NeurIPS 2025PastOther
Women in Machine Learning Workshop @ NeurIPS 2025
WiML @ NeurIPS 2025
- Submission deadline
- Sep 8, 2025, 23:59 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (259)
Fetched from OpenReview (v2) on 2026-06-10.
$Addressing Racial Bias in AI-Driven Photo Restoration: Enhancing Fidelity for African Facial Features$
A Hybrid AI Framework for Automating High-Stakes Procurement Workflows
A Multimodal Retrieval-Augmented Generation System for Banking Knowledge Access
A Reinforcement Learning Approach for Personalized Automated Anesthesia Control
A robust parameterized enhanced shift-splitting preconditioner for three-by-three block saddle point problems
Accent-Aware Text-to-Speech for Nigerian English: Building Inclusive Voice AI from Community-Curated Data
Addressing Data Scarcity in Women’s Health with Generative Autoencoders
Addressing Domain Shift in Low-Resource Neuroimaging: Glioma Segmentation for Sub-Saharan MRI
Advancing Equitable AI: Evaluating Cultural Expressiveness in LLMs for Latin American Contexts
Adversarial Priors Unleashed with Soft Actor Critic
Agentic Multilingual NLP for Conflict Forecasting from Open-Source Text Streams
AgentX: Automating AI Agent Creation with No-Code, Prompt-Driven Orchestration
AI-Driven Accident Detection and Emergency Response for Low-Resource Settings
AI-Powered Agritourism Chatbot: A Domain-Adapted RAG Chatbot with Transformer NLU for Rural Business Decision Support
AInstein: Can AI Rediscover Scientific Concepts from First Principles?
Aligned Machine
Aligning Agent Policies with Preferences: Human-Centered Interpretable Reinforcement Learning
An Explainable Machine Learning Framework for K–12 Artificial Intelligence Education
Analysing and Classifying Legal Texts on Mexican Cases of Domestic Violence: A Natural Language Processing and CNN-Based Approach
AnnotateThis: Training research assistants to code subjective concepts with LLMs - a case study with climate change pessimism
Artificial Mental Modeling by Leveraging Prescriptive Components in Large Language Models (LLMs)
Ask Me Again Differently: GRAS for Measuring Bias in Vision Language Models on Gender, Race, Age, and Skin Tone
Audio-Visual Open-Vocabulary Egocentric Spatio-Temporal Action Localization with NeRFs
Auto-Prompt-Tuner: A Framework for Meta-LLM driven Prompt Optimization
Automated Triage Classification in Emergency Services Using Spanish Clinical Notes: A Comparative Analysis between ALBERT and Classical Machine Learning Approaches
Batch-Adaptive Annotations for Causal Inference with Complex-Embedded Outcomes
BEDTIME: A Unified Benchmark for Automatically Describing Time Series
Beyond Data Scarcity: Quality Barriers to Trustworthy AI in Low-Resource Medical Imaging
Beyond Detection: Predicting Code-Switch Points in Multilingual Conversations
Beyond I-Con: A Roadmap for Representation Learning Loss Discovery
BiasEdit: Debiasing Stereotyped Language Models via Model Editing
Biologically Refined Imputation via Diffusion for Gene Expression
Bootstrapping-Based Regularisation for Stable Deep Learning Clinical Prediction Models
Building Text and Speech Benchmark Datasets and Models for Low-Resourced East African Languages: Experiences and Lessons
Calibration-Free Passenger Re-ID in Mixed-Modality, Crowded Buses in East Africa
Can AI-powered urban green space monitoring help African cities build climate resilience while addressing environmental inequities
Can Text-to-Speech Systems enable Inclusive Computer-Based Testing? An Evaluation of Yoruba TTS for Visually Impaired Learners
Can We Estimate The Entropy Of Arbitrary Distributions Known Up To A Normalization Constant? A Tale of Stein Variational Gradient Descent Scalability
Can We Predict Alignment Before Models Finish Thinking? Towards Monitoring Misaligned Reasoning Models
CardioPredictor: An Intelligent IoT-Based Risk Prediction Model for Cardiovascular Disease in Low Resourced Environments
Causal Discovery over High-Dimensional Structured Hypothesis Spaces with Causal Graph Partitioning
Causal Investigations of Compound AI System Behaviors: Applications in Synthetic Audio Detection and Air Combat Training Scenario Generation
Causal Strengths and Leaky Beliefs: Interpreting LLM Reasoning via Noisy-OR Causal Bayes Nets
Causal Survival Analysis via Neural Mediation with Counterfactual Risk Estimation
CAVE: Detecting and Explaining Commonsense Anomalies in Visual Environments
CGR-SMILES: A Compact and Universal Sequence Representation for Chemical Reaction Modeling
Climate-Driven Malaria Prediction in Southwest Nigeria: Early Results from a Weighted Deep Learning Ensemble Framework
Clinically Grounded Agent-based Report Evaluation: An Interpretable Metric for Radiology Report Generation
Cognitive Decision Intelligence Framework for Explainable AI Systems
Cognitive Machine Learning for Reducing Survey Fatigue in Clinical Trials
Comparative Analysis of Machine Learning Models for Climate Change Sentiment Classification: A Multi-Method Evaluation Study
Computer-assisted cyclist road safety warning system
Conditional Adversarial Random Forest for Synthetic Electronic Health Record Generation
Conformal Prediction for Time-series Forecasting with Change Points
Context-Aware Neural Machine Translation of English Numerical Expressions to Yorùbá: A Fine-Tuning Approach for Financial and General Domains
Continual Neural Topic Model
Continual world model with counterfactual simulated interactions
Contrastive Representations for Temporal Reasoning
Conv-GRU Temporal Refiner for Prandial Recommendations in Type 1 Diabetes
Correlated Privacy Mechanisms for Differentially Private Distributed Mean Estimation
Cross-Subject and Cross-Montage EEG transfer learning with Individual Tangent Space Alignment
CubicVLA: Efficient Robot Action Representation via Cubic Trajectory Parameterization
Data Driven AI: Federated Explainable AI for Privacy-Preserving Lung and Colon Cancer Medical Image Diagnosis
Data-Driven Detection of Leaking Valves in Air Handling Units
Deep Learning for Urban Planning and Location-Based Services
Deep Models Under Domain Shift: A Sketch-Based Study
Development of a model for customer reviews and feedback on E-commerce website
Dialect-Aware Neural Models for Low-Resource African Languages: A Case Study on Igbo
Differential Gated Self-Attention
Discovering neo-Hebbian plasticity rules for reward-driven training of RNNs
Distributed Specialization: How Transformers Process Rare Tokens Through Parameter Differentiation
Do Biased Models Have Biased Thoughts?
Do Machines Think Emotionally? A Cognitive Appraisal Analysis of Large Language Models
DP-MicroAdam: Private and Frugal Algorithm for Training and Fine-tuning
Dream Diary: Case Study on Diffusion LLM’s Arithmetic Behavior
Dynamic 3D MRI Reconstruction from Single-Spoke via Motion-Compensated Neural Representation
Efficient Data Selection for Split Neural Networks
Efficient Spam Detection with Sentence-BERT using Adaptive Uncertainty-Diversity Ranking Coresets
Electroencephalogram Interpretable Signal Processing for Anesthesia Predictive Monitoring with Knowledge Distillation
Embedding Emotions: Measuring What Matters in Flemish Daily Stories
Embodied Relational Intelligence: A Feminist-Informed Framework for Inclusive Multimodal Agents
Empirical Evidence of the Hidden Costs of Overparameterization: Prediction Instability in Statistical & Machine Learning Models
Ensemble Deep Learning for Forecasting Lassa Fever Outbreaks in Nigeria: Integrating Incidence and Weather Data for Early Warning
Evaluating AI Agent Persuasion of Safety Monitors
Evaluating and Enhancing Large Language Models in Generating UML Class Diagram for Good Code Design
Evaluating the Causal Effect of Chain-of-Thought on Groundedness in Tool-Use Agents via Counterfactual Mutations
Exact Learning Dynamics of Bottlenecked and Wide Deep Linear Networks
Explainable Multimodal Machine Learning for ESG Rating Prediction
Explaining and Predicting Fine-Tuning in Large Models via Linearization
Factorization Machine-Enhanced Crossformer for Multivariate Time Series Event Detection in Epidemic
FairFusion: Distributionally Robust Fair-Multimodal Learning for College Admissions
Fairness-Aware Resource Optimization in Federated Learning
FairSHAP: Preprocessing for Fairness Through Attribution-Based Data Augmentation
FairSimCLR: A Fairness-Aware Contrastive Learning Framework for Demographic Bias Mitigation in Dermatology Imaging
Federated Learning and Class Imbalances - А Study on Breast Lesion Segmentation in DCE-MRI
FEEL: Modeling Physiological Diversity for Robust Emotion Recognition
Finding Memo: The Hidden Influence of Memorization in Large Language Models’ Performance – A Critical Analysis of Benchmark Evaluation
Finding Reaction Mechanism Pathways with Deep Reinforcement Learning and Heuristic Search
Fine-Tuning Large Language Models on EHR Data for Early Endometriosis Diagnosis in Adolescents
Fixed Aggregation Features Can Rival GNNs
Flatness-Aware Regularization for Robust Generalization in Deep Neural Networks
Foundation model based prostate cancer segmentation on whole mount digitized H&E radical prostatectomy section
Foundation Models on a Budget: Approximating Blocks in Large Vision Models
From Algorithm to Alliance: A Blueprint for Responsible and Explainable AI in Mental Health Screening
From Mechanisms to Models: Multi-Modal Machine Learning for Kinetically Constrained Genome-Scale Metabolic Models
From National Goals to Industry Action: AI-Driven Forecasting of India’s Carbon Emissions
From Prediction to Causation: Active Experiment Design for Robust Discovery
From Sensing to Reasoning: Multi-Modal Large Language Models Guiding Robotic Intelligence in Autonomous Labs
G-Loss: Graph-Guided Fine-Tuning of Language Models
GAITGen: Disentangled Motion-Pathology Impaired Gait Generative Model
Generating and Adapting Audio Description with Vision–Language Models for Blind and Low-Vision Users
Generation of Multiple Types of Driving Scenarios with a Unified Generative Model for Autonomous Driving
Graph Dreamer: Temporal Graph World Models for Sample-Efficient and Generalisable Reinforcement Learning
Graph-Based Multimodal Learning for Early Sepsis Prediction in Resource-Constrained Clinical Settings
Greenwashing Detection with Causal Explanation: A Novel Multi-layered Approach
Gricean Maxims in LLM Development
HIFoD: Rethinking Indicators of Compromise in Heterogeneous Image Forgery Detection, Classification and Localization
How to Give Health-Behavioural Recommendations Using Meta-Reinforcement Learning to Reduce Cancer Risk
How Well Do LLMs Unlearn Facts? - A Knowledge Graph Perspective
Hybrid SNN-Transformer Networks for Event-Based, Energy-Efficient Large-Scale Learning
Identifying Key Predictors of Food Security in Mexico using Machine Learning Models
iLLuMinaTE: An LLM-XAI Framework Leveraging Social Science Explanation Theories Towards Actionable Student Performance Feedback
IMAiGen: A Cross-Modal Image-to-Music Generation with a Non-Deep Learning Core
Improving BGE-M3 Multilingual Dense Embeddings for Nigerian Low Resource Languages
Improving Generation Quality of Long-Tailed Diffusion via Disentangled Latent Representations
Improving Vision-LLMs with Human Cognitive Signals
Imputation Free Deep Survival Prediction using Conditional Variational Autoencoders
Inclusive Education through AI: A Framework for Swahili - English Audio Access in Tanzanian Libraries
Individually Fair Clustering with Outliers
Instruction-based Time Series Editing
Integrating Thermal Imaging and Deep Learning for Real-Time Strength Estimation in 3D Concrete Printing
Intermediate Representations for Improved Code Translation with LLMs
Interpretable KPI Analytics for Resource-Efficient AI-RAN Intelligence
Interpreting GFlowNets for Drug Discovery: Extracting Actionable Insights for Medicinal Chemistry
Intrinsic Meets Extrinsic Fairness: Assessing the Downstream Impact of Bias Mitigation in Large Language Models
Invariant Graph Representations Learning via Redundant Information
Investigating the Hate–Credibility Nexus Across Datasets and Content Formats
Kernel Distributionally Robust Recourse Action
Law-like Principles for Artificial Intelligence: Better Construction and Interpretation of Rules
Layer of Truth: How Much Poison Is Enough? Illusory-Truth Effects in Continual Pre-training
Learning Robust Multimodal Control for Resource-Constrained Platforms
Learning to Handle Constraints in Routing Problems via a Construct-and-Refine Framework
Learning Visual Concepts via Vision Language Programs
LEMON: A Unified and Scalable 3D Multimodal Model for Universal Spatial Understanding
Leveraging Machine Learning and Large Language Models for Enhanced Occupational Stress Detection
Lightweight Continual Learning for Cervical Cancer Diagnosis with Synthetic Augmentation and Explainable AI
Lightweight Vision Transformers for Mammography: Balancing Accuracy and Efficiency with Methodological Rigor
LISTEN: Leveraging Open-Weight LLMs for Real-Time Monitoring of Health Misinformation on Social Media
LLM-based Code Evaluation for Fairness
LLM-Enabled Semantic Caching for Affordable Web Access
LLM-Powered Graph Reasoning for Knowledge Discovery
Low-Resource Rhythm Learning: Machine Learning Approaches to Structured Classical Beats
LVT: Large-Scale Scene Reconstruction via Local View Transformers
Machine learning discovery of regional and social disparities in electric vehicle charging reliability
Machine Learning Models for Predicting Suicidal Ideation in University Students
Mental Accounts for Actions: EWA-Inspired Attention in Decision Transformers
Milk Prediction Using Conformation Traits as Privileged Information
Mind the Gap: LLM Actions vs. Human Social Understanding in Moral Dilemmas
Mitigating Knowledge Entropy: A Multi-Agent Framework with Decoupled Reranking and Governance-by-Design
Modeling Dynamical Systems of Energetic Materials: Physics-Aware Convolutional Neural Networks in a Latent Space (LatentPARC)
Multi-Architecture Temporal Models for Early Symptom-Based Disease Prediction
Multimodal Asymmetric Convolutional Autoencoder for Vehicle Small Damage Detection
Multimodal Neuroimaging Fusion for Alzheimer's Disease: An Image Colorization Approach With Mobile Vision Transformer.
Multimodality extension to Universal Multilingual BPE Text Tokenizer
Narrative2Music: Generating Emotion-Aligned Music for Sentences
Neither Valid Nor Reliable? Investigating the Use of LLMs as Judges
Netlist‑Level Design and Evaluation of Stealthy Hardware Trojans
Network Inversion for Uncertainty-Aware Out-of-Distribution Detection
Neuroscience-Inspired Encoding and Learning: A Path to Robust Representation Learning
No-Regret Contextual Bandits for Cost-Sensitive Decision-Making
Online Anti-sexist Speech: Identifying Resistance to Gender Bias in Political Discourse
Online two-sided markets: many buyers enhance learning
OpenHype: Hyperbolic Embeddings for Hierarchical Open-Vocabulary Radiance Fields
Optimizing Noise Distributions for Differential Privacy
ORANGE: A Machine Learning Approach for Modeling Tissue-Specific Aging from Transcriptomic Data
Overcoming Data Scarcity in Depth-Based Human Action Recognition via Zero-Shot Depth Estimation
ÒWE-YOR: Leveraging Transformer Based Models for Yoruba Proverb Classification
Perceptual Regularization from Human Visual System Models Improves Adversarial Robustness
Persona-Infused Dynamic Collaborative Decoding
Personalized AI-driven Teacher’s Comment Model for Nigerian Secondary School Students’ Result
Personalizing Foundation Models for Cancer Imaging: A Study on Lymph Node Segmentation with SAM2 and MedSAM2
Physics-Informed Graph Diffusion for Climate Downscaling
Pidgin Science Voices: A Community-Driven Speech Corpus for Inclusive STEM Education
Plot'n Polish: Zero-shot Story Visualization and Disentangled Editing with Text-to-Image Diffusion Models
Political Bias in Neural Retrieval: Model-Agnostic Measurement on Canadian Social Media
Poly-Autoregressive Prediction for Modeling Interactions
Preference-Driven Multi-Objective Combinatorial Optimization with Conditional Computation
PRIME Guardrails: A General, Low‑Latency Safety Framework for Generative AI
PRISM-FL: Privacy-preserving Image Synthesis Mechanism for Federated Learning
Prompt Engineering for Imposter Scam Detection by Resourced-Constrained Organizations
Prompt Engineering for Spanish Sexism Detection
QuantumConoMix: Benchmarking Shallow VQCs for Resource-Constrained Peptide Classification
RADAR: A Reasoning-Guided Attribution Framework for Explainable Visual Data Analysis
Reasoning with Preference Constraints: A Benchmark for Language Models in Many-to-One Matching Markets
Recurrent Hamiltonian Echo Learning Enables Biologically Plausible Training of Recurrent Neural Networks
Reduced-Dimensional Anomaly-Aware Generalization for Deepfake Image Detection
REPLAY-BASED CONTINUAL FEDERATED LEARNING USING INCREMENTALLY AGGREGATED GRADIENTS
RetinaSynth: Diffusion‑Based Synthetic Imaging
REVEAL – Reasoning and Evaluation of Visual Evidence through Aligned Language
Revisiting Replay and Gradient Alignment For Continual Pretraining of Large Language Models
Reward the Reward Designer: Making Reinforcement Learning Useful for Clinical Decision Making
Risk-Aware Deep Reinforcement Learning with Hierarchical Adaptation for XAU/USD Trading
Robust phoneme classification under adverse conditions using MEG data
Robustness of Vision-Based Human Activity Recognition under Naturalistic Distribution Shifts
Safe Reinforcement Learning Framework Under a Linear Programming Formulation
Say It Another Way: Auditing LLMs with a User-Grounded Automated Paraphrasing Framework
Scaling Up Liquid-Resistance Liquid-Capacitance Networks for Efficient Sequence Modeling
Score-Based Denoising Diffusion Models for Photon-Starved Image Restoration Problems
SCRIBE: A Fine-Tuned Transformer Embedding Model for Evaluating Medical School Personal Statements
See No Evil: Adversarial Attacks on Referring Multi-Object Tracking Systems
SENSE: SENsing Similarity SEeing Structure
Separating Control and Data Planes for Safe Agentic Browsing
SGEAG: Semantic-guided emotional-aware gesture generation from audio
SicklePrenatal: Biometric-Guided Deep Learning For Early Sickle Cell Risk Detection From Fetal Ultrasound
SignFormer-GCN: Continuous Sign Language Translation using Spatio-Temporal Graph Convolutional Networks
SiniticMTError: A Machine Translation Dataset with Error Annotations for Sinitic Languages
Skill-Aligned Fairness in Multi-Agent Learning for Collaboration in Healthcare
SpatialThinker: Reinforcing 3D Reasoning in Multimodal LLMs via Spatial Rewards
Spatio-Temporal Dual Attention with Cross-Sensor Attention for Enhanced IMU-based Human Activity Recognition
Speak, Start, See, Sense: How NLP, Robotics, and Computer Vision can Improve Automated Experimentation in Self-driving Labs
Spectral–Topology-Aware KG-MARL for 5G V2V Sidelink
Stable and Uncertainty-Aware Local Post-hoc Explanations Using Active Learning
Strategic Feature Selection
Stress-Testing Byzantine Defenses under Data Heterogeneity
Subclass-Aware Inclusive Classifier via Repulsive Hidden Strata
Summarizing Diagnoses from Clinical Notes: Towards a Benchmark and Systematic Evaluation
Tag2M- A Task-Agnostic Knowledge Distillation Framework for Distilling Gnn to MLP
Talking with Oompa Loompas: A Novel Framework for Evaluating Linguistic Acquisition of LLM Agents
Targeted GAN Unlearning via Mode Suppression under Memory Budgets
TARnISHED: Forecasting Emergency Department visits using Wastewater with Multivariate Gaussian Random Walks
Temporal Kolmogorov-Arnold Networks for Robust Multi-Horizon PM$_ {2.5}$ Forecasting
The Exposome Interpreter as a Multi-modal Framework for Autoimmune Trigger Identification
The Representations of Deep Neural Networks Trained on Dihedral Group Multiplication
The Social Laboratory: A Psychometric Framework for Multi-Agent LLM Evaluation
TimeSeriesExamAgent: Creating Time Series Reasoning Benchmarks at Scale
TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents
Tonative: Community-Driven Extension of African Datasets Through Human-AI Collaboration
Toward Scalable and Physically-Grounded Learning Frameworks: Neural Finite Volume Methods for Solving Hyperbolic PDEs
Towards Democratizing LLMs: Investigating Multilingual Mixture-of-Experts Models
Towards Inclusive NLP: Benchmarking and Mitigating Bias in Named Entity Recognition for African Languages and Entities.
Towards Test-Time Adaptation for Neural Surrogates
Towards Understanding Multimodal Fine-Tuning: A Case Study into Spatial Features
Towards Well-Calibrated AutoML: A Theoretical Analysis based on Ensemble Diversity
Trustworthiness of LLMs in Grading and Demographic Fairness in Medical RAG
Two Steps from Hell: Compositionality on Chemical LMs
Uncertainty-driven Multimedia Source File Matching
Understanding Adversarial Weakness in Vision-Language Models
Understanding LoRA Update Complexity Through Stable Rank
Unifying Mechanistic Interpretations of Neural Networks Trained on Modular Addition
Unmasking COVID-19 Vulnerability in Nigeria: Mapping Risks Beyond Urban Hotspots
Unveiling Signal Property Usage in Transformers for Time Series Classification
V-Trans4Style: Visual Transition Recommendation for Video Production Style Adaptation
VesselGPT: Autoregressive Modeling of Vascular Geometry
ViAD : A Novel Strategic Robotic Navigation Methodology
Voices of Fashion: 150-Hour Yoruba Speech Corpus for Egba Adire and Color Advisory Systems
When “Government-Approved” LLMs Silence Citizen Voices: Evidence of Systematic Demographic Bias in Federal Comment Analysis
When Endangered Voices Speak: Building the First Ehugbo Dialect Audio Dataset Through Grassroots Collaboration
Which View Works Best? Evaluating Representations for Scientific Document Retrieval
Who is In Charge? Dissecting Role Conflicts in LLM Instruction Following