Dianbo Liu
According to our database1,
Dianbo Liu authored at least 101 papers
between 2017 and 2026.
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Bibliography
2026
Quotient DAGs for Off-Policy Evaluation:Forward-Flow Importance Sampling and Exact Slate Propensities.
CoRR, May, 2026
FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics.
CoRR, May, 2026
JEDI: Joint Embedding Diffusion World Model for Online Model-Based Reinforcement Learning.
CoRR, May, 2026
Absurd World: A Simple Yet Powerful Method to Absurdify the Real-world for Probing LLM Reasoning Capabilities.
CoRR, May, 2026
When Language Overwrites Vision: Over-Alignment and Geometric Debiasing in Vision-Language Models.
CoRR, May, 2026
Resolving the bias-precision paradox with stochastic causal representation learning for personalized medicine.
CoRR, May, 2026
Mitigating Premature Discretization with Progressive Quantization for Robust Vector Tokenization.
CoRR, March, 2026
Early Quantization Shrinks Codebook: A Simple Fix for Diversity-Preserving Tokenization.
CoRR, March, 2026
CoRR, March, 2026
CoRR, February, 2026
Expected Return Causes Outcome-Level Mode Collapse in Reinforcement Learning and How to Fix It with Inverse Probability Scaling.
CoRR, January, 2026
AI-generated data contamination erodes pathological variability and diagnostic reliability.
CoRR, January, 2026
Bridging Mechanistic Interpretability and Prompt Engineering with Gradient Ascent for Interpretable Persona Control.
CoRR, January, 2026
SOLAR : A Self-Optimizing Open-Ended Autonomous Agent for Lifelong Learning and Continual Adaptation.
Proceedings of the 1st Streaming Continual Learning Bridge at AAAI (StreamingCL 2026) co-located with 40th Annual AAAI Conference on Artificial Intelligence (AAAI 2026), 2026
BayesAgent: Bayesian Agentic Reasoning Under Uncertainty via Verbalized Probabilistic Graphical Modeling.
Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026
2025
On the Theoretical Foundation of Sparse Dictionary Learning in Mechanistic Interpretability.
CoRR, December, 2025
Deconstructing Generative Diversity: An Information Bottleneck Analysis of Discrete Latent Generative Models.
CoRR, December, 2025
How does My Model Fail? Automatic Identification and Interpretation of Physical Plausibility Failure Modes with Matryoshka Transcoders.
CoRR, November, 2025
CoRR, November, 2025
CoRR, October, 2025
HypoSpace: Evaluating LLM Creativity as Set-Valued Hypothesis Generators under Underdetermination.
CoRR, October, 2025
FML-bench: A Benchmark for Automatic ML Research Agents Highlighting the Importance of Exploration Breadth.
CoRR, October, 2025
CoRR, September, 2025
Attention Schema-based Attention Control (ASAC): A Cognitive-Inspired Approach for Attention Management in Transformers.
CoRR, September, 2025
CoRR, September, 2025
CoRR, September, 2025
Interpretable Evaluation of AI-Generated Content with Language-Grounded Sparse Encoders.
CoRR, August, 2025
BEnchmarking LLMs for Ophthalmology (BELO) for Ophthalmological Knowledge and Reasoning.
CoRR, July, 2025
JEDI: Latent End-to-end Diffusion Mitigates Agent-Human Performance Asymmetry in Model-Based Reinforcement Learning.
CoRR, May, 2025
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers.
CoRR, April, 2025
Benchmarking Next-Generation Reasoning-Focused Large Language Models in Ophthalmology: A Head-to-Head Evaluation on 5,888 Items.
CoRR, April, 2025
CoRR, February, 2025
Multi-Novelty: Improve the Diversity and Novelty of Contents Generated by Large Language Models via inference-time Multi-Views Brainstorming.
CoRR, February, 2025
Can OpenAI o1 Reason Well in Ophthalmology? A 6,990-Question Head-to-Head Evaluation Study.
CoRR, January, 2025
FedWeight: mitigating covariate shift of federated learning on electronic health records data through patients re-weighting.
npj Digit. Medicine, 2025
Uncertainty-Aware Multimodal Fusion for Reliable Fundus Disease Classification Using a Vision-Language Foundation Model.
Proceedings of the Ophthalmic Medical Image Analysis - 12th International Workshop, 2025
Uncertainty-Based Extensible Codebook for Discrete Federated Learning in Heterogeneous Data Silos.
Proceedings of the Forty-second International Conference on Machine Learning, 2025
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025
2024
BarlowTwins-CXR: enhancing chest X-ray abnormality localization in heterogeneous data with cross-domain self-supervised learning.
BMC Medical Informatics Decis. Mak., December, 2024
Trans. Mach. Learn. Res., 2024
Trans. Mach. Learn. Res., 2024
CoRR, 2024
CodeUnlearn: Amortized Zero-Shot Machine Unlearning in Language Models Using Discrete Concept.
CoRR, 2024
CoRR, 2024
CoRR, 2024
CoRR, 2024
Language Enhanced Model for Eye (LEME): An Open-Source Ophthalmology-Specific Large Language Model.
CoRR, 2024
CoRR, 2024
Common and Rare Fundus Diseases Identification Using Vision-Language Foundation Model with Knowledge of Over 400 Diseases.
CoRR, 2024
CoRR, 2024
Improve Robustness of Eye Disease Detection by including Learnable Probabilistic Discrete Latent Variables into Machine Learning Models.
CoRR, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
2023
Discrete Messages Improve Communication Efficiency among Isolated Intelligent Agents.
CoRR, 2023
Probabilistic Generative Modeling for Procedural Roundabout Generation for Developing Countries.
CoRR, 2023
Causal Inference in Gene Regulatory Networks with GFlowNet: Towards Scalability in Large Systems.
CoRR, 2023
Enhancing Human Capabilities through Symbiotic Artificial Intelligence with Shared Sensory Experiences.
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the International Conference on Machine Learning, 2023
Stateful Active Facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization for Heterogeneous Representational Coarseness.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
npj Digit. Medicine, 2022
Confederated learning in healthcare: Training machine learning models using disconnected data separated by individual, data type and identity for Large-Scale health system Intelligence.
J. Biomed. Informatics, 2022
Construction of extra-large scale screening tools for risks of severe mental illnesses using real world healthcare data.
CoRR, 2022
Graph-Based Active Machine Learning Method for Diverse and Novel Antimicrobial Peptides Generation and Selection.
CoRR, 2022
Coordinating Policies Among Multiple Agents via an Intelligent Communication Channel.
CoRR, 2022
FedILC: Weighted Geometric Mean and Invariant Gradient Covariance for Federated Learning on Non-IID Data.
CoRR, 2022
CoRR, 2022
PMFL: Partial Meta-Federated Learning for heterogeneous tasks and its applications on real-world medical records.
Proceedings of the IEEE International Conference on Big Data, 2022
2021
FeARH: Federated machine learning with anonymous random hybridization on electronic medical records.
J. Biomed. Informatics, 2021
PMFL: Partial Meta-Federated Learning for heterogeneous tasks and its applications on real-world medical records.
CoRR, 2021
FakeSafe: Human Level Steganography Techniques by Disinformation Mapping Using Cycle-Consistent Adversarial Network.
IEEE Access, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the First Workshop on Language Technology for Equality, 2021
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021
2020
FakeSafe: Human Level Data Protection by Disinformation Mapping using Cycle-consistent Adversarial Network.
CoRR, 2020
A machine learning methodology for real-time forecasting of the 2019-2020 COVID-19 outbreak using Internet searches, news alerts, and estimates from mechanistic models.
CoRR, 2020
Federated pretraining and fine tuning of BERT using clinical notes from multiple silos.
CoRR, 2020
Federated machine learning with Anonymous Random Hybridization (FeARH) on medical records.
CoRR, 2020
2019
Patient clustering improves efficiency of federated machine learning to predict mortality and hospital stay time using distributed electronic medical records.
J. Biomed. Informatics, 2019
CoRR, 2019
Privacy Preserving Stochastic Channel-Based Federated Learning with Neural Network Pruning.
CoRR, 2019
Confederated Machine Learning on Horizontally and Vertically Separated Medical Data for Large-Scale Health System Intelligence.
CoRR, 2019
Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records.
CoRR, 2019
Proceedings of the 18th BioNLP Workshop and Shared Task, 2019
High Performance Computing on Flat FHIR Files Created with the New SMART/HL7 Bulk Data Access Standard.
Proceedings of the AMIA 2019, 2019
2018
Artificial neural networks condensation: A strategy to facilitate adaption of machine learning in medical settings by reducing computational burden.
CoRR, 2018
Border Effect of Complex Network: An analysis on the cooperation network of movie stars across different regions.
CoRR, 2018
CoRR, 2018
CoRR, 2018
Genie: A Secure, Transparent Sharing and Services Platform for Genetic and Health Data.
CoRR, 2018
2017
DeepFaceLIFT: Interpretable Personalized Models for Automatic Estimation of Self-Reported Pain.
CoRR, 2017
DeepFaceLIFT: Interpretable Personalized Models for Automatic Estimation of Self-Reported Pain.
Proceedings of the 1st IJCAI Workshop on Artificial Intelligence in Affective Computing (AffComp 2017), 2017