henry Kvinge ⋅ Scott Mahan
CoVAE: Consistency Training of Variational Autoencoders
Gianluigi Silvestri ⋅ Luca Ambrogioni
Insertion Language Models: Sequence Generation with Arbitrary-Position Insertions
Dhruvesh Patel ⋅ Aishwarya Sahoo ⋅ Avinash Amballa ⋅ Tahira Naseem ⋅ Tim G. J. Rudner ⋅ Andrew McCallum
Robust Multi-task Modeling for Bayesian Optimization via In-Context Learning
Yucen Li ⋅ Samuel Daulton ⋅ Samuel Müller ⋅ Andrew Wilson ⋅ Eytan Bakshy
When Do LLMs Improve Bayesian Optimization? A Systematic Comparison Across Molecular and Protein Design
Mattias Akke ⋅ Soojung Yang ⋅ Jurģis Ruža ⋅ Jinyeop Song ⋅ Elton Pan ⋅ Rafael Gomez-Bombarelli
Failure Prediction Is a Better Performance Proxy for Early-Exit Networks Than Calibration
Piotr Kubaty ⋅ Filip Szatkowski ⋅ Metod Jazbec ⋅ Bartosz Wójcik
Neural Universal Scene Descriptors
Alejandro Escontrela ⋅ Shrinu Kushagra ⋅ Sjoerd van Steenkiste ⋅ Yulia Rubanova ⋅ Aleksander Holynski ⋅ Kelsey Allen ⋅ Kevin Murphy ⋅ Thomas Kipf
Score-based Idempotent Distillation of Diffusion Models
Shehtab Zaman ⋅ Chengyan Liu ⋅ Kenneth Chiu
Improving Generation Quality of Long-Tailed Diffusion via Disentangled Latent Representations
Esther Rodriguez ⋅ Monica Welfert ⋅ Samuel McDowell ⋅ Nathan Stromberg ⋅ Julian Camarena ⋅ Lalitha Sankar
A Probabilistic Approach to Pose Synchronization for Multi-Reference Alignment with applications to wireless communication systems
Rob Romijnders ⋅ Gabriele Cesa ⋅ Christos Louizos ⋅ Kumar Pratik ⋅ Arash Behboodi
IAGA: Identity-Aware Gaussian Approximation for Efficient 3D Molecular Generation
Jingxiang Qu ⋅ Wenhan Gao ⋅ RUICHEN XU ⋅ Yi Liu
Efficient Flow Matching using Latent Variables
Anirban Samaddar ⋅ Yixuan Sun ⋅ Viktor Nilsson ⋅ Sandeep Madireddy
DenseMixer: Improving MoE Post-Training with Precise Router Gradient
Feng Yao ⋅ Junxia Cui ⋅ Ruohan Zhang ⋅ Liyuan Liu ⋅ Shibo Hao ⋅ Li Zhang ⋅ Chengyu Dong ⋅ Shuohang Wang ⋅ yelong shen ⋅ Jianfeng Gao ⋅ Jingbo Shang
State-Space Architectures for Scalable Diffusion-based 3D Molecule Generation
Adrita Das ⋅ Peiran Jiang ⋅ Dantong Zhu ⋅ Barnabas Poczos ⋅ Jose Lugo-Martinez
Entropy Is Not Enough: Uncertainty Quantification for LLMs fails under Aleatoric Uncertainty
Tim Tomov ⋅ Dominik Fuchsgruber ⋅ Tom Wollschläger ⋅ Stephan Günnemann
Selective Underfitting in Diffusion Models
Kiwhan Song ⋅ Jaeyeon Kim ⋅ Sitan Chen ⋅ Yilun Du ⋅ Sham Kakade ⋅ Vincent Sitzmann
Semantic Volume: Quantifying and Detecting both External and Internal Uncertainty in LLMs
Xiaomin Li ⋅ Zhou Yu ⋅ Ziji Zhang ⋅ Yingying Zhuang ⋅ Swair Shah ⋅ Narayanan Sadagopan ⋅ Anurag Beniwal
Myosotis: structured computation for attention like layer
Evgenii Egorov ⋅ Herbert Cai ⋅ Hanno Ackermann ⋅ Markus Nagel
Steering Pretrained Drafters during Speculative Decoding
Frédéric Berdoz ⋅ Peer Rheinboldt ⋅ Roger Wattenhofer
Is Sequence Information All You Need for Bayesian Optimization of Antibodies?
Sebastian Ober ⋅ Calvin McCarter ⋅ Aniruddh Raghu ⋅ Yucen Li ⋅ Alan Amin ⋅ Andrew Wilson ⋅ Hunter Elliott
Value Gradient Guidance for Flow Matching Alignment
Zhen Liu ⋅ Tim Xiao ⋅ Carles Domingo i Enrich ⋅ Weiyang Liu ⋅ Dinghuai Zhang
Rethinking Direct Preference Optimization in Diffusion Models
Junyong Kang ⋅ Seohyun Lim ⋅ Kyungjune Baek ⋅ Hyunjung Shim
3-Model Speculative Decoding
Sanghyun Byun ⋅ Mohanad Odema ⋅ Jung Ick Guack ⋅ Baisub Lee ⋅ Jacob Song ⋅ Woo Seong Chung
Foundations of Top-$k$ Decoding for Language Models
Georgy Noarov ⋅ Soham Mallick ⋅ Tao Wang ⋅ Sunay Joshi ⋅ Yan Sun ⋅ Yangxinyu Xie ⋅ Mengxin Yu ⋅ Edgar Dobriban
Weighted Conditional Flow Matching
Sergio Calvo Ordoñez ⋅ Matthieu Meunier ⋅ Alvaro Cartea ⋅ Christoph Reisinger ⋅ Yarin Gal ⋅ José Miguel Hernández-Lobato
Learning Boltzmann Generators via Constrained Mass Transport
Christopher von Klitzing ⋅ Denis Blessing ⋅ Henrik Schopmans ⋅ Pascal Friederich ⋅ Gerhard Neumann